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41419 Publications

Influence of gluconate on the retention of Eu(III), Am(III), Th(IV), Pu(IV), and U(VI) by C-S-H (C/S = 0.8)

Dettmann, S.; Huittinen, N. M.; Jahn, N.; Kretzschmar, J.; Kumke, M. U.; Kutyma, T.; Lohmann, J.; Reich, T.; Schmeide, K.; Shams Aldin Azzam, S.; Spittler, L.; Stietz, J.

The retention of actinides in different oxidation states (An(X), X = III, IV, VI) by a calcium-silicate-hydrate (C-S-H) phase with a Ca/Si (C/S) ratio of 0.8 was investigated in the presence of gluconate (GLU). The actinides considered were Am(III), Th(IV), Pu(IV), and U(VI). Eu(III) was investigated as chemical analogue for Am(III) and Cm(III). In addition to the ternary systems An(X)/GLU/C-S-H, also binary systems An(X)/C-S-H, GLU/C-S-H, and An(X)/GLU were studied. Complementary analytical techniques were applied to address the different specific aspects of the binary and ternary systems. Time-resolved laser-induced luminescence spectroscopy (TRLFS) was applied in combination with parallel factor analysis (PARAFAC) to identify retained species and to monitor species-selective sorption kinetics. 13C and 29Si magic-angle-spinning (MAS) nuclear magnetic resonance (NMR) spectroscopy and X-ray photoelectron spectroscopy (XPS) were applied to determine the bulk structure and the composition of the C-S-H surface, respectively, in the absence and presence of GLU. The interaction of Th(IV) with GLU in different electrolytes was studied by capillary electrophoresis-inductively coupled plasma mass spectrometry (CE-ICP-MS). The influence of GLU on An(X) retention was investigated for a large concentration range up to 10−2 M. The results showed that GLU had little to no effect on the overall An(X) retention by C-S-H with C/S of 0.8, regardless of the oxidation state of the actinides. For Eu(III), the TRLFS investigations additionally implied the formation of a Eu(III)-bearing precipitate with dissolved constituents of the C-S-H phase, which becomes structurally altered by the presence of GLU. For U(VI) sorption on the C-S-H phase, only a small influence of GLU could be established in the luminescence spectroscopic investigations, and no precipitation of U(VI)-containing secondary phases could be identified.

Keywords: actinide; organic ligand; sorption; cementitious material; concrete; luminescence

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Permalink: https://www.hzdr.de/publications/Publ-35722
Publ.-Id: 35722


Multisensor characterization of WEEE polymers: spectral fingerprints for the recycling industry

de Lima Ribeiro, A.; Fuchs, M.; Lorenz, S.; Röder, C.; Madriz Diaz, Y. C.; Herrmann, E.; Gloaguen, R.; Heitmann, J.

Waste from electronic equipment (WEEE) is a fast-growing complex waste stream, and plastics represent around 25% of its total. The proper recycling of plastics from WEEE depends on the identification of polymers prior to entering the recycling chain. Technologies aiming for this identification must be compatible with conveyor belt operations and fast data acquisition. Therefore, we selected three promising sensor types to investigate the potential of optical spectroscopy-based methods for identification of plastic constituents in WEEE. Reflectance information is obtained using Hyperspectral cameras (HSI) in the short-wave infrared (SWIR) and mid-wave infrared (MWIR). Raman point acquisitions are well-suited for specific plastic identification (532 nm excitation). Integration times varied according to the capabilities of each sensor, never exceeding 2 seconds. We have selected 23 polymers commonly found in WEEE (PE, PP, PVC ABS, PC, PS, PTFE, PMMA), recognising spectral fingerprints for each material according to literature reports. Spectral fingerprint identification was possible for 60% of the samples using SWIR-HSI; however, it failed to produce positive results for black plastics. Additional information from MWIR-HSI was used to identify two black samples (70% identified using SWIR + MWIR). Fingerprint assignment in short- time Raman acquisition (1 -2 seconds) was successful for all samples. Combined with the efficient mapping capabilities of HSI at time scales of milliseconds, further developments promise great potential for fast-paced recycling environments. Furthermore, integrated solutions enable increased accuracy (cross-validations) and hence, we recommend a combination of at least 2 sensors (SWIR + Raman or MWIR + Raman) for recycling activities.

Keywords: plastic; electronic waste; hyperspectral imagery; infrared; raman

  • Contribution to proceedings
    SPIE Photonics Europe - Optics, Photonics and Digital Technologies for Imaging Applications VII, 03.-07.04.2022, Strasbourg, France
    SPIE Proceedings Volume 12138, Optics, Photonics and Digital Technologies for Imaging Applications VII
    DOI: 10.1117/12.2632693
    Cited 1 times in Scopus

Permalink: https://www.hzdr.de/publications/Publ-35721
Publ.-Id: 35721


High-pressure investigations in CH₃NH₃PbX₃ (X = I, Br and Cl): suppression of ion migration and stabilization of low-temperature structure

Yuk, T. C.; Elliger, N.; Klis, B.; Kollar, M.; Horvath, E.; Forro, L.; Dressel, M.; Uykur, E.

Hybrid organic-inorganic halide perovskites represent a promising next-generation photovoltaic material with drawbacks on structure stability and composition concerns. Demonstrations of ion migration and molecular dynamics suggest room for structural contraction and subsequent property adjustments. Here, we have deployed dielectric and infrared spectroscopy under external pressure to probe the full structural phase diagram and dielectric response of methylammonium lead halide perovskites CH₃NH₃$PbX₃ (X = I, Br, or Cl). Ion migration can be fully suppressed by pressure beyond 4 GPa. The low-temperature orthorhombic phase transition can be gradually enhanced and stabilized at ambient conditions with increasing pressure. A slow relaxation mode, presumably the motion of the CH₃NH₃+ cation, is observed at lower pressure and is absent in the orthorhombic phase for every halide.

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Permalink: https://www.hzdr.de/publications/Publ-35720
Publ.-Id: 35720


Driving modular CARs through solid tumours and their microenvironment - a new era in cancer immunotherapy

Loureiro, L. R.

Chimeric antigen receptor (CAR) T-cell therapies are undoubtedly a promising approach in cancer immunotherapy and have revolutionized the treatment options for hematologic malignancies. Yet, their effectiveness is more limited and challenging when it comes to tackling solid tumours. Antigen escape, on-target off-tumour effects, and the immunosuppressive tumour microenvironment (TME) of solid tumours are among the main hurdles. Aiming for increased clinical safety and effectiveness, our group works with the adaptor CAR T-cell technologies named UniCAR and RevCAR. The versatility of the adaptor molecules used in these types of approaches allows not only the targeting of antigens expressed on the surface of tumour cells but also of key molecules expressed on immunosuppressive cells as well as immune checkpoint inhibitors. Given the features of such approaches and the ease in engineering the adaptor molecules, combinatorial targeting can be exploited to pave the way for improved and personalized immunotherapies.

  • Lecture (others)
    CENTRAL CLINICAL SCHOOL (CCS) SEMINAR SERIES, 14.10.2022, Melbourne, Australia

Permalink: https://www.hzdr.de/publications/Publ-35719
Publ.-Id: 35719


Immunotheranostic target modules suitable for imaging and navigation of UniCAR T-cells to strike FAP-expressing solid tumours and their microenvironment

Loureiro, L. R.; Neuber, C.; Hoffmann, L.; Kubeil, M.; Arndt, C.; Mitwasi, N.; Kegler, A.; Bergmann, R.; Feldmann, A.; Bachmann, M.

Chimeric antigen receptor (CAR) T-cells are unquestionably considered one of the most promising approaches in cancer immunotherapy. Nonetheless, mild to severe toxicities are associated with this approach which include e.g. on-target/off-tumour toxicities and cytokine release syndrome. Aiming for increased clinical safety, a modular universal CAR (UniCAR) platform was developed by our group in which UniCAR T-cells are exclusively activated in the presence of a target module (TM) that specifically establishes the cross-link between target cells and UniCAR T-cells. Fibroblast activation protein (FAP) is highly expressed on cancer-associated fibroblasts (CAFs) present in the tumour stroma and also found to be overexpressed in tumour cells. This protein plays an important role in promoting tumour growth, metastasis, and immunosuppression and has therefore been studied as a target for cancer diagnosis and treatment. Given this and the demonstrated efficacy, flexibility and switchability of the UniCAR system, currently demonstrated in phase I clinical trials, we hereby aimed to develop TMs targeting FAP that can be used for both immunotherapeutic and theranostic approaches. For that, the single-chain variable fragment (scFv) of an anti-human FAP mAb was fused to the peptide epitope E5B9 that is recognized by the UniCAR T-cells, creating low molecular weight TMs that are rapidly eliminated allowing a specific and recurrent on/off switch of UniCAR T-cell activity via TM dosing. Additionally, extended half-life anti-FAP TMs based on the human IgG4 Fc-domain, including a mutated version, were created intending to strengthen anti-tumour responses and to ease the clinical TM administration at later stages of tumour therapy. All TMs were tested in vitro based on naturally and artificially overexpressing 2D and 3D models, and proven to specifically redirect UniCAR T-cells to FAP-expressing target cells. Positron emission tomography (PET) using 64Cu radiolabelled anti-FAP IgG4 TMs demonstrated a FAP specific enrichment of these TMs at the tumour site of FAP overexpressing HT1080 xenografts resulting in a tumour SUV of 50 at 48h p.i. with almost no background. Single-photon emission tomography (SPECT) using 177Lu radiolabelled anti-FAP IgG4 TMs furthermore confirmed a high FAP-dependent tumour uptake. In conclusion, we hereby designed novel TMs targeting FAP with different formats that can be used for both endoradionuclide therapy and immunotherapeutic approaches using UniCAR T-cells, proving to be promising and innovative immunotheranostic tools to foster cancer treatment allowing a more convenient, individualized, and safe treatment of cancer patients.

  • Lecture (Conference)
    Australian Society of Molecular Imaging (ASMI) Conference 2022, 06.-07.10.2022, Melbourne, Australia

Permalink: https://www.hzdr.de/publications/Publ-35718
Publ.-Id: 35718


Interrelationship of Bulk and Oil-Water Interfacial Properties of Asphaltenes

Ashoorian, S.; Javadi, A.; Hosseinpour, N.; Nassar, N.

Prediction and control of the behavior of asphaltenes have always been one of the most challenging topics in the oil and gas industry. To this aim, comprehensive knowledge of the bulk and surface behavior of asphaltenes and the possible interrelationship are required. Many attempts have been done so far to scrutinize the behavior of asphaltenes at the oil/water interface. In this study, the changes in surface behavior of asphaltenes upon aromaticity variation in the bulk are investigated. For this purpose, dynamic light scattering (DLS) experiments are accompanied with dynamic interfacial tension (IFT), and interfacial rheology measurements to analyze the asphaltene aggregation size, mobility and surface activity upon a change in the bulk aromaticity. A wide range of aromatic conditions was used to cover possible changes in asphaltene behavior before and after the onset point. The results revealed that the interfacial activity and the structure of the interfacial film of the asphaltenes are significantly influenced by the bulk properties. Low aromaticity conditions led to an increase in asphaltene surface activity and changed the dilational rheological parameters considerably although the general trend of the asphaltene adsorption remained similar. Moreover, the results demonstrated the importance of the aging time on the measured parameters, particularly for the samples beyond the onset point. Our findings also showed the importance of dynamic interfacial data over static ones. Finally, by applying the concept of diffusion coefficient it was suggested that only a small portion of asphaltenes remain surface-active practically, although their surface activity is directly correlated with the system aromaticity.

Keywords: Asphaltene Adsorption; Dynamic Interfacial Tension; Interfacial Rheology; Dynamic Light Scattering; Asphaltene Onset Point; Diffusion Coefficient

Permalink: https://www.hzdr.de/publications/Publ-35717
Publ.-Id: 35717


The Outcome of the 2021 IEEE GRSS Data Fusion Contest—Track MSD: Multitemporal Semantic Change Detection

Li, Z.; Lu, F.; Zhang, H.; Tu, L.; Li, J.; Huang, X.; Robinson, C.; Malkin, N.; Jojic, N.; Ghamisi, P.; Hänsch, R.; Yokoya, N.

We present here the scientific outcomes of the 2021 Data Fusion Contest (DFC2021) organized by the Image Analysis and Data Fusion Technical Committee of the IEEE Geoscience and Remote Sensing Society. DFC2021 was dedicated to research on geospatial artificial intelligence (AI) for social good with a global objective of modeling the state and changes of artificial and natural environments from multimodal and multitemporal remotely sensed data toward sustainable developments. DFC2021 included two challenge tracks: “Detection of settlements without electricity” and “Multitemporal semantic change detection.” This article mainly focuses on the outcome of the multitemporal semantic change detection track. We describe in this article the DFC2021 dataset that remains available for further evaluation of corresponding approaches and report the results of the best-performing methods during the contest.

Permalink: https://www.hzdr.de/publications/Publ-35714
Publ.-Id: 35714


A Google Earth Engine Approach for Wildfire Susceptibility Prediction Fusion with Remote Sensing Data of Different Spatial Resolutions

Tavakkoli Piralilou, S.; Einali, G.; Ghorbanzadeh, O.; Nachappa, T. G.; Gholamnia, K.; Blaschke, T.; Ghamisi, P.

The effects of the spatial resolution of remote sensing (RS) data on wildfire susceptibility prediction are not fully understood. In this study, we evaluate the effects of coarse (Landsat 8 and SRTM) and medium (Sentinel-2 and ALOS) spatial resolution data on wildfire susceptibility prediction using random forest (RF) and support vector machine (SVM) models. In addition, we investigate the fusion of the predictions from the different spatial resolutions using the Dempster–Shafer theory (DST) and 14 wildfire conditioning factors. Seven factors are derived separately from the coarse and medium spatial resolution datasets for the whole forest area of the Guilan Province, Iran. All conditional factors are used to train and test the SVM and RF models in the Google Earth Engine (GEE) software environment, along with an inventory dataset from comprehensive global positioning system (GPS)-based field survey points of wildfire locations. These locations are evaluated and combined with coarse resolution satellite data, namely the thermal anomalies product of the moderate resolution imaging spectroradiometer (MODIS) for the period 2009 to 2019. We assess the performance of the models using four-fold cross-validation by the receiver operating characteristic (ROC) curve method. The area under the curve (AUC) achieved from the ROC curve yields 92.15% and 91.98% accuracy for the respective SVM and RF models for the coarse RS data. In comparison, the AUC for the medium RS data is 92.5% and 93.37%, respectively. Remarkably, the highest AUC value of 94.71% is achieved for the RF model where coarse and medium resolution datasets are combined through DST.

Permalink: https://www.hzdr.de/publications/Publ-35713
Publ.-Id: 35713


Rapid Mapping of Landslides from Sentinel-2 Data Using Unsupervised Deep Learning

Shahabi, H.; Rahimzad, M.; Ghorbanzadeh, O.; Piralilou, S. T.; Blaschke, T.; Homayouni, S.; Ghamisi, P.

This study investigates a pixel-based image analysis methodology built on unsupervised Deep Learning (DL) for rapid landslide detection. The utilized data includes the Minimum Noise Fraction (MNF) and Normalized Difference Vegetation Index (NDVI) derived from Sentinel-2 images and the topographic slope factor derived from the ALOS PALSAR sensor. We used a Convolutional auto-encoder (CAE) for extracting deep features from our input data. The Mini Batch K-means is then used for clustering the resulting deep features. The resulting landslide detection maps were then compared with a landslide inventory dataset for accuracy assessment. The proposed approach achieved the highest values of 76%, 91%, 83%, and 70% in terms of precision, recall, f1-score, and mIOU, respectively. This is the first study investigating unsupervised DL for landslide detection using Sentinel-2 images to the best of our knowledge.

  • Contribution to proceedings
    2022 IEEE Mediterranean and Middle-East Geoscience and Remote Sensing Symposium (M2GARSS), 07.03.2022, Istanbul, Turkey
    IEEE Mediterranean and Middle-East Geoscience and Remote Sensing Symposium (M2GARSS)
    DOI: 10.1109/M2GARSS52314.2022.9840273
    Cited 4 times in Scopus

Permalink: https://www.hzdr.de/publications/Publ-35712
Publ.-Id: 35712


Nonnegative-Constrained Joint Collaborative Representation with Union Dictionary for Hyperspectral Anomaly Detection

Chang, S.; Ghamisi, P.

Recently, many collaborative representation-based (CR) algorithms have been proposed for hyperspectral anomaly detection. CR-based detectors approximate the image by a linear combination of background dictionaries and the coefficient matrix, and derive the detection map by utilizing recovery residuals. However, these CR-based detectors are often established on the premise of precise background features and strong image representation, which are very difficult to obtain. In addition, pursuing the coefficient matrix reinforced by the general -min is very time consuming. To address these issues, a nonnegative-constrained joint collaborative representation model is proposed in this paper for the hyperspectral anomaly detection task. To extract reliable samples, a union dictionary consisting of background and anomaly sub-dictionaries is designed, where the background sub-dictionary is obtained at the superpixel level and the anomaly sub-dictionary is extracted by the pre-detection process. And the coefficient matrix is jointly optimized by the Frobenius norm regularization with a nonnegative constraint and a sum-to-one constraint. After the optimization process, the abnormal information is finally derived by calculating the residuals that exclude the assumed background information. To conduct comparable experiments, the proposed nonnegative-constrained joint collaborative representation (NJCR) model and its kernel version (KNJCR) are tested in four HSI data sets and achieve superior results compared with other state-of-the-art detectors.

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Permalink: https://www.hzdr.de/publications/Publ-35711
Publ.-Id: 35711


Landslide detection using deep learning and object-based image analysis

Ghorbanzadeh, O.; Shahabi, H.; Crivellari, A.; Homayouni, S.; Blaschke, T.; Ghamisi, P.

Recent landslide detection studies have focused on pixel-based deep learning (DL) approaches. In contrast, intuitive annotation of landslides from satellite imagery is based on distinct features rather than individual pixels. This study examines the feasibility of the integration framework of a DL model with rule-based object-based image analysis (OBIA) to detect landslides. First, we designed a ResU-Net model and then trained and tested it in the Sentinel-2 imagery. Then we developed a simple rule-based OBIA with only four rulesets, applying it first to the original image dataset and then to the same dataset plus the resulting ResU-Net heatmap. The value of each pixel in the heatmap refers to the probability that the pixel belongs to either landslide or non-landslide classes. Thus, we evaluate three scenarios: ResU-Net, OBIA, and ResU-Net-OBIA. The landslide detection maps from three different classification scenarios were compared against a manual landslide inventory map using thematic accuracy assessment metrics: precision, recall, and f1-score. Our experiments in the testing area showed that the proposed integration framework yields f1-score values 8 and 22 percentage points higher than those of the ResU-Net and OBIA approaches, respectively.

Permalink: https://www.hzdr.de/publications/Publ-35710
Publ.-Id: 35710


Leveraging OpenStreetMap and Multimodal Remote Sensing Data with Joint Deep Learning for Wastewater Treatment Plants Detection

Li, H.; Zech, J.; Hong, D.; Ghamisi, P.; Schultz, M.; Zipf, A.

Humans rely on clean water for their health, well-being, and various socio-economic activities. During the past few years, the COVID-19 pandemic has been a constant reminder of about the importance of hygiene and sanitation for public health. The most common approach to securing clean water supplies for this purpose is via wastewater treatment. To date, an effective method of detecting wastewater treatment plants (WWTP) accurately and automatically via remote sensing is unavailable. In this paper, we provide a solution to this task by proposing a novel joint deep learning (JDL) method that consists of a fine-tuned object detection network and a multi-task residual attention network (RAN). By leveraging OpenStreetMap (OSM) and multimodal remote sensing (RS) data, our JDL method is able to simultaneously tackle two different tasks: land use land cover (LULC) and WWTP classification. Moreover, JDL exploits the complementary effects between these tasks for a performance gain. We train JDL using 4,187 WWTP features and 4,200 LULC samples and validate the performance of the proposed method over a selected area around Stuttgart with 723 WWTP features and 1,200 LULC samples to generate an LULC classification map and a WWTP detection map. Extensive experiments conducted with different comparative methods demonstrate the effectiveness and efficiency of our JDL method in automatic WWTP detection in comparison with single-modality/single-task or traditional survey methods. Moreover, lessons learned pave the way for future works to simultaneously and effectively address multiple large-scale mapping tasks (e.g., both mapping LULC and detecting WWTP) from multimodal RS data via deep learning.

Permalink: https://www.hzdr.de/publications/Publ-35709
Publ.-Id: 35709


Asymmetric Hash Code Learning for Remote Sensing Image Retrieval

Song, W.; Gao, Z.; Dian, R.; Ghamisi, P.; Zhang, Y.; Benediktsson, J. A.

Remote sensing image retrieval (RSIR), aiming at searching for a set of similar items to a given query image, is a very important task in remote sensing applications. Deep hashing learning as the current mainstream method has achieved satisfactory retrieval performance. On one hand, various deep neural networks are used to extract semantic features of remote sensing images. On the other hand, the hashing techniques are subsequently adopted to map the high-dimensional deep features to the low-dimensional binary codes. This kind of method attempts to learn one hash function for both the query and database samples in a symmetric way. However, with the number of database samples increasing, it is typically time-consuming to generate the hash codes of large-scale database images. In this article, we propose a novel deep hashing method, named asymmetric hash code learning (AHCL), for RSIR. The proposed AHCL generates the hash codes of query and database images in an asymmetric way. In more detail, the hash codes of query images are obtained by binarizing the output of the network, while the hash codes of database images are directly learned by solving the designed objective function. In addition, we combine the semantic information of each image and the similarity information of pairs of images as supervised information to train a deep hashing network, which improves the representation ability of deep features and hash codes. The experimental results on three public datasets demonstrate that the proposed method outperforms symmetric methods in terms of retrieval accuracy and efficiency. The source code is available at https://github.com/weiweisong415/Demo_AHCL_for_TGRS2022 .

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Permalink: https://www.hzdr.de/publications/Publ-35708
Publ.-Id: 35708


MS2A-Net: Multiscale Spectral–Spatial Association Network for Hyperspectral Image Clustering

Shahi, K. R.; Ghamisi, P.; Rasti, B.; Gloaguen, R.; Scheunders, P.

Remote sensing hyperspectral cameras acquire high spectral-resolution data that reveal valuable composition information on the targets (e.g., for Earth observation and environmental applications). The intrinsic high dimensionality and the lack of sufficient numbers of labeled/training samples prevent efficient processing of hyperspectral images (HSIs). HSI clustering can alleviate these limitations. In this study, we propose a multiscale spectral–spatial association network (MS 2 A-Net) to cluster HSIs. The backbone of MS 2 A-Net is an autoencoder architecture that allows the network to capture the nonlinear relation between data points in an unsupervised manner. The network applies a multistream approach. One stream extracts spectral information by deploying a spectral association unit. The other stream derives multiscale contextual and spatial information by employing dilated (atrous) convolutional kernels. The obtained feature representation generated by MS 2 A-Net is fed into a standard k-means clustering algorithm to produce the final clustering result. Extensive experiments on four HSIs for different types of applications (i.e., geological-, rural-, and urban-mapping) demonstrate the superior performance of MS 2 A-Net over the state-of-the-art shallow/deep learning-based clustering approaches in terms of clustering accuracy.

Permalink: https://www.hzdr.de/publications/Publ-35707
Publ.-Id: 35707


Evaluation of Different Landslide Susceptibility Models for a Local Scale in the Chitral District, Northern Pakistan

Aslam, B.; Maqsoom, A.; Khalil, U.; Ghorbanzadeh, O.; Blaschke, T.; Farooq, D.; Tufail, R. F.; Suhail, S. A.; Ghamisi, P.

This work evaluates the performance of three machine learning (ML) techniques, namely logistic regression (LGR), linear regression (LR), and support vector machines (SVM), and two multi-criteria decision-making (MCDM) techniques, namely analytical hierarchy process (AHP) and the technique for order of preference by similarity to ideal solution (TOPSIS), for mapping landslide susceptibility in the Chitral district, northern Pakistan. Moreover, we create landslide inventory maps from LANDSAT-8 satellite images through the change vector analysis (CVA) change detection method. The change detection yields more than 500 landslide spots. After some manual post-processing correction, the landslide inventory spots are randomly split into two sets with a 70/30 ratio for training and validating the performance of the ML techniques. Sixteen topographical, hydrological, and geological landslide-related factors of the study area are prepared as GIS layers. They are used to produce landslide susceptibility maps (LSMs) with weighted overlay techniques using different weights of landslide-related factors. The accuracy assessment shows that the ML techniques outperform the MCDM methods, while SVM yields the highest accuracy of 88% for the resulting LSM.

Permalink: https://www.hzdr.de/publications/Publ-35706
Publ.-Id: 35706


Time Series of Remote Sensing Data for Interaction Analysis of the Vegetation Coverage and Dust Activity in the Middle East

Namdari, S.; Zghair Alnasrawi, A. I.; Ghorbanzadeh, O.; Sorooshian, A.; Kamran, K. V.; Ghamisi, P.

Motivated by the lack of research on land cover and dust activity in the Middle East, this study seeks to increase the understanding of the sensitivity of dust centers to climatic and surface conditions in this specific region. In this regard, we explore vegetation cover and dust emission interactions using 16-day long-term Normalized Difference Vegetation Index (NDVI) data and daily Aerosol Optical Depth (AOD) data from Moderate Resolution Imaging Spectroradiometer (MODIS) and conduct spatiotemporal and statistical analyses. Eight major dust hotspots were identified based on long-term AOD data (2000–2019). Despite the relatively uniform climate conditions prevailing throughout the region during the study period, there is considerable spatial variability in interannual relationships between AOD and NDVI. Three subsets of periods (2000–2006, 2007–2013, 2014–2019) were examined to assess periodic spatiotemporal changes. In the second period (2007–2013), AOD increased significantly (6% to 32%) across the studied hotspots, simultaneously with a decrease in NDVI (−0.9% to −14.3%) except in Yemen−Oman. Interannual changes over 20 years showed a strong relationship between reduced vegetation cover and increased dust intensity. The correlation between NDVI and AOD (−0.63) for the cumulative region confirms the significant effect of vegetation canopy on annual dust fluctuations. According to the results, changes in vegetation cover have an essential role in dust storm fluctuations. Therefore, this factor must be regarded along with wind speed and other climate factors in Middle East dust hotspots related to research and management efforts.

Permalink: https://www.hzdr.de/publications/Publ-35705
Publ.-Id: 35705


Supervised Contrastive Learning-Based Classification for Hyperspectral Image

Huang, L.; Chen, Y.; He, X.; Ghamisi, P.

Recently, deep learning methods, especially convolutional neural networks (CNNs), have achieved good performance for hyperspectral image (HSI) classification. However, due to limited training samples of HSIs and the high volume of trainable parameters in deep models, training deep CNN-based models is still a challenge. To address this issue, this study investigates contrastive learning (CL) as a pre-training strategy for HSI classification. Specifically, a supervised contrastive learning (SCL) framework, which pre-trains a feature encoder using an arbitrary number of positive and negative samples in a pair-wise optimization perspective, is proposed. Additionally, three techniques for better generalization in the case of limited training samples are explored in the proposed SCL framework. First, a spatial–spectral HSI data augmentation method, which is composed of multiscale and 3D random occlusion, is designed to generate diverse views for each HSI sample. Second, the features of the augmented views are stored in a queue during training, which enriches the positives and negatives in a mini-batch and thus leads to better convergence. Third, a multi-level similarity regularization method (MSR) combined with SCL (SCL–MSR) is proposed to regularize the similarities of the data pairs. After pre-training, a fully connected layer is combined with the pre-trained encoder to form a new network, which is then fine-tuned for final classification. The proposed methods (SCL and SCL–MSR) are evaluated on four widely used hyperspectral datasets: Indian Pines, Pavia University, Houston, and Chikusei. The experiment results show that the proposed SCL-based methods provide competitive classification accuracy compared to the state-of-the-art methods.

Permalink: https://www.hzdr.de/publications/Publ-35704
Publ.-Id: 35704


Deep Learning and Earth Observation to Support the Sustainable Development Goals: Current approaches, open challenges, and future opportunities

Persello, C.; Wegner, J. D.; Hänsch, R.; Tuia, D.; Ghamisi, P.; Koeva, M.; Camps-Valls, G.

The synergistic combination of deep learning (DL) models and Earth observation (EO) promises significant advances to support the Sustainable Development Goals (SDGs). New developments and a plethora of applications are already changing the way humanity will face the challenges of our planet. This article reviews current DL approaches for EO data, along with their applications toward monitoring and achieving the SDGs most impacted by the rapid development of DL in EO. We systematically review case studies to achieve zero hunger, create sustainable cities, deliver tenure security, mitigate and adapt to climate change, and preserve biodiversity. Important societal, economic, and environmental implications are covered. Exciting times are coming when algorithms and Earth data can help in our endeavor to address the climate crisis and support more sustainable development.

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Permalink: https://www.hzdr.de/publications/Publ-35703
Publ.-Id: 35703


Universal Adversarial Examples in Remote Sensing: Methodology and Benchmark

Xu, Y.; Ghamisi, P.

Deep neural networks have achieved great success in many important remote sensing tasks. Nevertheless, their vulnerability to adversarial examples should not be neglected. In this study, we systematically analyze the Universal Adversarial Examples in Remote Sensing (UAE-RS) data for the first time, without any knowledge from the victim model. Specifically, we propose a novel black-box adversarial attack method, namely, Mixup-Attack, and its simple variant Mixcut-Attack, for remote sensing data. The key idea of the proposed methods is to find common vulnerabilities among different networks by attacking the features in the shallow layer of a given surrogate model. Despite their simplicity, the proposed methods can generate transferable adversarial examples that deceive most of the state-of-the-art deep neural networks in both scene classification and semantic segmentation tasks with high success rates. We further provide the generated universal adversarial examples in the dataset named UAE-RS, which is the first dataset that provides black-box adversarial samples in the remote sensing field. We hope UAE-RS may serve as a benchmark that helps researchers design deep neural networks with strong resistance toward adversarial attacks in the remote sensing field. Codes and the UAE-RS dataset are available online ( https://github.com/YonghaoXu/UAE-RS ).

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Permalink: https://www.hzdr.de/publications/Publ-35701
Publ.-Id: 35701


Tailoring oxide quantum materials by ion beams

Wang, C.; Chang, C.-H.; Herklotz, A.; Kentsch, U.; Chen, D.; Chu, Y.-H.; Helm, M.; Zhou, S.

Complex oxides host a multitude of novel phenomena in condensed matter physics, such as various forms of multiferroicity, colossal magnetoresistance, quantum magnetism and superconductivity. Defect engineering via ion irradiation can be a useful knob to control these physical properties for future practical applications. Two prominent effects are disorder and uniaxial strain. Particularly, the uniaxial strain, manifesting as the elongation of the out-of-plane lattice spacing, is not limited to available substrates. In this contribution, we will take SrRuO3 thin films as an example to show the emerging properties upon defect engineering by ion irradiation. The irradiated SRO films exhibit a pronounced topological Hall effect in a wide temperature range from 5 to 80 K. It can be attributed to the emergence of Dzyaloshinskii–Moriya interaction as a result of artificial inversion symmetry breaking associated with the lattice defect engineering. Ion irradiation has been well developed for semiconductor-chip technology and is readily applicable for all kinds of oxide quantum materials.

Related publications

  • Poster
    LEAPS meets Quantum Technology, 15.-20.05.2022, La Biodola, Italy

Permalink: https://www.hzdr.de/publications/Publ-35700
Publ.-Id: 35700


Ultra-doped semiconductors and their photonic applications

Zhou, S.

Doping allows us to modify semiconductor materials for desired electrical and optical properties. The solubility limit is a fundamental barrier for dopants incorporated into a specific semiconductor. Ultra-doping or hyper-doping refers to doping a semiconductor much beyond the corresponding solid solubility limit and often results in exotic properties. In this talk, we show that ion implantation combined with flash lamp annealing in millisecond and pulsed laser melting in nanosecond can realize ultra-doping in widely used semiconductors, including Si [1-5], Ge [6-8] and GaAs [9]. Various dopants, from conventional shallow-level impurities to deep-level ones, can be substitutionally incorporated up to a few atomic percent. This leads to the insulator-to-metal transition and the large modification to the semiconductor bandgap. The ultra-doped semiconductors can be used as photodetectors and plasmonic elements [10]. Ion implantation followed by annealing is a well-established method to dope Si, being maturely integrated with the IC industry production line. Therefore, ultra-doped semiconductors can be a wafer-scale platform for photonics.

[1] M. Wang, et al., Phys. Rev. Applied. 10, 024054 (2018)
[2] M. Wang, et al., Phys. Rev. Applied. 11, 054039 (2019)
[3] M. Wang, et al., Phys. Rev. B 102, 085204 (2020)
[4] M. Wang, et al., Adv. Optical Mater. 9, 2001546 (2021)
[5] M. Wang, et al., Nanoscale, 14, 2826-2836 (2022)
[6] S. Prucnal, et al., Scientific Reports 6, 27643 (2016)
[7] S. Prucnal, et al., Phys. Rev. Materials 3, 054802 (2019)
[8] S. Prucnal, et al., New J. Phys. 22, 123036 (2020)
[9] J. Duan, et al., New J. Phys. 23, 083034 (2021)
[10] G. V. Naik, V.M. Shalaev, A. Boltasseva, Alternative Plasmonic Materials: Beyond Gold and Silver, Adv. Mater. 25, 3264 (2013).

Related publications

  • Lecture (others)
    Seminar at Department of Electrical and Photonics Engineering, Technical University of Denmark, 27.06.2022, Lyngby, Denmark

Permalink: https://www.hzdr.de/publications/Publ-35699
Publ.-Id: 35699


Sparsity Regularized Deep Subspace Clustering for Multicriterion-Based Hyperspectral Band Selection

Das, S.; Pratiher, S.; Kyal, C.; Ghamisi, P.

Hyperspectral images provide rich spectral information corresponding to visible and near-infrared imaging regions, facilitating accurate classification, object identification, and target detection. However, the high volume of data creates a computational challenge in processing. The band selection process identifies specific informative and discriminative spectral bands from the data to speed up the processing without impeding the performance. This article presents an application-independent band selection framework that utilizes improved sparse deep subspace clustering and introduces an efficient multicriteria-based representative band selection (BS). The proposed sparse deep subspace clustering approach efficiently identifies the underlying nonlinear subspace structure of the data and organizes the data accordingly. The work introduces a novel, robust sparsity measure to obtain a powerful self-representation and ameliorated performance compared to the prevalent subspace clustering methods. The work subsequently selects the representative bands from each cluster by combining structural information of the band images with the statistical similarity measure. We evaluate the BS performance on standard real images using information-theoretic criterion, classification, and unmixing performance. The comparative performance assessment demonstrates that our proposed method identifies the informative bands and outperforms the other approaches in terms of the subsequent tasks.

Permalink: https://www.hzdr.de/publications/Publ-35698
Publ.-Id: 35698


Tellurium hyperdoped Silicon

Zhou, S.

Tellurium is one of the deep-level impurities in Si, leading to states of 200-400 meV below the conduction band. Non-equilibrium methods allow for doping deep-level impurities in Si well above the solubility limit, referred as hyperdoping, that can result in exotic properties, such as extrinsic photo-absorption well below the Si bandgap [1]. In this contribution, we will present an overview about Te hyperdoped Si. The hyperdoping is realized by ion implantation and pulsed laser melting. We will present the resulting optical, electrical properties and the perspective applications as infrared photodetectors. With increasing the Te concentration, the samples undergo an insulator to metal transition [2,3]. The metallic phase is governed by a power law dependence of the conductivity at temperatures below 25 K, whereas the conductivity in the insulating phase is well described by a variable-range hopping mechanism with a Coulomb gap. Surprisingly, the electron concentration obtained in Te-hyperdoped Si is approaching 10 21 cm-3 and does not show saturation [4]. It is even high than that of P or As doped Si and potentially meets the criteria of source/drain applications in future nanoelectronics. The infrared optical absorptance is found to increase with increasing dopant concentration [2]. We demonstrate the room-temperature operation of a mid-infrared photodetector based on Te-hyperdoped Si. The key parameters, such as the detectivity, the bandwidth and the rise/fall time, show competitiveness with the commercial products [5]. To
understand the microscopic picture, we have performed Rutherford backscattering/channeling angular scans and first-princiles calcluations [4]. The Te-dimer complex sitting on adjacent Si lattice sites has the smallest formation energy and is thus the preferred configuration at high doping concentration. Those substitutional Te-dimers are effective donors, leading to the insulator-to-metal transition, the non-saturating carrier concentration as well as the sub-band photoresponse. Moreover, the Te-hyperdoped Si layers exhibit thermal stability up to 400 °C with a duration of at least 10 minutes [6]. Therefore, Te-hyperdoped Si presents a test-bed for electrical and optical applications utilizing deep-level impurities.
[1] J. M. Warrender, Laser hyperdoping silicon for enhanced infrared optoelectronic properties, Appl. Phys.Rev. 3, 031104 (2016).
[2] M. Wang, ..., S. Zhou, Extended Infrared Photoresponse in Te-Hyperdoped Si at Room Temperature, Phys.Rev. Appl. 10, 024054 (2018).
[3] M. Wang, ..., S. Zhou, Critical behavior of the insulator-to-metal transition in Te-hyperdoped Si, Phys. Rev.B 102, 085204 (2020).
[4] M. Wang, ... Breaking the doping limit in silicon by deep impurities, Phys. Rev. Appl. 11, 054039 (2019).
[5] M. Wang, ..., S. Zhou, Silicon-Based Intermediate-Band Infrared Photodetector Realized by Te Hyperdoping, Adv. Opt. Mater. 9, 2001546, (2020).
[6] M. Wang, ..., S. Zhou, Thermal stability of Te-hyperdoped Si: Atomic-scale correlation of the structural, electrical, and optical properties, Phys. Rev. Mater. 3, 044606 (2019).

Related publications

  • Lecture (Conference)
    19th Conference on Gettering and Defect Engineering in Semiconductor Technology, 10.-16.09.2022, Mondsee, Austria

Permalink: https://www.hzdr.de/publications/Publ-35697
Publ.-Id: 35697


Superpixel Contracted Neighborhood Contrastive Subspace Clustering Network for Hyperspectral Images

Cai, Y.; Zhang, Z.; Ghamisi, P.; Ding, Y.; Liu, X.; Cai, Z.; Gloaguen, R.

Deep subspace clustering (DSC) has achieved remarkable performances in the unsupervised classification of hyperspectral images. However, previous models based on pixel-level self-expressiveness of data suffer from the exponential growth of computational complexity and access memory requirements with an increasing number of samples, thus leading to poor applicability to large hyperspectral images. This article presents a neighborhood contrastive subspace clustering (NCSC) network, a scalable and robust DSC approach, for unsupervised classification of large hyperspectral images. Instead of using a conventional autoencoder, we devise a novel superpixel pooling autoencoder to learn the superpixel-level latent representation and subspace, allowing a contracted self-expressive layer. To encourage a robust subspace representation, we propose a novel neighborhood contrastive regularization to maximize the agreement between positive samples in subspace. We jointly train the resulting model in an end-to-end fashion by optimizing an adaptively weighted multitask loss. Extensive experiments on three hyperspectral benchmarks demonstrate the effectiveness of the proposed approach and its substantial advancement of state-of-the-art approaches.

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Permalink: https://www.hzdr.de/publications/Publ-35696
Publ.-Id: 35696


Semisupervised Hyperspectral Image Classification Using a Probabilistic Pseudo-Label Generation Framework

Seydgar, M.; Rahnamayan, S.; Ghamisi, P.; Bidgoli, A. A.

Deep neural networks (DNNs) show impressive performance for hyperspectral image (HSI) classification when abundant labeled samples are available. The problem is that HSI sample annotation is extremely costly and the budget for this task is usually limited. To reduce the reliance on labeled samples, deep semisupervised learning (SSL), which jointly learns from labeled and unlabeled samples, has been introduced in the literature. However, learning robust and discriminative features from unlabeled data is a challenging task due to various noise effects and ambiguity of unlabeled samples. As a result, recent advances are constrained, mainly in the pretraining or warm-up stage. In this article, we propose a deep probabilistic framework to generate reliable pseudo-labels to explicitly learn discriminative features from unlabeled samples. The generated pseudo-labels of our proposed framework can be fed to various DNNs to improve their generalization capacity. Our proposed framework takes only ten labeled samples per class to represent the label set as an uncertainty-aware distribution (We use the Gaussian distribution to represent the uncertainty of the label set in the latent space.) in the latent space. The pseudo-labels are then generated for those unlabeled samples whose feature values match the distribution with high probability. By performing extensive experiments on four publicly available datasets, we show that our framework can generate reliable pseudo-labels to significantly improve the generalization capacity of several state-of-the-art DNNs. In addition, we introduce a new DNN for HSI classification that demonstrates outstanding accuracy results in comparison with its rivals.

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  • Secondary publication expected

Permalink: https://www.hzdr.de/publications/Publ-35695
Publ.-Id: 35695


Ferromagnetism and superconductivity in hyperdoped semiconductors

Zhou, S.

Doping allows us to modify semiconductor materials for desired electrical, optical and magnetic properties. The solubility limit is a fundamental barrier for dopants incorporated into a specific semiconductor. Hyperdoping refers to doping a semiconductor much beyond the corresponding solid solubility limit and often results in exotic properties. In this talk, we show that ion implantation combined with flash lamp annealing in millisecond and pulsed laser melting in nanosecond can be a versatile approach to fabricate hyperdoped semiconductors. Mn hyperdoped III-V compound semiconductors become ferromagnetic, where Mn impurities are in 2+ valence and providing local moments of 5 μB and free holes [1-5]. Their Curie temperatures can be varied either by the Mn or free hole concentration, and also depend on the host semiconductors, which reveal different pd exchange strength. On the other hand, Ga and Al hyperdoped Ge exhibits superconductivity with controllable critical temperature [6, 7]. In combination with first-principles calculation, phonon-mediated superconductivity is counted for the mechanism. The critical-field reveals significant difference when the field is in-plane or out-of-plane. This remarkable anisotropy may be considered as proof that Ga is incorporated in the Ge matrix homogeneously in a thin layer. Ion implantation followed by annealing is a well-established method to dope Si and Ge, being maturely integrated with the IC industry production line. We propose ferromagnetic and superconducting semiconductors prepared by ion implantation can be a scalable platform for quantum technology.

[1] M. Khalid, et al., Phys. Rev. B 89, 121301(R) (2014).
[2] S. Zhou, J. Phys. D: Appl. Phys. 48, 263001(2015).
[3] S. Prucnal, et al., Phys. Rev. B 92, 222407 (2015).
[4] Y. Yuan, et al., ACS Appl. Mater. Interfaces, 8, 3912 (2016).
[5] Y. Yuan, et al., Phys. Rev. Mater. 1, 054401 (2017).
[6] T. Herrmannsdörfer, et al., Phys. Rev. Lett. 102, 217003 (2009).
[7] S. Prucnal, et al., Phys. Rev. Materials 3 054802 (2019).

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  • Lecture (others)
    Condensed Matter Seminar Series at Niels Bohr Institute, University of Copenhagen, 24.06.2022, University of Copenhagen, Denmark

Permalink: https://www.hzdr.de/publications/Publ-35694
Publ.-Id: 35694


HyperViTGAN: Semisupervised Generative Adversarial Network With Transformer for Hyperspectral Image Classification

He, Z.; Xia, K.; Ghamisi, P.; Hu, Y.; Fan, S.; Zu, B.

Generative adversarial networks (GANs) have achieved many excellent results in hyperspectral image (HSI) classification in recent years, as GANs can effectively solve the dilemma of limited training samples in HSI classification. However, due to the class imbalance problem of HSI data, GANs always associate minority-class samples with fake label. To address this issue, we first propose a semisupervised generative adversarial network incorporating a transformer, called HyperViTGAN. The proposed HyperViTGAN is designed with an external semisupervised classifier to avoid self-contradiction when the discriminator performs both classification and discrimination tasks. The generator and discriminator with skip connection are utilized to generate HSI patches by adversarial learning. The proposed HyperViTGAN captures semantic context and low-level textures to reduce the loss of critical information. In addition, the generalization ability of the HyperViTGAN is improved through the use of data augmentation. Experimental results on three well-known HSI datasets, Houston 2013, Indian Pines 2010, and Xuzhou, show that the proposed model achieves competitive HSI classification performance in comparison with the current state-of-the-art classification models.

Permalink: https://www.hzdr.de/publications/Publ-35693
Publ.-Id: 35693


Doping semiconductors by ion implantation and subsecond annealing

Zhou, S.

Doping allows us to modify semiconductor materials for desired electrical, optical and magnetic properties. The solubility limit is a fundamental barrier for dopants incorporated into a specific semiconductor. Hyperdoping refers to doping a semiconductor much beyond the corresponding solid solubility limit and often results in exotic properties. For example, Ga hyperdoped Ge reveals superconductivity and Mn hyperdoped GaAs represents a typical ferromagnetic semiconductor. Ion implantation followed by annealing is a well-established method to dope Si and Ge. This approach has been maturely integrated with the IC industry production line. However, being applied to hyperdoping, the annealing duration has to be shortenedto millisecond or even nanosecond. The intrinsic physical parameters related to dopants and semiconductors (e.g. Solubility, diffusivity, melting point and thermal conductivity) have to be considered to choose the right annealing time regime. In this talk, we propose that ion implantation combined with flash lamp annealing in millisecond and pulsed laser melting in nanosecond can be a versatile approach to fabricate hyperdoped semiconductors. The examples include magnetic semiconductors [1-5], superconducting Ge [6] and chalcogen doped Si [10-12].
[1] M. Khalid, et al., Phys. Rev. B 89, 121301(R) (2014).
[2] S. Zhou, J. Phys. D: Appl. Phys. 48, 263001(2015).
[3] S. Prucnal, et al., Phys. Rev. B 92, 222407 (2015).
[4] Y. Yuan, et al., ACS Appl. Mater. Interfaces, 8, 3912 (2016).
[5] Y. Yuan, et al., Phys. Rev. Mater. 1, 054401 (2017).
[6] S. Prucnal, et al., Phys. Rev. Materials 3, 054802 (2019).
[7] S. Prucnal, et al., New J. Phys., 22 123036 (2020).
[8] M. Wang, et al., Phys. Rev. Applied. 10, 024054 (2018).
[9] M. Wang, et al., Phys. Rev. Applied. 11, 054039 (2019).
[10] M. Wang, et al., Nanoscale 14, 2826 (2022).

Related publications

  • Lecture (others)
    Seminar at CNRS / Université Paris-Sud, 02.12.2022, CNRS / Université Paris-Sud, France

Permalink: https://www.hzdr.de/publications/Publ-35692
Publ.-Id: 35692


Transferring CNN With Adaptive Learning for Remote Sensing Scene Classification

Wang, W.; Chen, Y.; Ghamisi, P.

Accurate classification of remote sensing (RS) images is a perennial topic of interest in the RS community. Recently, transfer learning, especially for fine-tuning pretrained convolutional neural networks (CNNs), has been proposed as a feasible strategy for RS scene classification. However, because the target domain (i.e., the RS images) and the source domain (e.g., ImageNet) are quite different, simply using the model pretrained on an ImageNet dataset presents some difficulties. The RS images and the pretrained models need to be properly adjusted to build a better classification system. In this study, an adaptive learning strategy for transferring a CNN-based model is proposed. First, an adaptive transform is used to adjust the original size of the RS image to a certain size, which is tailored to the input of the subsequent pretrained model. Then, an adaptive transferring model is proposed to automatically learn what knowledge from the pretrained model should be transferred to the RS scene classification model. Finally, in combination with a label smoothing approach, an adaptive label is presented to generate soft labels based on the statistics of the classification model predictions for each category, which is beneficial for learning the relationships between the target and nontarget categories of scenes. In general, the proposed methods adaptively manage the input, model, and label simultaneously, which leads to better classification performance for RS scene classification. The proposed methods are tested on three widely used datasets, and the obtained results show that the proposed methods provide competitive classification accuracy compared to the state-of-the-art methods.

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Permalink: https://www.hzdr.de/publications/Publ-35691
Publ.-Id: 35691


Mixed Noise Removal for Hyperspectral Image With l0-l1−2SSTV Regularization

Zhang, L.; Qian, Y.; Han, J.; Duan, P.; Ghamisi, P.

Hyperspectral images (HSIs) are usually corrupted by various types of mixed noises, which degrades the qualities of acquired images and limits the subsequent applications. In this article, we propose a novel denoised method based on a hybrid spatial–spectral total variation (SSTV) regularization, which we refer to as l0 - l1−2 SSTV. Specifically, l0 - l1−2 SSTV can be treated as an integrated regularization embedding spatial–spectral l0 gradient model into l1−2 SSTV. l1−2 SSTV regularization exploits the sparse structures in both spatial and spectral domains. Hence, the correlations within HSIs are fully considered. Due to the good performance of l1−2 -norm in image restoration, l1−2 SSTV gives a tighter approximation for the gradient domains of HSIs. It can effectively avoid artifacts and oversmoothing caused by the limitation of the SSTV regularization based on l1 -norm ( l1 SSTV). Meanwhile, the l0 gradient regularization controls the number of nonzero gradients to promote the local piecewise smoothness, making denoised images preserve clear edges. With the effective combination of l1−2 SSTV and l0 gradient regularization, l0 - l1−2 SSTV produces high-quality restoration results in the denoising process: better detail preservation and sharper edges. The augmented Lagrangian method and the difference of convex algorithm are exploited to optimize the proposed model. The results for simulated and real experiments demonstrate the effectiveness and superiority of the proposed method compared with state-of-the-art methods.

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Permalink: https://www.hzdr.de/publications/Publ-35690
Publ.-Id: 35690


Optical Remote Sensing Image Understanding With Weak Supervision: Concepts, methods, and perspectives

Yue, J.; Fang, L.; Ghamisi, P.; Xie, W.; Li, J.; Chanussot, J.; Plaza, A.

In recent years, supervised learning has been widely used in various tasks of optical remote sensing image (RSI) understanding, including RSI classification, pixel-wise segmentation, change detection, and object detection. The methods based on supervised learning need a large amount of high-quality training data, and their performance highly depends on the quality of the labels. However, in practical remote sensing applications, it is often expensive and time consuming to obtain large-scale data sets with high-quality labels, which leads to a lack of sufficient supervised information. In some cases, only coarse-grained labels can be obtained, resulting in the lack of exact supervision. In addition, the supervised information obtained manually may be wrong, resulting in a lack of accurate supervision. Therefore, RSI understanding often faces the problems of incomplete, inexact, and inaccurate supervised information, which will affect the breadth and depth of remote sensing applications.

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Permalink: https://www.hzdr.de/publications/Publ-35689
Publ.-Id: 35689


Microdialysis reveals anti-inflammatory effects of sulfated glycosaminoglycanes in the early phase of bone healing

Schulze, S.; Neuber, C.; Möller, S.; Pietzsch, J.; Schaser, K.-D.; Rammelt, S.

Although chronic inflammation inhibits bone healing, the healing process is initiated by an inflammatory phase. In a well-tuned sequence of molecular events, pro-inflammatory cytokines
are secreted to orchestrate the inflammation response to injury and the recruitment of progenitor cells. These events in turn activate the secretion of anti-inflammatory signaling molecules and attract cells and mediators that antagonize the inflammation and initiate the repair phase. Sulfated glycosaminoglycanes (sGAG) are known to interact with cytokines, chemokines and growth factors and, thus, alter the availability, duration and impact of those mediators on the local molecular level. sGAG-coated polycaprolactone-co-lactide (PCL) scaffolds were inserted into critical-size femur defects in adult male Wistar rats. The femur was stabilized with a plate, and the defect was filled with either sGAG-containing PCL scaffolds or autologous bone (positive control). Wound fluid samples obtained by microdialysis were characterized regarding alterations of cytokine concentrations over the first 24 h after surgery. The analyses revealed the inhibition of the pro-inflammatory cytokines IL-1β and MIP-2 in the sGAG-treated groups compared to the positive control. A simultaneous increase of IL-6 and TNF-α indicated advanced regenerative capacity of sGAG, suggesting their potential to improve bone healing.

Permalink: https://www.hzdr.de/publications/Publ-35688
Publ.-Id: 35688


NFANet: A Novel Method for Weakly Supervised Water Extraction From High-Resolution Remote-Sensing Imagery

Lu, M.; Fang, L.; Li, M.; Zhang, B.; Zhang, Y.; Ghamisi, P.

The use of deep learning for water extraction requires precise pixel-level labels. However, it is very difficult to label high-resolution remote-sensing images at the pixel level. Therefore, we study how to utilize point labels to extract water bodies and propose a novel method called the neighbor feature aggregation network (NFANet). Compared with pixel-level labels, point labels are much easier to obtain, but they will lose much information. In this article, we take advantage of the similarity between the adjacent pixels of a local water body, and propose a neighbor sampler to resample remote-sensing images. Then, the sampled images are sent to the network for feature aggregation. In addition, we use an improved recursive training algorithm to further improve the extraction accuracy, making the water boundary more natural. Furthermore, our method utilizes neighboring features instead of global or local features to learn more representative features. The experimental results show that the proposed NFANet method not only outperforms other studied weakly supervised approaches, but also obtains similar results as the state-of-the-art ones.

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Permalink: https://www.hzdr.de/publications/Publ-35687
Publ.-Id: 35687


Deep Semantic Segmentation of Trees Using Multispectral Images

Ulku, I.; Akagündüz, E.; Ghamisi, P.

Forests can be efficiently monitored by automatic semantic segmentation of trees using satellite and/or aerial images. Still, several challenges can make the problem difficult, including the varying spectral signature of different trees, lack of sufficient labelled data, and geometrical occlusions. In this article, we address the tree segmentation problem using multispectral imagery. While we carry out large-scale experiments on several deep learning architectures using various spectral input combinations, we also attempt to explore whether hand-crafted spectral vegetation indices can improve the performance of deep learning models in the segmentation of trees. Our experiments include benchmarking a variety of multispectral remote sensing image sets, deep semantic segmentation architectures, and various spectral bands as inputs, including a number of hand-crafted spectral vegetation indices. From our large-scale experiments, we draw several useful conclusions. One particularly important conclusion is that, with no additional computation burden, combining different categories of multispectral vegetation indices, such as NVDI, atmospherically resistant vegetation index, and soil-adjusted vegetation index, within a single three-channel input, and using the state-of-the-art semantic segmentation architectures, tree segmentation accuracy can be improved under certain conditions, compared to using high-resolution visible and/or near-infrared input.

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Permalink: https://www.hzdr.de/publications/Publ-35686
Publ.-Id: 35686


Sketched Multiview Subspace Learning for Hyperspectral Anomalous Change Detection

Chang, S.; Kopp, M.; Ghamisi, P.

In recent years, multiview subspace learning has been garnering increasing attention. It aims to capture the inner relationships of the data that are collected from multiple sources by learning a unified representation. In this way, comprehensive information from multiple views is shared and preserved for the generalization processes. As a special branch of temporal series hyperspectral image (HSI) processing, the anomalous change detection (ACD) task focuses on detecting very small changes among different temporal images. However, when the volume of datasets is very large or the classes are relatively comprehensive, the existing methods may fail to find those changes between the scenes, and end up with terrible detection results. In this article, inspired by the sketched representation and multiview subspace learning, a sketched multiview subspace learning (SMSL) model is proposed for HSI ACD. The proposed model preserves major information from the image pairs and improves the computational complexity using a sketched representation matrix. Furthermore, the differences between scenes are extracted using the specific regularizer of the self-representation matrices. To evaluate the detection effectiveness of the proposed SMSL model, experiments are conducted on a benchmark hyperspectral remote sensing dataset and a natural hyperspectral dataset and compared with other state-of-the-art approaches. The code of the proposed method will be available at https://github.com/ShizhenChang/SMSL .

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Permalink: https://www.hzdr.de/publications/Publ-35685
Publ.-Id: 35685


Deep Bilateral Filtering Network for Point-Supervised Semantic Segmentation in Remote Sensing Images

Wu, L.; Fang, L.; Yue, J.; Zhang, B.; Ghamisi, P.; He, M.

Semantic segmentation methods based on deep neural networks have achieved great success in recent years. However, training such deep neural networks relies heavily on a large number of images with accurate pixel-level labels, which requires a huge amount of human effort, especially for large-scale remote sensing images. In this paper, we propose a point-based weakly supervised learning framework called the deep bilateral filtering network (DBFNet) for the semantic segmentation of remote sensing images. Compared with pixel-level labels, point annotations are usually sparse and cannot reveal the complete structure of the objects; they also lack boundary information, thus resulting in incomplete prediction within the object and the loss of object boundaries. To address these problems, we incorporate the bilateral filtering technique into deeply learned representations in two respects. First, since a target object contains smooth regions that always belong to the same category, we perform deep bilateral filtering (DBF) to filter the deep features by a nonlinear combination of nearby feature values, which encourages the nearby and similar features to become closer, thus achieving a consistent prediction in the smooth region. In addition, the DBF can distinguish the boundary by enlarging the distance between the features on different sides of the edge, thus preserving the boundary information well. Experimental results on two widely used datasets, the ISPRS 2-D semantic labeling Potsdam and Vaihingen datasets, demonstrate that our proposed DBFNet can achieve a highly competitive performance compared with state-of-the-art fully-supervised methods. Code is available at https://github.com/Luffy03/DBFNet .

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Permalink: https://www.hzdr.de/publications/Publ-35684
Publ.-Id: 35684


The Outcome of the 2022 Landslide4Sense Competition: Advanced Landslide Detection From Multisource Satellite Imagery

Ghorbanzadeh, O.; Xu, Y.; Zhao, H.; Wang, J.; Zhong, Y.; Zhao, D.; Zang, Q.; Wang, S.; Zhang, F.; Shi, Y.; Zhu, X. X.; Bai, L.; Li, W.; Peng, W.; Ghamisi, P.

The scientific outcomes of the 2022 Landslide4Sense (L4S) competition organized by the Institute of Advanced Research in Artificial Intelligence are presented here. The objective of the competition is to automatically detect landslides based on large-scale multiple sources of satellite imagery collected globally. The 2022 L4S aims to foster interdisciplinary research on recent developments in deep learning (DL) models for the semantic segmentation task using satellite imagery. Over the past few years, DL-based models have achieved performance that meets expectations on image interpretation due to the development of convolutional neural networks. The main objective of this article is to present the details and the best-performing algorithms featured in this competition. The winning solutions are elaborated with state-of-the-art models, such as the Swin Transformer, SegFormer, and U-Net. Advanced machine learning techniques and strategies, such as hard example mining, self-training, and mix-up data augmentation, are also considered. Moreover, we describe the L4S benchmark dataset in order to facilitate further comparisons and report the results of the accuracy assessment online. The data are accessible on Future Development Leaderboard for future evaluation at https://www.iarai.ac.at/landslide4sense/challenge/ , and researchers are invited to submit more prediction results, evaluate the accuracy of their methods, compare them with those of other users, and, ideally, improve the landslide detection results reported in this article.

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Permalink: https://www.hzdr.de/publications/Publ-35683
Publ.-Id: 35683


Consistency-Regularized Region-Growing Network for Semantic Segmentation of Urban Scenes With Point-Level Annotations

Xu, Y.; Ghamisi, P.

Deep learning algorithms have obtained great success in semantic segmentation of very high-resolution (VHR) remote sensing images. Nevertheless, training these models generally requires a large amount of accurate pixel-wise annotations, which is very laborious and time-consuming to collect. To reduce the annotation burden, this paper proposes a consistency-regularized region-growing network (CRGNet) to achieve semantic segmentation of VHR remote sensing images with point-level annotations. The key idea of CRGNet is to iteratively select unlabeled pixels with high confidence to expand the annotated area from the original sparse points. However, since there may exist some errors and noises in the expanded annotations, directly learning from them may mislead the training of the network. To this end, we further propose the consistency regularization strategy, where a base classifier and an expanded classifier are employed. Specifically, the base classifier is supervised by the original sparse annotations, while the expanded classifier aims to learn from the expanded annotations generated by the base classifier with the region-growing mechanism. The consistency regularization is thereby achieved by minimizing the discrepancy between the predictions from both the base and the expanded classifiers. We find such a simple regularization strategy is yet very useful to control the quality of the region-growing mechanism. Extensive experiments on two benchmark datasets demonstrate that the proposed CRGNet significantly outperforms the existing state-of-the-art methods. Codes and pre-trained models are available online ( https://github.com/YonghaoXu/CRGNet ).

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Permalink: https://www.hzdr.de/publications/Publ-35682
Publ.-Id: 35682


(Data set) Effect of magnetism and phonons on localized carriers in ferrimagnetic kagome metals GdMn6Sn6 and TbMn6Sn6

Wenzel, M.; Tsirlin, A. A.; Iakutkina, O.; Yin, Q.; Lei, H. C.; Dressel, M.; Uykur, E.

  1. Data from the publication are given in Origin format with Figure codes.
  2. More data are available upon request.

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Permalink: https://www.hzdr.de/publications/Publ-35681
Publ.-Id: 35681


(Data set) Effect of nonhydrostatic pressure on the superconducting kagome metal CsV₃Sb₅

Tsirlin, A. A.; Ortiz, B. R.; Dressel, M.; Wilson, S. D.; Winnerl, S.; Uykur, E.

  1. Data from the publication are given in Origin format with Figure codes.
  2. More data are available upon request.

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Permalink: https://www.hzdr.de/publications/Publ-35680
Publ.-Id: 35680


Geospatial flow data extraction and visualization using Earth mover's distance

Mertel, A.; Calabrese, J.

A flow map is a common visualization technique displaying the significant trends and changes in data over a given spatial and temporal domain. While most flow maps are constructed using trajectory datasets as input, only a few research initiatives focus on producing flow maps from other data forms. This paper uses the Earth Mover's Distance to extract flows from geospatial data in two consecutive temporal snapshots. We further perform a generalization of the flows to avoid visual cluttering. To demonstrate the proposed approach, we provide an interactive web application where the user can see the pre-calculated flows extracted from the 2021 COVID incidence data in the regions of Germany, Poland, and Czechia.

Keywords: flow extraction; geospatial visualization; Earth mover's distance

  • Poster
    VIS22, 15.-21.10.2022, Oklahoma City, USA

Permalink: https://www.hzdr.de/publications/Publ-35679
Publ.-Id: 35679


Topological Hall effect arising from the mesoscopic and microscopic non-coplanar magnetic structure in MnBi

He, Y.; Schneider, S.; Helm, T.; Gayles, J.; Wolf, D.; Soldatov, I.; Borrmann, H.; Schnelle, W.; Schaefer, R.; Fecher, G. H.; Rellinghaus, B.; Felser, C.

The topological Hall effect (THE), induced by the Berry curvature that originates from non-zero scalar spin chirality, is an important feature for mesoscopic topological structures, such as skyrmions. However, the THE might also arise from other microscopic non-coplanar spin structures in the lattice. Thus, the origin of the THE inevitably needs to be determined to fully understand skyrmions and find new host materials. Here, we examine the Hall effect in both, bulk- and micron-sized lamellar samples of MnBi. The sample size affects the temperature and field range in which the THE is detectable. Although a bulk sample ex- hibits the THE only upon exposure to weak fields in the easy-cone state, in micron-sized lamella the THE exists across a wide temperature range and occurs at fields near saturation. Our results show that both the non-coplanar spin structure in the lattice and topologically non-trivial skyrmion bubbles are respon- sible for the THE, and that the dominant mechanism depends on the sample size. Hence, the magnetic phase diagram for MnBi is size-dependent. Our study provides an example in which the THE is simulta- neously induced by two mechanisms, and builds a bridge between mesoscopic and microscopic magnetic structures.

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Permalink: https://www.hzdr.de/publications/Publ-35677
Publ.-Id: 35677


Observation of a 1/3 magnetization plateau in Pb2Cu10O4(SeO3)4Cl7 arising from (Cu2+)7 clusters of corner-sharing (Cu2+)4 tetrahedra

Vasiliev, A. N.; Berdonosov, P. S.; Kozlyakova, E. S.; Maximova, O. V.; Murtazoev, A. F.; Dolgikh, V. A.; Lyssenko, K. A.; Pchelkina, Z. V.; Gorbunov, D.; Chung, S. H.; Koo, H.-J.; Whangbo, M.-H.

A mixed-valence compound Pb2Cu10O4(SeO3)4Cl has a complex structure consisting of one nonmagnetic Cu+ (S = 0) ion and four nonequivalent magnetic Cu2+ (S = 1/2) ions. It exhibits antiferromagnetic ordering at TN = 10.2 K. At a temperature below TN, a sequence of spin-flop transition at Bspin-flop = 1.3 T and 1/3 plateau formation at Bspin-flip = 4.4 K is observed in the magnetization curve M(B). The 1/3 magnetization plateau persists at least up to 53.5 T. The spin exchanges of Pb2Cu10O4(SeO3)4Cl7 evaluated by performing energy-mapping analysis based on DFT+U calculations show that the magnetic properties of Pb2Cu10O4(SeO3)4Cl7 are described by the (Cu2+)7 cluster of corner-sharing (Cu2+)4 tetrahedra, and that each (Cu2+)7 cluster has a S = 3/2 spin arrangement in the ground state. The 1/3 magnetization plateau observed for Pb2Cu10O4(SeO3)4Cl7 is explained by the field-induced flip of every second (Cu2+)7 cluster within a unit cell.

Permalink: https://www.hzdr.de/publications/Publ-35676
Publ.-Id: 35676


Scalable quantum control and non-Abelian anyon creation in the Kitaev honeycomb model

Raii, O.; Mintert, F.; Burgarth, D.

The Kitaev honeycomb model is a system allowing for experimentally realizable quantum computation with
topological protection of quantum information. Practical implementation of quantum information processing
typically relies on adiabatic, i.e., slow dynamics. Here we show that the restriction to adiabatic dynamics can be
overcome with optimal control theory, enabled by an extension of the fermionization of the Kitaev honeycomb
model to the time-dependent case. Moreover, we present a quantum control method that is applicable to large
lattice models due to subexponential scaling.

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Permalink: https://www.hzdr.de/publications/Publ-35675
Publ.-Id: 35675


Magnetocaloric effect and magnetic phase diagram of Ni-Mn-Ga Heusler alloy in steady and pulsed magnetic fields

Koshkid'Ko, Y. S.; Dilmieva, E. T.; Kamantsev, A. P.; Cwik, J.; Rogacki, K.; Mashirov, A. V.; Khovaylo, V. V.; Salazar Mejia, C.; Zagrebin, M. A.; Sokolovskiy, V. V.; Buchelnikov, V. D.; Ari-Gur, P.; Bhale, P.; Shavrov, V. G.; Koledov, V. V.

The work is devoted to the study of the phenomenon of irreversibility of the magnetocaloric effect (MCE) in the vicinity of the magnetostructural phase transition (PT) in Ni-Mn-Ga Heusler alloys. For this purpose, the MCE was studied by the direct method in stationary (up to 14 T) and pulsed magnetic fields (up to 50 T), and a magnetic phase diagram was constructed. Using a specially designed microscope, in-situ studies of the magnetostructural phase transition were carried out in magnetic fields of up to 14 T. Comparing the results of the MCE with those of the phase diagram, as well as in-situ studies, made it possible to determine the width of the irreversible MCE region. In-situ studies have shown, that the main reason of the occurrence of the irreversible MCE is the presence of the residual martensite formed as a result of the first magnetization of the sample. The results are discussed within the framework of Landau's phenomenological PT theory, which predicts the disappearance of thermal hysteresis under a field of 30 T. Within the framework of the same theory, a recommendation is made to reduce the value of the critical field and, as a result, the width of the hysteresis.

Permalink: https://www.hzdr.de/publications/Publ-35674
Publ.-Id: 35674


Signatures of a magnetic-field-induced Lifshitz transition in the ultra-quantum limit of the topological semimetal ZrTe5

Galeski, S.; Legg, H. F.; Wawrzynczak, R.; Förster, T.; Zherlitsyn, S.; Gorbunov, D.; Uhlarz, M.; Lozano, P. M.; Li, Q.; Gu, G. D.; Felser, C.; Wosnitza, J.; Meng, T.; Gooth, J.

The quantum limit (QL) of an electron liquid, realised at strong magnetic fields, has long been proposed to host a wealth of strongly correlated states of matter. Electronic states in the QL are, for example, quasi-one dimensional (1D), which implies perfectly nested Fermi surfaces prone to instabilities. Whereas the QL typically requires unreachably strong magnetic fields, the topological semimetal ZrTe5 has been shown to reach the QL at fields of only a few Tesla. Here, we characterize the QL of ZrTe5 at fields up to 64 T by a combination of electrical-transport and ultrasound measurements. We find that the Zeeman effect in ZrTe5 enables an efficient tuning of the 1D Landau band structure with magnetic field. This results in a Lifshitz transition to a 1D Weyl regime in which perfect charge neutrality can be achieved. Since no instability-driven phase transitions destabilise the 1D electron liquid for the investigated field strengths and temperatures, our analysis establishes ZrTe5 as a thoroughly understood platform for potentially inducing more exotic interaction-driven phases at lower temperatures.

Permalink: https://www.hzdr.de/publications/Publ-35673
Publ.-Id: 35673


Transfer printing of GMR sensing elements for curved electronics

Bezsmertna, O.; Xu, R.; Oliveros Mata, E. S.; Voigt, C.; Mosch, S.; Faßbender, J.; Vinnichenko, M.; Makarov, D.

During last years, touchless interaction between human beings and environments is attracting more and more attentions [1,2]. This opens a request for integration of electronic structures into more complex curved, flexible, or even living organism substrates for skin-like electronics, wearable health monitoring devices, virtual reality etc. Sensors based on giant magnetoresistance (GMR) effect are widely considered as a workhorse to address this demand. However, the fabrication of GMR multi-layer elements face many limitations (e.g., inappropriate to substrates with curved and/or rough surfaces) due to the layer thickness dependence of performance [3].
Here, we propose a transfer technique, which allows to overcome the aforementioned limitations. We demonstrate that a high-performance sensing elements can be transferred from flat polymer-based donor substrates to variable receiver surfaces with little loss of GMR performance (figure 1). Furthermore, such technique does not require any substrate deformation, temporary carriers or high-temperature processing methods, what prevents device damage.
During last years, touchless interaction between human beings and environments is attracting more and more attentions [1,2]. This opens a request for integration of electronic structures into more complex curved, flexible, or even living organism substrates for skin-like electronics, wearable health monitoring devices, virtual reality etc. Sensors based on giant magnetoresistance (GMR) effect are widely considered as a workhorse to address this demand. However, the fabrication of GMR multi-layer elements face many limitations (e.g., inappropriate to substrates with curved and/or rough surfaces) due to the layer thickness dependence of performance [3].
Here, we propose a transfer technique, which allows to overcome the aforementioned limitations. We demonstrate that a high-performance sensing elements can be transferred from flat polymer-based donor substrates to variable receiver surfaces with little loss of GMR performance (figure 1). Furthermore, such technique does not require any substrate deformation, temporary carriers or high-temperature processing methods, what prevents device damage

References

[1] M. Ha, et al. Advanced Materials 33.12 (2021)
[2] P. Makushko et al. Advanced Functional Materials 31.25 (2021)
[3] A. Paul et al. Journal of physics: condensed matter 15.17 (2003)

  • Lecture (Conference)
    Wilhelm and Else Heraeus Seminar 2023, 04.-06.01.2023, Bad Honnef, Germany

Permalink: https://www.hzdr.de/publications/Publ-35672
Publ.-Id: 35672


Anisotropic magnetization and electronic structure of the first-order ferrimagnet ErCo2 studied by polarization dependent hard X-ray photoemission spectroscopy

Abozeed, A. A.; Gorbunov, D.; Kadono, T.; Kanai-Nakata, Y.; Yamagami, K.; Fujiwara, H.; Sekiyama, A.; Higashiya, A.; Yamasaki, A.; Tamasaku, K.; Yabashi, M.; Ishikawa, T.; Wada, H.; Andreev, A. V.; Imada, S.

The first-order ferrimagnet ErCo2 attracts interest not only because of metamagnetism and magnetocaloric effect just above TC ≈ 32–34 K but also because it is closely related with the itinerant metamagnetism of YCo2 and LuCo2. We study the electronic structure of single crystals with hard X-ray photoemission spectroscopy (HAXPES). Magnetization measurements reconfirm the first-order magnetic transition, metamagnetism, and strong magnetic anisotropy. Calculated ErCo2 band structures of the ferrimagnetic and paramagnetic phases are presented in detail. In the ferrimagnetic state, the density of states just below EF is smaller than in the paramagnetic phase. Valence band spectra in the paramagnetic state show strong polarization dependence. Furthermore, the change across the first-order ferrimagnetic transition in the valence band electronic structures is observed. These experimental data are well described by the band structure calculation incorporated with the polarization dependent cross-sections of orbitals. We further discuss possible effects of electron correlation and spin fluctuation

Permalink: https://www.hzdr.de/publications/Publ-35671
Publ.-Id: 35671


New Insights into the Rare Earth Element Mineralization of the Storkwitz Carbonatite, Germany

Loidolt, C.; Zimmermann, R.; Tusa, L.; Lorenz, S.; Ebert, D.; Gloaguen, R.; Broom-Fendley, S.

The Storkwitz carbonatite breccia, located near Delitzsch, Germany, is one of the few European domestic rare earth elements (REE) deposits, but is relatively understudied owing to more than 100 m of Cenozoic sedimentary cover. We present the results of a petrological investigation of the recently acquired ~700 m-deep SES 1/2012 borehole. The Storkwitz breccia is composed of clasts of country rock and carbonatite ranging from ,1 mm to ~30 cm in size, cemented by ankeritic carbonatite. Extensive fenitization and biotitization mainly affect clasts of coarse-grained granitoids and medium-grained dolomite-calcite- carbonatites. An intersection of Storkwitz breccia at 425 to 542 m contains local REE enrichment up to ~1.7 wt.%. total rare earth oxides, which is predominantly contained in a REE-fluorcarbonate bearing mineral assemblage. The assemblage locally forms irregularly shaped vug-like features and rare hexagonal pseudomorphs in clasts of fine-grained ankerite-carbonatite. The REE-fluorcarbonate mineral assemblage formed prior to brecciation in the ankerite-carbonatite, which paragenetically fits with recent experimental and fluid inclusion data demonstrating the importance of late magmatic processes in forming carbonatite- hosted REE mineralization, possibly from an evolved ‘brine-melt’ phase. Our findings indicate that minor REE recrystallization and redistribution occurred during late-stage hydrothermal or supergene processes, without leading to significant REE enrichment in the upper part of the breccia compared to the lower part. Cross-cutting faults represent the last deformation event and post-date carbonatite intrusion and fenitization. They may represent important conduits for late-stage hydrothermal or supergene fluids responsible for recrystallization of the breccia matrix to a cryptocrystalline oxide mineral assemblage. Our findings highlight the importance of REE enrichment in late-stage ‘brine-melt’ phases through magmatic fractionation and in situ hydrothermal replacement.

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Permalink: https://www.hzdr.de/publications/Publ-35670
Publ.-Id: 35670


Ab initio path integral Monte Carlo simulation of electrons at extreme conditions

Dornheim, T.

I present an overview of ab initio path integral Monte Carlo simulations of electrons at extreme conditions.

  • Invited lecture (Conferences) (Online presentation)
    NHR-Atomistic Simulation Symposium 2022, 28.-29.11.2022, Paderborn, Deutschland

Permalink: https://www.hzdr.de/publications/Publ-35669
Publ.-Id: 35669


Interfacial dynamics of adsorption layers as support of biomedical research and diagnostics

Santini, E.; Nepita, I.; Bykov, A. G.; Ravera, F.; Liggieri, L.; Dowlati, S.; Javadi, A.; Miller, R.; Loglio, G.

The input of chemical and physical sciences to life sciences is increasingly important. Surface science as a complex multidisciplinary research area provides many relevant practical tools to support for example research in medicine. Tensiometry and surface rheology of human biological liquid as diagnostic tool is very successfully applied. Also for the characterization of pulmonary surfactants, this methodology is essential to deepen the insight into the functionality of lungs and the most efficient administration of drugs. Problems in ophthalmology can be addressed by surface science methods, such as the stability of wetting films and the development of artificial tears. The serious problem of obesity is a fast developing disease in many industrial countries and must be better understood and therapies for its treatment developed. Finally, the application of fullerenes as a suitable system for detecting cancer in humans is discussed.

Keywords: Dynamic surface tension; Dilational surface visco-elasticity; Drop Profile Analysis Tensiometry; Bubble Pressure Tensiometry; Langmuir trough; Brewster angle microscopy; Medical applications

Permalink: https://www.hzdr.de/publications/Publ-35668
Publ.-Id: 35668


Interaction of Catalyst Nanoparticles and Pollutant Molecules in Photocatalytic Wastewater Treatment: Novel Characterization via Dynamic Surface Properties

Javadi, A.; Nourizade, M.; Rahmani, M.; Eckert, K.

In a photocatalytic wastewater treatment, the degradation reaction mostly occurs at the surface of the catalyst and nearby regions. Therefor understanding the interaction of the catalyst and pollutant in a photocatalytic degradation system is a very important issue, indicating affinity of the pollutant molecules to be attracted or repulsed from the photocatalyst particles. The aim of this experimental study is to get a better insight into the interaction of the catalyst nanoparticles and pollutant molecules via a novel characterization method based on dynamic surface phenomena analysis. Drop profile analysis tensiometry (PAT) is used for this purpose for dynamic surface tension and elasticity measurements at aqueous solution/air interface at different pH conditions. The results show that the cationic dye Malachit Green (MG) indicates low surface activity at neutral pH (about 6.5), with an equilibrium surface tension about 69. While it becomes much more surface active at pH= 9 and surface tension is decreased to 59 mN/m. Adding TiO2 nanoparticles to MG solution at pH=9 causes a significant increase in surface tension, with much slower dynamic of adsorption at water air interface, that indicates a significant attraction and attachment of MG molecules at TiO2 nanoparticles surface. This observation is in a good correlation with observed higher efficiency of MG degradation around pH 9. The capability of this novel experimental protocol is also examined for the anionic dye Eriochrom Black-T (EBT). The results show a significant interaction between TiO2 nanoparticles and EBT at pH=3, which also is in good correlation with reported higher efficiency of EBT degradation around pH 3. The elasticity measurements also are in good agreement with these results, as an important characterization parameter, for molecular interaction in adsorbed layer, discussed in this article.

Keywords: Photocatalytic wastewater treatment; TiO2 catalyst nanoparticles; Dynamic surface phenomen; Drop profile analysis tensiometry; Interfacial elasticity; Textile dye surface activity; Malachit Green (MG); Eriochrom Black-T (EBT).

Permalink: https://www.hzdr.de/publications/Publ-35667
Publ.-Id: 35667


Imaging of Gαq proteins in mouse and human organs and tissues

Voss, J. H.; Al-Hroub, H.; Gedschold, R.; Dietrich, J.; Gaffal, E.; Toma, M.; Kehraus, S.; König, G. M.; Brust, P.; Fleischmann, B. K.; Wenzel, D.; Deuther-Conrad, W.; Müller, C. E.

G protein-coupled receptors (GPCRs) transfer extracellular signals across cell membranes by ac-tivating intracellular heterotrimeric G proteins. Recent studies suggested G proteins as novel drug targets for the treatment of complex diseases, e.g. asthma and cancer. Recently, we devel-oped specific radiotracers, [³H]PSB-15900-FR and [³H]PSB-16254-YM, for the Gαq family of G proteins by tritiation of the macrocyclic natural products FR900259 (FR) and YM-254890 (YM). In the present study, we utilized these potent radioligands to perform autoradiography studies in tissues of healthy mice, mouse models of disease, and human tissues. Specific binding was high, while non-specific binding was extraordinarily low, both radioligands giving nearly identical results. High expression levels of Gq proteins were detected in healthy mouse organs showing the following rank order of potency: kidney > liver > brain > pancreas > lung > spleen >> heart. Organ sub-structures, e.g. of mouse brain and lung, were clearly distinguishable. Whereas an acute asthma model in mouse did not result in altered Gq protein expression as compared to control animals, a cutaneous melanoma model displayed significantly increased expression in comparison to healthy skin. These results suggest the future development of Gq-protein-binding radiotracers as novel diagnostics.

Keywords: asthma; autoradiography; G protein-coupled receptors; Gαq protein; FR900359; mouse brain; YM-254890; radioligand; lung

Permalink: https://www.hzdr.de/publications/Publ-35666
Publ.-Id: 35666


Pickering foams and parameters influencing their characteristics

Amani, P.; Miller, R.; Javadi, A.; Firouzi, M.

Pickering foams are available in many applications and have been continually gaining interest in the last two decades. Pickering foams are multifaceted, and their characteristics are highly dependent on many factors, such as particle size, charge, hydrophobicity and concentration as well as the charge and concentration of surfactants and salts available in the system. A literature review of these individual studies at first might seem confusing and somewhat contradictory, particularly in multi-component systems with particles and surfactants with different charges in the presence of salts. This paper provides a comprehensive overview of particle-stabilized foams, also known as Pickering foams and froths. Underlying mechanisms of foam stabilization by particles with different morphology, surface chemistry, size and type are reviewed and clarified. This paper also outlines the role of salts and different factors such as pH, temperature and gas type on Pickering foams.

Further, we highlight recent developments in Pickering foams in different applications such as food, mining, oil and gas, and wastewater treatment industries, where Pickering foams are abundant. We conclude this overview by presenting important research avenues based on the gaps identified here. The focus of this review is limited to Pickering foams of surfactants with added salts and does not include studies on polymers, proteins, or other macromolecules.

Keywords: Particles; Foam stability; Stabilizing mechanism; Pickering foam; Salts

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Permalink: https://www.hzdr.de/publications/Publ-35665
Publ.-Id: 35665


Neptunyl(VI) Nitrate Coordination Polymer with Bis(2-pyrrolidone) Linkers Highlighting Crystallographic Analogy and Solubility Difference in Actinyl(VI) Nitrates

Takeyama, T.; März, J.; Ono, R.; Tsushima, S.; Takao, K.

NpO2(NO3)2 units are connected by bis(2-pyrrolidone) linker molecules with trans-1,4-cyclohexyl bridging part (L1) to form a 1-dimensional coordination polymer, [NpO2(NO3)2(L1)] n. Molecular and crystal structures of this compound are nearly identical to that of UO22+ analogue, while its aqueous solubility is much enhanced probably due to weaker thermodynamic stability of complexation in NpO22+ compared with that in UO22+.

Keywords: neptunyl; transuranium; coordination polymer; SC-XRD

Permalink: https://www.hzdr.de/publications/Publ-35664
Publ.-Id: 35664


Unfolded Lipase at Interfaces Studied via Interfacial Dilational Rheology: The Impact of Urea

Dowlati, S.; Javadi, A.; Miller, R.; Eckert, K.; Kraume, M.

Unfolding can interrupt the activity of enzymes. Lipase, the enzyme responsible for triglyceride catalysis, can be deactivated by unfolding, which can significantly affect the yield of enzymatic processes in biochemical engineering. Different agents can induce lipase unfolding, among which we study the impact of urea as a strong denaturant. Unfolding weakens the rigidity and stability of globular proteins, thereby changing the viscoelastic properties of the protein adsorbed layers. These changes can be detected and quantified using interfacial dilational rheology. The urea-induced unfolding of lipase destructs its globular structure, making it more flexible. The interfacial tension and viscoelastic moduli of lipase adsorbed layers reduce upon the addition of urea in the range of studied concentrations. The results agree with the theory that, upon unfolding, a distal region of the loop and tail domain forms adjacent to the proximal region of the interface. The exchange of matter between these regions reduces the viscoelasticity of the unfolded lipase adsorbed layers. Additionally, unfolding reduces the rigidity and brittleness of the lipase adsorbed layers: the aged adsorbed layer of native lipase can break upon high-amplitude perturbations of the interfacial area, unlike the case for urea-induced unfolded lipase.

Keywords: Lipase; protein unfolding; interfacial dilational rheology; interfacial viscoelasticity; profile analysis tensiometer; urea-induced unfolding

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Permalink: https://www.hzdr.de/publications/Publ-35663
Publ.-Id: 35663


Reply: Discussion Cerebral Blood Flow of the Frontal Lobe in Untreated Children with Trigonocephaly versus Healthy Controls: An Arterial Spin Labeling Study

de Planque, C. A.; Petr, J.; Gaillard, L.; Mutsaerts, H. J. M. M.; van Veelen, M.-L. C.; Versnel, S. L.; Dremmen, M. H. G.; Mathijssen, I. M. J.

Dear Editor,
We have read the letter to the editor from Long et al. with great interest. 1 The authors of this
letter stated two methodological concerns on which we will respond.
The first concern is that objective criteria are missing for true trigonocephaly or benign metopic
ridge. We only included moderate to severe trigonocephaly patients according to the definitions
of Birgfeld et al2. Birgfeld et al. provide both a phenotypical distinction between benign metopic
ridge and metopic synostosis in their article, as well as illustrative photographs with
corresponding CT-imaging in Figure 1.2 Cho et al. and Anolik et al. described CT measures to
assess severity of metopic synostosis. In both articles the cut-off point to determine surgical
indication remains subjective and poor consensus for the intermediate presentation of metopic
craniosynostosis is found.3, 4 In addition, Sisti et al. recently reviewed all literature in Pubmed
on trigonocephaly, relating to 15 anthropometric cranial measurements for surgical
indications.5 This study illustrates that most papers have a lack of diagnostic criteria for
trigonocephaly.5 At our center, the decision for surgery is made through shared decision
making with parents. In 2021 this resulted in surgery for 14 patients (moderate or severe
presentation) and a conservative treatment for 40 patients (18 mild, and 22 moderate or severe
presentation).
The second raised concern is the potential blunting effect of sevoflurane on CBF. If it does, a
similar effect on both the patients and controls is expected. In our previous ASL study in
patients with syndromic craniosynostosis using the same sedation protocol, we found a
difference between the groups.6 This suggests that the normal findings in patients with
trigonocephaly reflect normal CBF.
Very few studies have investigated the influence of anesthesia on ASL CBF in the pediatric
population. Carsin-Vu et al. included 84 subjects from 6 months to 15 years and showed no
significant CBF changes with sevoflurane in comparison with general anesthesia.7 Kaisti et al.
Without sedation, scanning of one sequence is possible, because of the limited timeframe.
However, more sequences, as in our protocol, requires a longer time period. Without sedation,
motion artifacts would make it impossible to analyze.
Finally, Long et al. mention that cerebral perfusion is a limited measure of neurodevelopment
and that fMRI studies in scaphocephaly patients have shown a difference in functional brain
connectivity compared to controls. However, there is still a lot unknown about the optimal way
of scanning, reproducibility, and interpretation of the fMRI results. Finding a difference in
connectivity in fMRI studies would be at the same level of evidence as the ASL brain MRI
study.
To conclude, our study further supports our hypothesis that surgery for trigonocephaly is rarely
indicated functionally. Parents should be informed about the unknown added value of surgery
regarding raised intracranial pressure and brain perfusion. Comparative research on outcome of
conservative versus surgical treatment of moderate to severe trigonocephaly is needed to establish clinical guidelines.

  • Open Access Logo Abstract in refereed journal
    Plastic and Reconstructive Surgery 151(2023)3, 527e-528e
    Online First (2022) DOI: 10.1097/PRS.0000000000009947

Permalink: https://www.hzdr.de/publications/Publ-35662
Publ.-Id: 35662


Identifying Influential Pandemic Regions Using Graph Signal Variation

Darapu, S.; Ghosh, S.; Senapati, A.; Hens, C.; Nannuru, S.

Developing methods to analyse infection spread is an impor-tant step in the study of pandemic and containing them. Theprincipal mode for geographical spreading of pandemics isthe movement of population across regions. We are interestedin identifying regions (cities, states, or countries) which areinfluential in aggressively spreading the disease to neighbor-ing regions. We consider a meta-population network withSIR (Susceptible-Infected-Recovered) dynamics and developgraph signal-based metrics to identify influential regions.Specifically, a local variation and a temporal local variationmetric is proposed. Simulations indicate usefulness of the lo-cal variation metrics over the global graph-based processingsuch as filtering.

Keywords: Graph signal processing; Total variation; Local variation; Network; SIR dynamics

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Permalink: https://www.hzdr.de/publications/Publ-35661
Publ.-Id: 35661


Data publication: Role of assortativity in predicting burst synchronization using echo state network

Roy, M.; Senapati, A.; Poria, S.; Mishra, A.; Hens, C.

Code for reproducing results of the paper "Role of assortativity in predicting burst synchronization using echo state network"

Keywords: Echo State Network; Assortativity; Complex network; Synchronization

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Permalink: https://www.hzdr.de/publications/Publ-35660
Publ.-Id: 35660


Role of assortativity in predicting burst synchronization using echo state network

Roy, M.; Senapati, A.; Poria, S.; Mishra, A.; Hens, C.

In this study, we use a reservoir computing based echo state network (ESN) to predict the collective burst synchronization of neurons. Specifically, we investigate the ability of ESN in predicting the burst synchronization
of an ensemble of Rulkov neurons placed on a scale-free network. We have shown that a limited number of nodal
dynamics used as input in the machine can capture the real trend of burst synchronization in this network. Further,
we investigate the proper selection of nodal inputs of degree-degree (positive and negative) correlated networks.
We show that for a disassortative network, selection of different input nodes based on degree has no significant
role in the machine’s prediction. However, in the case of assortative network, training the machine with the
information (i.e., time series) of low degree nodes gives better results in predicting the burst synchronization.
The results are found to be consistent with the investigation carried out with a continuous time Hindmarsh-Rose
neuron model. Furthermore, the role of hyperparameters like spectral radius and leaking parameter of ESN on the
prediction process has been examined. Finally, we explain the underlying mechanism responsible for observing
these differences in the prediction in a degree correlated network.

Keywords: Echo State Network; Assortativity; Complex network; Synchronization

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Permalink: https://www.hzdr.de/publications/Publ-35659
Publ.-Id: 35659


Software publication: Quantifying how post-transcriptional noise and gene copy number variation bias transcriptional parameter inference from mRNA distributions

Fu, X.; Patel, H. P.; Coppola, S.; Xu, L.; Cao, Z.; Lenstra, T. L.; Grima, R.

The url https://github.com/palmtree2013/RNAInferenceTool.jl is a Julia GitHub code repository for the paper https://doi.org/10.7554/eLife.82493:

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Permalink: https://www.hzdr.de/publications/Publ-35658
Publ.-Id: 35658


Quantifying how post-transcriptional noise and gene copy number variation bias transcriptional parameter inference from mRNA distributions

Fu, X.; Patel, H. P.; Coppola, S.; Xu, L.; Cao, Z.; Lenstra, T. L.; Grima, R.

Transcriptional rates are often estimated by fitting the distribution of mature mRNA numbers measured using smFISH (single molecule fluorescence in situ hybridization) with the distribution predicted by the telegraph model of gene expression, which defines two promoter states of activity and inactivity. However, fluctuations in mature mRNA numbers are strongly affected by processes downstream of transcription. In addition, the telegraph model assumes one gene copy but in experiments, cells may have two gene copies as cells replicate their genome during the cell cycle. While it is often presumed that post-transcriptional noise and gene copy number variation affect transcriptional parameter estimation, the size of the error introduced remains unclear. To address this issue, here we measure both mature and nascent mRNA distributions of GAL10 in yeast cells using smFISH and classify each cell according to its cell cycle phase. We infer transcriptional parameters from mature and nascent mRNA distributions, with and without accounting for cell cycle phase and compare the results to live-cell transcription measurements of the same gene. We find that: (i) correcting for cell cycle dynamics decreases the promoter switching rates and the initiation rate, and increases the fraction of time spent in the active state, as well as the burst size; (ii) additional correction for post-transcriptional noise leads to further increases in the burst size and to a large reduction in the errors in parameter estimation. Furthermore, we outline how to correctly adjust for measurement noise in smFISH due to uncertainty in transcription site localisation when introns cannot be labelled. Simulations with parameters estimated from nascent smFISH data, which is corrected for cell cycle phases and measurement noise, leads to autocorrelation functions that agree with those obtained from live-cell imaging.

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Permalink: https://www.hzdr.de/publications/Publ-35657
Publ.-Id: 35657


Biotechnology meets Resource Technology - Metal recovery with biological means

Pollmann, K.

Biotechnological approaches for metal recovery

Keywords: biohydrometallurgy; microbiology; metals

  • Invited lecture (Conferences)
    Mini-Workshop with Wroclaw University, 22.-23.06.2022, Dresden, Deutschland

Permalink: https://www.hzdr.de/publications/Publ-35656
Publ.-Id: 35656


Biohydrometallurgical Concepts for Metal Recovery from Primary and Secondary Resources

Pollmann, K.

Presentation of different approaches for bio-based metal recovery

Keywords: biohydrometallurgy; microbiology; biotechnology; metals

  • Invited lecture (Conferences)
    CASUSCON, 12.-14.06.2022, Wroclaw, Poland

Permalink: https://www.hzdr.de/publications/Publ-35655
Publ.-Id: 35655


Contrast modes in transmission experiments using broad and focussed keV ion beams

Lohmann, S.; Hlawacek, G.; Holeňák, R.; Klingner, N.; Primetzhofer, D.; Serralta, E.

The helium ion microscope (HIM) is an instrument for high-resolution imaging, composition analysis, and materials modification at the nanoscale. Ion transmission experiments could further improve the analytical capabilities of this technique, and multiple contrast modes are possible. We explore the latter at keV ion energies using a HIM in a scanning transmission approach as well as a broad beam in combination with a time-of-flight (ToF) set-up. Both systems employ positionsensitive detectors allowing for analysis of angular distributions.
In the ToF-system, we find a strong trajectory-dependence of the measured specific energy loss attributed to charge-exchange events in close collisions. Channelling and blocking of transmitted ions allows for mapping of intensity as well as different energy loss moments. In the HIM we demonstrate different contrasts, e.g., due to orientation of nanocrystals, channelling in single-crystalline membranes and material contrast for layered films.

Related publications

  • Lecture (Conference)
    DPG-Tagung der Sektion Kondensierte Materie (SKM), 04.-09.09.2022, Regensburg, Deutschland

Permalink: https://www.hzdr.de/publications/Publ-35654
Publ.-Id: 35654


Influence of crystal structure on helium-induced tendril formation in an FeCoCrNiV high-entropy alloy

Lohmann, S.; Goodall, R.; Hlawacek, G.; Hübner, R.; Ma, L.; Gandy, A. S.

High-entropy alloys (HEAs) are a relatively new class of metal alloys composed of several principal elements, usually at (near) equiatomic ratios. It has previously been reported that some HEAs dis-play superior radiation damage resistance, with composition and microstructure being cited as con-tributing factors, though the precise mechanism is still unknown. To study the influence of the crys-tal structure on the response to radiation, we have chosen FeCoCrNiV as a model system. While FeCoCrNi has a face-centred cubic (fcc) structure, adding V leads to a structural transformation to-wards a body-centred tetragonal (bct) structure with both phases present at near-stochiometric composition.
The as-cast sample was characterised by energy-dispersive X-ray spectroscopy (EDXS) and electron backscatter diffraction (EBSD) in a scanning electron microscope (SEM) confirming the presence of both phases. Irradiations were performed with a focussed He beam provided by a helium ion mi-croscope (HIM) at temperatures between room temperature and 500°C. The irradiation fluence was varied between 6x10^17 ions/cm² and 1x10^20 ions/cm². High-resolution images of the irradiated areas were taken with the same HIM, and an example is shown in Fig. 1a. Selected irradiated areas were additionally studied by transmission electron microscopy (TEM) in combination with EDXS.
Under irradiation, pores start to be generated in the material with pore sizes differing significantly between the two phases. At higher fluences and above a critical temperature, a tendril structure as exemplary shown for the bct phase in Fig. 1a forms in both phases. We have found that the critical temperature depends on the phase and is lower for fcc. TEM images reveal that the tendrils span the whole depth of the irradiated area and are accompanied by bubbles of various sizes as shown in Fig. 1b for the bct phase. Scanning TEM-based EDXS of these structures indicates a He-induced change in composition.

Related publications

  • Lecture (Conference)
    FIT4NANO Workshop, 11.-13.07.2022, Krakow, Poland

Permalink: https://www.hzdr.de/publications/Publ-35653
Publ.-Id: 35653


Helium-induced nano-structuring in an FeCoCrNiV high-entropy alloy

Lohmann, S.; Goodall, R.; Hlawacek, G.; Hübner, R.; Ma, L.; Gandy, A. S.

High-entropy alloys (HEAs) are a relatively new class of metal alloys composed of several principal elements, usually at (near) equiatomic ratios. It has previously been reported that some HEAs display superior radiation damage resistance, with composition and microstructure being cited as contributing factors, though the precise mechanism is still unknown. To study the influence of the crystal structure on the response to radiation, we have chosen FeCoCrNiV as a model system. While FeCoCrNi has a face-centred cubic (fcc) structure, adding V leads to a structural transformation towards a body-centred tetragonal (bct) structure with both phases present at near-stochiometric composition.
The as-cast sample was characterised by energy-dispersive X-ray spectroscopy (EDXS) and electron backscatter diffraction in a scanning electron microscope confirming the presence of both phases. Irradiations were performed with a focussed He beam provided by a helium ion microscope (HIM) at temperatures between 20°C and 500°C. The fluence was varied between 6×10^17 ions/cm² and 1×10^20 ions/cm². High-resolution images of the irradiated areas were taken with the same HIM as shown in Fig. 1a. Selected irradiated areas were additionally
studied by transmission electron microscopy (TEM) in combination with EDXS.
Under irradiation, pores start to be generated in the material with pore sizes differing significantly between the two phases. At higher fluences and above a critical temperature, a tendril structure as exemplary shown for the bct phase in Fig. 1a forms in both phases. TEM images reveal that these tendrils span the whole depth of the irradiated area (Fig. 1b) and are accompanied by bubbles of various sizes. Scanning TEM-based EDXS of these structures indicates a He-induced change in composition.

Related publications

  • Lecture (Conference)
    29th International conference on atomic collisions in solids & 11th International symposium on swift heavy ions in matter, 19.-24.06.2022, Helsinki, Finnland

Permalink: https://www.hzdr.de/publications/Publ-35652
Publ.-Id: 35652


Kennzahlenbasierte Beschreibung von Tropfenmitriss flashender Feeds und Tropfenabscheidern für Realstoffsysteme

Jasch, K.; Döß, A.; Schubert, M.; Kryk, H.; Hampel, U.; Scholl, S.

Die Reduktion oder weitgehende Vermeidung von Tropfen bzw. deren Abscheidung sind häufig auftretende Fragestellungen während Auslegung, Betrieb oder Revamps von Trennkolonnen. Der Mitriss von Tropfen durch die Dampfphase wirkt der bereits eingetragenen Trennleistung erheblich entgegen und beeinträchtigt die Energie¬effizienz des Verfahrens, die Produktqualität oder auch den Betrieb nachgeschalteter Apparate. Eine effiziente Tropfenabscheidung trägt daher wesentlich zur Einsparung energetischer und stofflicher Ressourcen bei. Dies erfordert eine möglichst genaue Vorhersage der auftretenden Tropfenspektren in Trennkolonnen und deren Mitriss.
Flashende Feeds sind wesentlich an der Entstehung von Tropfen in Trennkolonnen beteiligt, wobei konsolidierte Kenntnisse über entstehende Tropfengrößen- und -spektren sowie dominierende Einflussfaktoren fehlen. Ein Druckabfall unter den Sättigungsdruck des Feedgemisches führt zunächst zu einem metastabilen Zustand des überhitzten Fluids. In Folge lokaler Verdampfungs-vorgänge stellt sich ein thermodynamischer Gleichgewichtszustand im Zweiphasen¬gebiet ein. Derartige Vorgänge sind in fast allen Rückläufen in thermischen Trennkolonnen, Feeds mit kryogenen Medien oder Kolonnen mit mechanischer Brüdenkompression zur Wärmeintegration vertreten. Abhängig von Massenstrom, Überhitzung, Stoffwerten des Fluides und geometrischen Randbedingungen kommt es aufgrund der schlagartigen Druckabsenkung zu einem explosionsartigen Zerfall des metastabilen Flüssigkeitsstrahls, bei dem sich thermodynamische Instabilitäten, wie Keimbildung, Blasenwachstum und -zerfall, und fluiddynamische Beanspruchung überlagern. Erhebliche Tropfenströme sind die Folge. Dabei ist unklar, welchen Einfluss stoffliche, anlagentechnische und betriebliche Bedingungen auf die entstehende Tropfenanzahl, deren Größenspektrum und Abtrennbarkeit haben. Hier besteht ein erhebliches Interesse seitens der Anlagenbetreiber und -ausrüster, Beschrei¬bungsgrundlagen zur Abscheidung von Tropfen flashender Feeds basierend auf Experimentaldaten für Realstoffsysteme ableiten zu können.
Die Tropfenabscheidung in Trennkolonnen erfolgt über installierte Abscheider, wie z. B. Gestricke, Trägheitsabscheider oder Füllkörper. Die Auslegung und Auswahl der¬ar¬tiger Abscheider erfordert Kenntnis über das Abscheidevermögen bzw. die maximale Abscheidekapazität (Flutpunkte). Verfügbare Experimentaldaten decken jedoch nur einen ungenügenden Bereich von Stoffwerten der industriellen Praxis ab. Weitere Einfluss¬größen auf die Abscheidung, wie Tropfengrößen oder die geometrischen Parameter der Abscheider, werden derzeit nicht in den Auslegungsmodellen berücksichtigt.
Das kürzlich gestartete AiF-IGF Projekt „Kennzahlenbasierte Auslegung von Ge-stricken bei Tropfenmitriss aus flashenden Feeds von Realstoffsystemen – GeTReal“ adressiert die verlässliche kennzahlenbasierte Auslegung von Gestrickabscheidern zur Abtrennung von mitgerissenen Tropfen aus flashenden Feeds in Trennapparaten. Von den Forschungsstellen an der TU Braunschweig und am Helmholtz-Zentrum Dresden-Rossendorf werden experimentelle Untersuchungen für Modell- und Realstoffsysteme zu Tropfenmitriss und Tropfenabscheidung in Gestrickabscheidern durchgeführt. Durch eine Zwangsumlaufentspannungsverdampfung (ZUEV) werden flashende Feeds nachgebildet und der Tropfenmitriss als auch die -abscheidung unter Variation stofflicher, apparativer und betrieblicher Parameter quantitativ und qualitativ erfasst.
In dem Beitrag werden neben der ausführlichen Darstellung der Versuchsanlagen, der Methoden und des experimentellen Untersuchungsrahmens, erste experimentelle Ergebnisse zum Tropfenmitriss vorgestellt. Verschiedene Gestrickabscheider wurden im Rahmen einer geometrischen Charakterisierung untersucht. Dies umfasst die experimentelle Ermittlung von Porositätsdaten und die Bestimmung des trockenen Druckverlusts. Die so gewonnenen Daten bilden die Grundlage eines praxistauglichen Modells zur Vorhersage des Druckverlustes, welches neben viskosen Effekten auch den Einfluss von Turbulenzeffekten auf den Druckverlust berücksichtigt.
Die Arbeiten im Rahmen des Projektes GeTReal werden durch das Bundesministerium für Wirtschaft und Klimaschutz (BMWK) über die Arbeitsgemeinschaft industrieller Forschungsvereinigungen „Otto von Guericke“ e.V. (AiF) gefördert (IGF-Vorhaben: 22594 BG)

  • Poster
    Jahrestreffen der DECHEMA-Fachgruppen Fluidverfahrenstechnik und Adsorption 2023, 21.-23.03.2023, Frankfurt am Main, Deutschland

Permalink: https://www.hzdr.de/publications/Publ-35651
Publ.-Id: 35651


Bubble dynamics on laser structured porous nickel electrodes

Rox, H.; Baumann, R.; Bashkatov, A.; Yang, X.; Ränke, F.; Lasagni, A. F.; Mutschke, G.; Eckert, K.

Hydrogen produced by water electrolysis using renewable energy sources is a promising approach towards a net-zero-emission-industry that is replacing fossil fuels [1]. One cost effective and mature technology for hydrogen production is alkaline water electrolysis. The advantage is the usage of non-critical electrode materials like nickel instead of noble metals such as platinum needed for acidic water electrolysis [2]. However, compared to other technologies alkaline water electrolysis shows larger partial load limits, lower current densities and lower operating pressures [3]. Nevertheless, by enhancing the bubble growth and detachment from the electrode, the overall efficiency of alkaline electrolysis can be improved [4] to make it even more competitive for future large scale installations.

By influencing the detachment behavior of the bubbles, the efficiency can be increased. Laser technology depicts a promising approach to create a supportive micro- and nano-texturing of the electrodes. Specifically, the Direct Laser Interference Pattering (DLIP) technique is applied for structuring the electrode surfaces to increase their wettability [5]. By two overlapping laser beams, a periodic line-like pattern with a spatial period of 6.0 μm is generated.

The present study uses a 3D printed electrolysis cell developed for the analysis of the bubble dynamics and the electrochemical performance of structured and non-structured electrodes. Therefore, a removable working electrode holder is applied to a cell with optical access from the side and the top of the working electrode. Two different observation perspectives allow to study the bubble growth, the detachment size and the electrode coverage at the same time. By characterizing the electrodes beforehand using cyclic voltammetry (CV) to determine the double-layer capacitance and thus the electrochemical active surface area, a profound characterization of different laser structured electrodes is given.

References:

[1] L. Lüke, Chem. Ing. Tech. 2020, 92, No. 1–2, 70–73.
[2] S. Wang, Nano Converg. 2021, 8, 4.
[3] M. Carmo, Int. J. Hydrog. Energy. 2003, 38, 4901-4934.
[4] R. Iwata, Joule. 2021, 5, 1-14.
[5] R. Baumann, J. Laser Micro Nanoeng. 2020, 15, 2.

Keywords: Electrolysis; Hydrogen bubble; Laser structured; Porous electrode

  • Lecture (Conference)
    Electrochemistry 2022, 27.-30.09.2022, Berlin, Deutschland

Permalink: https://www.hzdr.de/publications/Publ-35650
Publ.-Id: 35650


Fundamental research on f-elements and fission products at the Institute of Resource Ecology at HZDR

März, J.

Research activities at the Institute of Resource Ecology at HZDR with a special focus on coordination chemistry of tetravalent actinides

Keywords: actinides; complexes; SC-XRD; quantum chemical calculations; magnetic spectroscopy

Related publications

  • Invited lecture (Conferences)
    The 9th ZC Colloquium in FY2022, 11.11.2022, Tokyo, Japan

Permalink: https://www.hzdr.de/publications/Publ-35649
Publ.-Id: 35649


Actinide Chemistry - From Small Molecules To Real Rock

Schmidt, M.

Actinide chemistry is of utmost importance for chemical engineering and environmental science related to the nuclear industry or nuclear waste repositories. Yet, their chemistry remains underexplored relative to other elements in the periodic table. This is equally true for fundamental studies regarding complexation chemistry or redox properties and applied investigations of geochemical behavior and environmental transport.
In this presentation, I will give an overview of recent (and not so recent) studies attempting to link the actinides’ fundamental properties with their environmental transport. Systematic studies of their coordination chemistry offer a promising route to obtain fundamental knowledge about chemical bonding in actinide compounds. Here, a suitable approach is to study series of isostructural actinide compounds, in which the metal is present in the same oxidation state. Changes in structures, bond distances, or spectroscopic properties can then be related to changes in f-orbital occupation. One important issue in this context is the degree of covalency in these compounds and how it depends on the donor atoms of a ligand, or the electronic structure and oxidation state of the actinide.
It is this chemical behavior, which then affects how mobile actinides can be if they are released into the environment as a consequence of nuclear accidents, other accidental releases or in the context of nuclear waste disposal. In these scenarios, special attention must be paid to processes occurring at the water/mineral interface. Here, we will discuss how a combination of spectroscopy, microscopy, and surface X-ray diffraction can be used to both, obtain molecular level information from the interfacial region and also relate this molecular processes to retention behavior in macroscopic, close-to-realistic systems, such as natural crystalline rock.

Keywords: Actinides; Coordination Chemistry; Sorption; Geochemistry; TRLFS; Spectroscopy; XRD

  • Invited lecture (Conferences)
    GDCh Fachtagung Nuklearchemie 2022, 04.-06.10.2022, Bergisch Gladbach, Deutschland

Permalink: https://www.hzdr.de/publications/Publ-35648
Publ.-Id: 35648


Spin dynamics in patterned magnetic multilayers with perpendicular magnetic anisotropy

Zelent, M.; Gruszecki, P.; Moalic, M.; Hellwig, O.; Barman, A.; Krawczyk, M.

The magnetization dynamics in nanostructures has been extensively studied in the last decades, and nanomagnetism has
evolved significantly over that time, discovering new effects, developing numerous applications, and identifying promising
new directions. This includes magnonics, an emerging research field oriented on the study of spin-wave dynamics and their
applications. In this context, thin ferromagnetic films with perpendicular magnetic anisotropy (PMA) offer interesting
opportunities to study spin waves, in particular, due to out-of-plane magnetization in remanence or at relatively weak
external magnetic fields. This is the only magnetization configuration offering isotropic in-plane spin-wave propagation within
the sample plane, the forward volume magnetostatic spin-wave geometry. The isotropic dispersion relation is highly
important in designing signal-processing devices, offering superior prospects for direct replicating various concepts from
photonics into magnonics. Analogous to photonic or phononic crystals, which are the building blocks of optoelectronics and
phononics, magnonic crystals are considered as key components in magnonics applications. Arrays of nanodots and
structured ferromagnetic thin films with a periodic array of holes, popularly known as antidot lattices based on PMA
multilayers, have been recently studied. Novel magnonic properties related to propagating spin-wave modes, exploitation of
the band gaps, and confined modes were demonstrated. Also, the existence of nontrivial magnonic band topologies has
been shown. Moreover, the combination of PMA and Dzyaloshinskii–Moriya interaction leads to the formation of chiral
magnetization states, including Néel domain walls, skyrmions, and skyrmionium states. This promotes the multilayers with
PMA as an interesting topic for magnonics and this chapter reviews the background and attempts to provide future
perspectives in this research field.

Keywords: Domain wall; Magnon; Magnonics; Noncolinear magnetic state; Perpendicular magnetic anisotropy

  • Open Access Logo Book chapter
    in: Solid State Physics - Advances in Research and Applications, Amsterdam: Elsevier, 2022, 1-51
    DOI: 10.1016/bs.ssp.2022.08.002

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Permalink: https://www.hzdr.de/publications/Publ-35647
Publ.-Id: 35647


Data publication: Examining different regimes of ionization-induced damage in GaN through atomistic simulations

Sequeira, M.; Djurabekova, F.; Nordlund, K.; Mattei, J.-G.; Monnet, I.; Grygiel, C.; Alves, E.; Lorenz, K.

Two Temperature Model - Molecular Dynamics (TTM-MD) simulations describing the interaction of Swift Heavy Ions (0.35-0.54 MeV/amu Xe, 0.6 and 5.8 MeV/amu Pb, and 3.8 MeV/amu U ions. The simulations are discussed in:

Sequeira, M. C., Djurabekova, F., Nordlund, K., Mattei, J.-G., Monnet, I., Grygiel, C., Alves, E., Lorenz, K., Examining Different Regimes of Ionization-Induced Damage in GaN Through Atomistic Simulations. Small 2022, 2102235. https://doi.org/10.1002/smll.202102235

Each zip file contains the input and output corresponding to each ion simulation. The input and output files are those used and generated by PARCAS 5.22 (https://gitlab.com/acclab/parcas). The radial energy profile deposited by the ion, as calculated within the TTM, can be found in the in/track.in file. The file contains two columns: one with the distance to the ion trajectory (in Angstrom) and another with the energy per atom (in eV/atom). For additional information on the simulations (e.g. bulk vs surface), please refer to the methods section of the reference above.

Keywords: Defects; GaN; Molecular Dynamics; Radiation; Recrystallization; Two-Temperature Model

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Permalink: https://www.hzdr.de/publications/Publ-35645
Publ.-Id: 35645


The RevCAR T cell platform: a switchable and combinatorial therapeutic strategy for glioblastoma

Mitwasi, N.; Abdelfatah Saleh Hassan, H. A.; Arndt, C.; Loureiro, L. R.; Kegler, A.; Kubeil, M.; Toussaint, M.; Deuther-Conrad, W.; Bachmann, M.; Feldmann, A.

Background:

Glioblastoma (GBM) is a very aggressive brain tumor, associated with poor prognosis and survival. So far, the efficiency of available therapies is limited. After proving their effectiveness in targeting hematological malignancies, chimeric antigen receptor (CAR) T cells might provide a promising therapeutic approach for GBM. Here, we present our switchable Reverse CAR technology (RevCAR). Unlike conventional CAR T cells, RevCAR T cells contain an epitope in their extracellular receptor domain, and can only be activated via bispecific target modules (RevTM) which recognize the RevCAR T cells on one side and tumor cells on the other side. Once these TMs are eliminated, RevCARs are switched off. In addition, we have developed dual-targeting RevCARs allowing the control of T cells according to the AND gate logic of Boolean algebra.

Methods:

RevTMs directed against GMB were expressed in eukaryotic cells and purified with affinity chromatography. The ability of these RevTMs to bind GBM cells and RevCAR T cells was analyzed using flow cytometry. Moreover, the capability of the mono-specific and the dual-targeting RevCAR T cells to kill GBM cells was analyzed using luminescence-based cytotoxicity assay in the absence or presence of a range of RevTM concentrations. Secreted pro-inflammatory cytokines were also evaluated by ELISA. In addition to the in vitro assays, a proof of concept co-injection experiment was performed in vivo.

Results:

In this study, we show that GBM-specific RevTMs can bind both the RevCAR T cells and the GBM cells. Importantly, the RevCAR T cells can be activated to secrete pro-inflammatory cytokines and to efficiently kill GBM cells via the RevTMs. Moreover, we were able to prove that dual-targeting RevCAR T cells can be activated only upon recognition of two different GBM targets, thereby allowing a highly specific and selective killing of GBM both in vitro and in vivo.

Conclusion:

In conclusion, the switchable RevCAR platform is a novel therapeutic approach that provides improved safety and allows combinatorial targeting of GBM.

  • Open Access Logo Poster
    ESMO IMMUNO-ONCOLOGY CONGRESS 2022, 07.-09.12.2022, Geneva, Switzerland

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Permalink: https://www.hzdr.de/publications/Publ-35644
Publ.-Id: 35644


Local Neumann semitransparent layers: Resummation, pair production, and duality

Ahmadiniaz, N.; Franchino-Vinas, S.; Manzo, L.; Mazzitelli, F. D.

We consider local semitransparent Neumann boundary conditions for a quantum scalar field as imposed by a quadratic coupling to a source localized on a flat codimension-one surface. Upon a proper regularization to give meaning to the interaction, we interpret the effective action as a theory in a first-quantized phase space. We compute the relevant heat-kernel to all order in a homogeneous background and quadratic order in perturbations, giving a closed expression for the corresponding effective action in $D=4$. In the dynamical case, we analyze the pair production caused by a harmonic perturbation and a Sauter pulse. Notably, we prove the existence of a strong/weak duality that links this Neumann field theory to the analogue Dirichlet one.

Keywords: Neumann boundary conditions; Dynamical Casimir effect; Quantum field theory in background fields; Effective action; Pair creation; Duality; Dirichlet semitransparent boundary conditions

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Permalink: https://www.hzdr.de/publications/Publ-35643
Publ.-Id: 35643


In Search of Covalency in Tetravalent Actinide (Th - Pu) Monosalen Complex Series

Blei, M. K.; Patzschke, M.; Kvashnina, K.; Waurick, L.; Schmidt, M.; Stumpf, T.; März, J.

Actinides play an important role in chemical engineering and environmental science related to the nuclear industry or nuclear waste repositories.[1] One of the major tools to obtain a profound basic knowledge about actinide (An) binding is the coordination chemistry of An using model ligands. However, fundamental An chemistry is still relatively little explored. Characteristic of the actinides is their huge variety of possible oxidation states, typically ranging from +II to +VII for early An, making their chemistry complex but interesting. A suitable approach to explore fundamental physico-chemical properties of the actinides is to study series of isostructural An compounds in which the An is in the same oxidation state.[2] Observed changes in e.g. the binding situation or magnetic effects among the An series may deliver insight into their unique electronic properties mainly originating from the f-electrons. A question still remaining in the field of An chemistry is the degree of “covalency” in compounds across the An series,[3] which may be addressed by systematic studies on series of An compounds, including transuranium (TRU) elements.
In this study we investigate the coordination chemistry of tetravalent actinides (An(IV)), which are dominant particularly under anoxic environmental conditions, using the organic salen ligand (salen = N,N’-bis(salicylidene)ethylenediamine) as a small N,O donor.[4] In addition, we change halogen (F, Cl, Br, I) and solvent (MeOH, THF, MeCN, pyridine) donors (see Figure 1) in order to analyse the ligand’s effect on covalency trends as well as their mutual influence, mainly using single crystal X-ray diffraction (SC-XRD), high-energy-resolution fluorescence detection X-ray absorption near edge spectroscopy (HERFD-XANES), and quantum chemical calculations (QCC).

Keywords: actinides; complexes; SC-XRD; quantum chemical calculations; thorium; uranium; neptunium; plutonium; N-donor ligands

Related publications

  • Invited lecture (Conferences)
    Plutonium Futures, 27.09.2022, Avignon, Frankreich

Permalink: https://www.hzdr.de/publications/Publ-35642
Publ.-Id: 35642


Early An(IV) complexes with N-donor ligands

März, J.; Fichter, S.; Patzschke, M.; Kaden, P.; Köhler, L.; Schmidt, M.; Stumpf, T.

The 5f electrons of particularly the early actinides are found to participate in bonding, e.g. to organic ligands, in contrast to the strongly shielded 4f electrons of the lanthanides. Reactivity and complexation strength of such bonds are affected by donor properties of the ligand and the electronic situation of the actinide metal center. Furthermore, coinciding properties of ligand and actinide ion regarding Pearson’s principle of hard and soft acids and bases (HSAB) can even drive the development of selective ligands, e.g. for extraction processes. Here, soft N-donor ligands were found to interact stronger with trivalent actinides in comparison to their harder lanthanide analogues.1
To evaluate how these electronic properties can be extended to a series of tetravalent actinides and their interactions with N-donor ligands, we have studied the complexation of tetravalent Th, Pa, U, Np, and Pu with the amidinate (S,S)-N,N’-bis-(1-phenylethyl)-benzamidine (PEBA), and the Schiff base N,N’-ethylene-bis((pyrrole-2-yl)methan¬imine (pyren).2-4
Complex syntheses using one equivalent of AnCl4(dme)x (An = Th, U, Np, Pu; x = 0 for U, x = 2 for Th, Np, Pu) and three equivalents of PEBA, or two equivalents of pyren led to isostructural heteroleptic 3:1 complexes [AnCl(PEBA)3] or homoleptic 2:1 complexes [An(pyren)2]. Both series were analyzed in the solid state by SC-XRD and IR, as well as in solution by NMR spectroscopy. SC-XRD results and quantum chemical calculations (QCC) revealed differences in AnIV–ligand bond length and strength between the different nitrogen donors (Namidinate, Nimine, Npyrrolide). In addition, with the help of QCC, trends regarding the covalency of the metal-ligand bonds could be derived and assigned to the involved orbitals. Delocalization indices for N–PaIV showed a strong preference of the highly polarizable 5f 1 configuration of PaIV to pyren in its homoleptic complex. This effect disappears in the heteroleptic amidinate complex. Calculated quadrupole moments give a first explanation, showing an isotropically distributed charge arround PaIV in [Pa(pyren)2] but a polarization in [PaCl(PEBA)3].
Halogen exchange reactions of Cl in [AnCl(PEBA)3] was successful for F, Br, and N3 (see Fig. 1). NMR spectra revealed a strong effect of the halogen on the paramagnetic shift, potentially again indicating the impact of the halogen on the polarizabiliy of charge arround the tetravalent actinide.

Keywords: actinides; complex; SC-XRD; quantum chemical calculations; thorium; uranium; neptunium; plutonium; N-donor ligands

  • Lecture (Conference)
    Actinides Revisited, 21.09.2022, Dresden, Deutschland

Permalink: https://www.hzdr.de/publications/Publ-35641
Publ.-Id: 35641


Bonding trends in full early actinide (Th-Pu) pyren complex series

Köhler, L.; Patzschke, M.; Kaden, P.; Kvashnina, K.; Schmidt, M.; Stumpf, T.; März, J.

In contrast to the strongly shielded 4f electrons of the lanthanides, 5f electrons of particularly the early actinides are found to participate in bonding, e.g. to organic ligands. Reactivity and complexation strength of such bonds are the most influenced by donor properties of the ligand and the electronic situation of the actinide metal center. Furthermore, coinciding properties of ligand and actinide ion regarding Pearson’s principle of hard and soft acids and bases (HSAB) can even drive the development of selective ligands, e.g. for extraction processes. Here, soft N-donor ligands were found to interact stronger with trivalent actinides in comparison to their harder lanthanide analogues.1
To evaluate how these HSAB properties can be extended to a series of tetravalent actinides and their interactions with N-donor ligands, we have studied the complexation of tetravalent Th, Pa, U, Np, and Pu with N,N’-ethylene-bis((pyrrole-2-yl)methanimine (pyren) in comparison to its structural N,O-analogue, the salen ligand.2
Complex syntheses using one equivalent of AnCl4(dme)x (An = Th, U, Np, Pu; x = 0 for U, x = 2 for Th, Np, Pu) and two equivalents of pyren led to isostructural 2:1 complexes, which were analyzed in the solid state by SC-XRD and IR, as well as in solution via NMR spectroscopy. SC-XRD results and quantum chemical calculations revealed differences in AnIV–ligand bond length and strength within pyren (Nimine vs. Npyrrolide donors) or salen (Nimine vs. Ophenolate). Interestingly, the overall bond strength of the N-donor vs. N,O-donor to An(IV), however, is almost equal for both, [An(pyren)2] and [An(salen)2] (An = Th-Pu). Delocalization indices even confirmed slightly more covalent interactions between the N,O-donor salen and Th, U, Np, and Pu in comparison with pyren. For Pa, on the other hand, this trend is reversed. QTAIM analysis could prove particularly strong interactions with the pure N-donor ligand pyren. This extraordinarily good electron sharing between pyren and Pa can be explained by the 5f1 configuration of Pa(IV), being particularly well polarizable and thus well suited for an effective backbonding to the soft N-donors of the pyren ligand.

Keywords: actinides; complex; SC-XRD; quantum chemical calculations; thorium; uranium; neptunium; plutonium; N-donor ligands

Related publications

  • Invited lecture (Conferences)
    19th Radiochemical Conference, 16.-20.05.2022, Mariánské Lázně, Tschechien

Permalink: https://www.hzdr.de/publications/Publ-35640
Publ.-Id: 35640


Copper-free click bioconjugation of technetium-99m complexes using strained cyclononyne derivatives

Schlesinger, M.; Jentschel, C.; Pietzsch, H.-J.; Kopka, K.; Mamat, C.

Click chemistry, and in particular copper-free click reactions, have gained growing interest for radiolabeling purposes in the field of radiopharmaceutical sciences. [99mTc][Tc(CO)3(H2O)3]+ is an excellent starting complex for radiolabeling of biomolecules under mild conditions. A new chelator, investigated for the copper-free strain-promoted cycloaddition, was synthesized containing the 2,2’-dipicolylamine (DPA) moiety for the 99mTc-tricarbonyl core and compared with a chelator based on activated esters for conventional radiolabeling. For the copper-free click labeling procedure, a DPA containing 4,8-diazacyclononyne moiety was prepared from a sulfonyl-modified diamide (four steps, 64% yield) ensued by the Nicholas reaction with butyne-1,3-diol. The 99mTc-DPA-DACN-complex was prepared with a radiochemical conversion (RCC) of 89% after 30 min. The following SPAAC reaction with an azide-functionalized PSMA molecule was performed within 4 hours to obtain the PSMA (prostate-specific membrane antigen) targeting 99mTc-complex with 79% RCC and without side products. For comparison, a second DPA-chelator based on a tetrafluorophenyl (TFP) ester was prepared (three steps, 64% yield) and was successfully radiolabeled with [[99mTc]Tc(CO)3(H2O)3]+ in 89% RCC after 20 min and >99% radiochemical purity after separation using an RP18 cartridge. The subsequent conjugation of an amine-functionalized PSMA targeting molecule was performed with 23% RCC after 150 min. Two other unknown side products were observed indicating hydrolysis of the TFP ester during the labeling. All nonradioactive Re(CO)3 complexes were synthesized from (Et4N)2[ReBr3(CO)3] (91% yield for the natRe-DPA-TFP ester, 76% yield for the natRe-DPA-DACN) and characterized to confirm the identity of the 99mTc-complexes.

Keywords: Technetium-99m; Click Chemie; kupferfrei

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  • Secondary publication expected

Permalink: https://www.hzdr.de/publications/Publ-35639
Publ.-Id: 35639


Recycling battery casing materials

Lyon, T.; Staudacher, M. T. L.; Mütze, T.; Peuker, U. A.

Lithium-ion batteries (LIBs) have become an indispensable part of modern life. Whether in tools, mobile phones, scooters, or electric cars, the demand for LIBs is increasing in many areas of everyday life. Various scenarios predict an almost exponential growth in the demand for electrochemically stored energy and thus also in the demand for key elements for LIBs such as lithium, cobalt, and nickel. Many of the current recycling processes are limited to recovering valuable metals such as cobalt and nickel due to economic viability. Base metals such as aluminum are usually not recovered and are thus lost to the raw material cycle.

Keywords: Mechanical processing; Selective crushing; Air classifier; Eddy-current separation; Housing fraction; Liberation comminution; Lithium-ion battery; Cell housing

Permalink: https://www.hzdr.de/publications/Publ-35638
Publ.-Id: 35638


Mechanical and physical processes of battery recycling

Werner, D. M. M.; Mütze, T.; Kaas, A.; Peuker, U. A.

The rising production of lithium-ion batteries (LIBs) due to the introduction of stationary and portable energy-storage devices as well as electric mobility in particular demands an efficient and sustainable waste management scheme. In principle, the material transformation from end-of-life (EOL) LIBs to secondary (raw) materials follows the recycling chain for wastes. Therein, processing aims to break up the bonds between the individual components and materials of the battery to enrich them into defined concentrates for subsequent metallurgical refining. In general, mechanical processes are more energyefficient and economically affordable than thermal, chemical, and metallurgical ones. Consequently, a combination of several crushing, size classifying, and sorting steps are commonly used to prepare concentrates for further treatment. This chapter presents the principles of mechanical liberation and physical separation processes for EOL LIB processing. Combinations of specific processes categorized by their feed materials are proposed and discussed, outlining possible material fractions and further potential for research and development. LIB recycling with a mechanical processing unit is shown to achieve high recycling efficiencies that enable the fulfill the upcoming and updated European legal framework regarding LIB disposal.

Keywords: waste processing; physical separation; mechanical liberation; Lithium-ion battery; fractions; coarse fractions

Permalink: https://www.hzdr.de/publications/Publ-35637
Publ.-Id: 35637


Insights into Uranium binding properties by magnetotactic bacteria

Krawczyk-Bärsch, E.; Ramtke, J.; Drobot, B.; Müller, K.; Steudtner, R.; Hübner, R.; Raff, J.

Magnetotactic bacteria are characterized by intracellular magnetic mineral crystals of magnetite (Fe3O4) or greigite (Fe3S4), which helps them to orientate themselves along the Earth's magnetic field for reaching regions of optimal oxygen concentrations. They are facultative anaerobe and usually found in a large abundance in oxic-anoxic transition zones of aquatic environments, in sediments of freshwater, brackish, marine, and hypersaline habitats [1]. Assuming that magnetotactic bacteria can also be found in the far-field of a nuclear waste repository, studies on the interaction of a natural bacterial strain of Magnetospirillum magneticum AMB-1 cells with U were carried out for the first time using a multidisciplinary approach combining microscopy and different spectroscopic techniques to achieve a better molecular understanding. Results of batch sorption experiments show that Magnetospirillum magneticum AMB-1 can survive both in a wide pH range and with relatively high U concentrations of up to 0.1 mM, while effectively and almost completely immobilizing U in the first hours of incubation. (S)TEM/EDXS studies on ultrathin sections of cells loaded with 0.1 mM U clearly indicate that U is predominantly located in the cell wall. Since it is known from previous studies [2] that U often binds to the cell wall of bacteria by interacting with cell wall compounds, important ligands were used, such as peptidoglycan, lipopolysaccharide, L-rhamnose, D-(+) galactose and D-(+) mannose as possible complexants for U and measured by cryo-TRLFS combined with PARAFAC. The results show five U species and highlight the dominant role of peptidoglycan as main sorbent of U on the cell wall of Magnetospirillum magneticum AMB-1 cells, showing three characteristic peptidoglycan species. In-situ ATR FT-IR studies confirm the predominant binding to carboxylic functionalities and reveal that polynuclear species seem to play an important role at higher pH.

Keywords: magnetotactic bacteria; uranium; sorption; peptidoglycan

  • Poster
    Jahrestagung der Fachgruppe Nuklearchemie 2022, 04.-06.10.2022, Bergisch-Gladbach, Germany

Permalink: https://www.hzdr.de/publications/Publ-35636
Publ.-Id: 35636


A local model to study precessing turbulence

Pizzi, F.; Mamatsashvili, G.; Giesecke, A.; Stefani, F.

Precession driven flows are ubiquitous natural phenomena. Similarly to other
forcing mechanism, precession motion causes complex behavior in the fluid flow
consisting of interplay between rotating and inertial wave turbulence. Turbulent
precessing flows can drive dynamo action

Keywords: Rotating turbulence; Precession

  • Poster
    17TH SEDI (Study Earth's Deep Interior) symposium, 11.07.2022, Zurich, Switzerland

Permalink: https://www.hzdr.de/publications/Publ-35635
Publ.-Id: 35635


Data publication: Numerical and theoretical framework for the DRESDYN precession dynamo experiment

Pizzi, F.; Giesecke, A.; Simkanin, J.; Kumar, V.; Gundrum, T.; Stefani, F.

This dataset is the base of the publication. It has been computed through a fully nonlinear DNS code (SEMTEX) and a code for the computation of magnetic field written by Dr. Andre' Giesecke.

Keywords: Direct Numerical Simulations (DNS); Dynamo; MHD

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Permalink: https://www.hzdr.de/publications/Publ-35633
Publ.-Id: 35633


Microbially induced reduction of Uranium in contaminated mine water for bioremediation purposes: A multidisciplinary approach study

Newman Portela, A.; Krawczyk-Bärsch, E.; Lopez-Fernandez, M.; Kassahun, A.; Roßberg, A.; Kvashnina, K.; Bazarkina, E.; Raff, J.; Merroun, M. L.

The legacy of the former uranium (U) mining in Saxony and Thuringia (Germany) still shows uranium concentrations, e.g., in the mine water of some mines. The present study describes the biostimulation of the native U reducing microbial community in a U contaminated mine water as an efficient and eco-friendly strategy for in situ bioremediation to prospectively support or outperform chemical water treatments.

The microbial community was characterized by 16S and ITS1 rRNA gene analyses, showing a relative abundance of native microbial groups with the ability to alter the speciation and redox state of soluble U (e.g., Desulfovibrio, Gallionella, Penicillium and Aspergillus). Additionally, Inductively Coupled Plasma-Mass spectrometry (ICP-MS) and Ionic Chromatography (IC) were used to determine geochemical profile of the mine water, exhibiting a notable concentration of U (1.01mg/L), SO4 2- (335mg/L), Fe (0.99mg/L) and Mn (1.44mg/L). Cryo-Time-Resolved Laser Fluorescence spectroscopy (cryo-TRLFS) and Parallel Factor Analysis (PARAFAC) determined the aqueous species Ca2UO2(CO3)3 4- as the main U species in mine water. A set of anerobic microcosms, supplemented with glycerol (10mM) as electron donor to stimulate U reducing bacteria, were designed as basis of an in situ bioremediation strategy for uranium contaminated waters. A thermodynamic Eh-pH dominance diagram calculated using Geochemist's Workbench predicted the reduction of U(VI) and the formation of the solid U-ore (uraninite). At the end of the experiment, ICP-MS and Ion-Chromatography analysis from the microcosms revealed a decrease of U (≈98%), Fe (≈91%) and SO4 2- (≈88%). Furthermore, the black precipitate formed at the bottom of the microcosm was analyzed by High Energy Resolution Fluorescence Detected Near-edge X-ray absorption fine structure (HERFD-XANES) and Extended X-ray absorption fine structure (EXAFS) identifying mainly U(IV) (≈80%) and U(V) (≈20%).

The results obtained revealed that microbial cycling processes have a significant impact on the complete enzymatic reduction of soluble U(VI) to U(IV) and U(V) by the addition of an electron donor in low U concentration contaminated mine water. Therefore, this methodology could be an efficient bioremediation approach for the management of U contaminated mine water, as well as low U contaminated mine water scenarios, through the biostimulation of its indigenous microbial community.

Keywords: microorganisms; uranium; mine water; reduction

Related publications

  • Lecture (Conference)
    Symposium on Remediation, 29.-30.09.2022, Jena, Germany

Permalink: https://www.hzdr.de/publications/Publ-35632
Publ.-Id: 35632


Suppression of Interband Heating for Random Driving

Zhao, H.; Knolle, J.; Moessner, R.; Mintert, F.

Heating to high-lying states strongly limits the experimental observation of driving induced nonequilibrium phenomena, particularly when the drive has a broad spectrum. Here we show that, for entire
families of structured random drives known as random multipolar drives, particle excitation to higher bands
can be well controlled even away from a high-frequency driving regime. This opens a window for
observing drive-induced phenomena in a long-lived prethermal regime in the lowest band.

Permalink: https://www.hzdr.de/publications/Publ-35631
Publ.-Id: 35631


Biostimulation of uranium reducing bacteria in contaminated mine water for bioremediation purposes: multidisciplinary approach study

Newman Portela, A.; Krawczyk-Bärsch, E.; Lopez-Fernandez, M.; Bok, F.; Kassahun, A.; Merroun, M. L.; Raff, J.

Uranium (U) and its mining have historically been strongly related to East Germany. From the second half of the 20th century onwards, the Federal States of Saxony and Thuringia have been the scene of intense mining activity. The cessation of mining activities in 1990, has led to the generation of U contaminated areas. Nowadays, conventional remediation methodologies are not able to remove soluble U entirely. Microorganisms offer an environmental friendly water remediation strategy for U through bioreduction or biomineralization. The present study describes a strategy for in situ bioremediation of U(VI) from a U mine water by biostimulation of the native U reducing microbial community.
The geochemical profile of the mine water was characterized by Inductively Coupled Plasma-Mass spectrometry (ICP-MS) and Ionic Chromatography (IC), showing a substantial concentration of U (1.01mg/L), SO4 2- (335mg/L), Fe (0.99mg/L) and Mn (1.44mg/L). Cryo-Time-Resolved Laser Fluorescence spectroscopy (cryo-TRLFS) and Parallel Factor Analysis (PARAFAC) determined the aqueous species Ca2UO2(CO3)3 4- as the main U species in mine water. In addition, 16S and ITS1 rRNA gene analyses were used to characterize the microbial community, indicating a relative abundance of natural microbial groups with U(VI)-reduction ability (e.g., Desulfovibrio, GallionellaSideroxydans). For the design of an in situ bioremediation technology for U contaminated waters, a set of anoxic microcosms supplemented with glycerol (10mM) as electron donor was previously designed. A thermodynamic Eh-pH dominance diagram calculated using Geochemist's Workbench predicted the reduction of U(VI) and the formation of the solid U-mineral (uraninite). After 3 months, ICP-MS and Ion-Chromatography analysis from the microcosms revealed a decrease of U (≈98%), SO42- (≈88%) and Fe (≈91%). Furthermore, the black precipitate formed at the bottom of the microcosm was analyzed by UV-Vis spectroscopy, identifying mainly U(IV).
The results obtained revealed the U enzymatic reduction of U(VI) to U(IV) by the addition of an electron donor in low concentrated U contaminated mine waters. Thus, this strategy might be an efficient bioremediation approach for U contaminated mine waters, by biostimulating their indigenous microbial community.

Keywords: microorganismens; uranium; mine water; reduction

  • Lecture (Conference)
    Goldschnmidt Conference 2022, 10.-15.07.2022, Honolulu, Hawaii, US

Permalink: https://www.hzdr.de/publications/Publ-35630
Publ.-Id: 35630


Iterative quantum optimization with an adaptive problem Hamiltonian for the shortest vector problem

Zhu, Y. R.; Joseph, D.; Ling, C.; Mintert, F.

Quantum optimization algorithms hold the promise of solving classically hard, discrete optimization problems
in practice. The requirement of encoding such problems in a Hamiltonian realized with a finite (and currently
small) number of qubits, however, poses the risk of finding only the optimum within the restricted space
supported by this Hamiltonian. We describe an iterative algorithm in which a solution obtained with such
a restricted problem Hamiltonian is used to define a new problem Hamiltonian that is better suited than the
previous one. In numerical examples of the shortest vector problem, we show that the algorithm with a sequence
of improved problem Hamiltonians converges to the desired solution.

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Permalink: https://www.hzdr.de/publications/Publ-35629
Publ.-Id: 35629


Identifying Time Scales in Particle Production from Fields

Diez, M.; Alkofer, R.; Kohlfürst, C.

Particle production through ultra-strong electric fields is a well-studied research field. Nevertheless, despite repeated attempts to relate the production rate within the field to the formation time of a particle, the latter is still shrouded in mystery. We provide an interpretation of a particle
distribution at finite times enabling us to isolate and, therefore, identify the relevant time scales
regarding particle formation in quantum physics within and beyond perturbation theory.

Keywords: Non-equilibrium Quantum Field Theory; Strong-Field Quantum Electrodynamics; Schwinger effect; Time scales

Permalink: https://www.hzdr.de/publications/Publ-35628
Publ.-Id: 35628


A glimpse into pion gravitational form factor

Xing, Z.; Ding, M.; Chang, L.

We provide a novel approach to calculate the gravitational form factor of pion under the ladder approximation of the Bethe-Salpeter equation, with contact interactions. Central to this approach is a symmetry-preserving treatment of the dressed ππ amplitude, which shows explicitly the contributions from intrinsic quarks and bound states, the latter being necessary to produce the D-term of pion in the soft-pion limit. The approach we provide in this work can be applied to many processes of physical significance.

Permalink: https://www.hzdr.de/publications/Publ-35627
Publ.-Id: 35627


High dimensional tori and chaotic and intermittent transients in magnetohydrodynamic Couette flows

Garcia Gonzalez, F.; Ogbonna, J. E.; Giesecke, A.; Stefani, F.

The magnetised spherical Couette (MSC) problem, a three dimensional magnetohydrodynamic paradigmatic model in geo- and astrophysics, is considered to investigate bifurcations to high-dimensional invariant tori and chaotic flows in large scale dissipative dynamical systems with symmetry. The main goal of the present study is to elucidate the origin of chaotic transients and intermittent behaviour from two different sequences of Hopf bifurcations involving invariant tori with four fundamental frequencies, which may be resonant. Numerical evidence of the existence of a crisis event destroying chaotic attractors and giving rise to the chaotic transients is provided. It is also shown that unstable invariant tori take part in the time evolution of these chaotic transients. For one sequence of bifurcations, the study demonstrates that chaotic transients display on-off intermittent behaviour. A possible explanatory mechanism is discussed.

Permalink: https://www.hzdr.de/publications/Publ-35626
Publ.-Id: 35626


Eu(III) and Cm(III) Complexation by the Aminocarboxylates NTA, EDTA, and EGTA Studied with NMR, TRLFS, and ITC – An Improved Approach to More Robust Thermodynamics

Friedrich, S.; Sieber, C.; Drobot, B.; Tsushima, S.; Barkleit, A.; Schmeide, K.; Stumpf, T.; Kretzschmar, J.

The complex formation of Eu(III) and Cm(III) was studied with tetradentate, hexadentate, and octadentate coordinating ligands of the aminopolycarboxylate family, viz. nitrilotriacetate (NTA³), ethylenediaminetetraacetate (EDTA⁴), and ethylene glycol-bis(2-aminoethyl ether)-N,N,N′,N′-tetraacetate (EGTA⁴), respectively. Based on the complexones’ pKa values obtained from ¹H nuclear magnetic resonance (NMR) spectroscopic pH titration, complex formation constants were determined by means of parallel-factor-analysis-assisted evaluation of Eu(III) and Cm(III) time-resolved laser-induced fluorescence spectroscopy (TRLFS). This was complemented by isothermal titration calorimetry (ITC), providing the enthalpy and entropy of the complex formation. This allowed us to obtain genuine species along with their molecular structures and corresponding reliable thermodynamic data. The three investigated complexones formed 1:1 complexes with both Eu(III) and Cm(III). Besides the established Eu(III)–NTA 1:1 and 1:2 complexes, we observed, for the first time, the existence of a Eu(III)–NTA 2:2 complex as of millimolar metal and ligand concentrations. Demonstrated for thermodynamic studies on Eu(III) and Cm(III) interaction with complexones, the utilized approach is commonly applicable to many other metal–ligand systems, even to high-affinity ligands.

Keywords: Europium; Curium; Metal complex; Spectroscopy; Calorimetry; Stability constant; High-affinity ligand

Permalink: https://www.hzdr.de/publications/Publ-35625
Publ.-Id: 35625


The chemical journey of Europium(III) through winter rye (Secale cereale L.) – Understanding through mass spectrometry and chemical microscopy

Stadler, J.; Vogel, M.; Steudtner, R.; Drobot, B.; Kogiomtzidis, A. L.; Weiss, M.; Walther, C.

A combination of biochemical preparation methods with microscopic, spectroscopic, and mass spectrometric analysis techniques as contemplating state of the art application, was used for direct visualization, localization, and chemical identification of europium in plants. This works illustrates the chemical journey of europium (Eu(III)) through winter rye (Secale cereale L.), providing insight into the possibilities of speciation for Rare Earth Elements (REE) and trivalent f-elements. Kinetic experiments of contaminated plants show a maximum europium concentration in Secale cereale L. after four days. Transport of the element through the vascular bundle was confirmed with Scanning Electron Microscopy (SEM) and Energy Dispersive X-ray analysis (EDS). For chemical speciation, plants were grown in a liquid nutrition medium, whereby Eu(III) species distribution could be measured by mass spectrometry and luminescence measurements. Both techniques confirm the occurrence of Eu malate species in the nutrition medium, and further analysis of the plant was performed. Luminescence results indicate a change in Eu(III) species distribution from root tip to plant leaves. Microscopic analysis show at least three different Eu(III) species with potential binding to organic and inorganic phosphate groups and a Eu(III) protein complex. With plant root extraction, further europium species could be identified by using Electrospray Ionization Mass Spectrometry (ESI MS). Complexation with malate, citrate, a combined malate-citrate ligand, and aspartate was confirmed mostly in a 1:1 stoichiometry (Eu:ligand). The combination of the used analytical techniques opens new possibilities in direct species analysis, especially regarding to the understanding of rare earth elements (REE) uptake in plants. This work provides a contribution in better understanding of plant mechanisms of the f-elements and their species uptake.

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Permalink: https://www.hzdr.de/publications/Publ-35624
Publ.-Id: 35624


data and code for "Species invasiveness and community invasibility of US freshwater fish fauna revealed via trait-based analysis"

Su, G.; Mertel, A.; Brosse, S.; Calabrese, J.

All data and codes used for the analyses in the paper "Species invasiveness and community invasibility of US freshwater fish fauna revealed via trait-based analysis

Keywords: invasiveness; invasibility; freshwater fish; functional traits; functional diversity

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Permalink: https://www.hzdr.de/publications/Publ-35623
Publ.-Id: 35623


The Chemical Journey of Europium(III) through Winter Rye (Secale cereale L.) – Understanding through Mass Spectrometry and Chemical Microscopy

Stadler, J.; Vogel, M.; Steudtner, R.; Drobot, B.; Kogiomtzidis, A.; Weiss, M.; Walther, C.

Archiv of research data for the manuscript

Keywords: Rare earth elements; plant uptake; species analysis; europium; imaging

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Permalink: https://www.hzdr.de/publications/Publ-35622
Publ.-Id: 35622


Comparison of two structurally different RevTMs for the RevCAR system to specifically target CEA expressing cells

González Soto, K. E.; Loureiro, L. R.; Bergmann, R.; Arndt, C.; Mitwasi, N.; Kegler, A.; Bartsch, T.; Drewitz, L.; Feldmann, A.; Bachmann, M.

Despite the fact that chimeric antigen receptor (CAR) engineered T cells have shown encouraging therapeutic effects in hematological setups, the targeting of solid tumor-related antigens still represents a challenge. One main issue is that the expression of this type of antigens is not restricted to cancer cells, but normal tissues express them as well to some degree. In order to avoid strong side-effects caused by on-target/off-tumor effects, more controllable and specific CAR T cell-derived technologies need to be developed. In this line of thought, we developed the switchable, flexible and programmable Reverse (Rev) CAR platform. This system is based on engineered T cells expressing RevCAR molecules, which have extracellular short peptide epitopes incapable of recognizing surface antigens. Thus, the RevCAR T cells are per se inert and will only recognize the target cell through the interaction with an antigen-specific target module, named RevTM. RevTMs are bispecific antibodies designed to bind simultaneously to the target antigen and the short epitopes on the RevCAR engineered T cells. This interaction triggers a specific activation and cytotoxic activity of the RevCAR T cells redirecting them to eradicate the cancer cells.
Here, we adapted our RevCAR technology to target the carcinoembryonic antigen (CEA), which is a significant tumor marker for colorectal cancers and other carcinomas. Moreover, we developed two RevTMs with different structures: scFv- and IgG4-based. The first one is built by linking a scFv against CEA to a scFv that recognizes the RevCAR epitope through glycine and serine residues, resulting in a small sized molecule (<60 kDa) with two binding sites. The IgG4-based RevTM connects the same scFv-structures but in this case through the hinge and constant Fc regions (CH2 and CH3) of an IgG4 antibody. The formation of disulfide bridges on the hinge portion causes the formation of homodimers, resulting in a molecule with increased molecular weight (160 kDa) with a total of four binding sites. The generation of diverse RevTMs formats is of interest because their structures influence their half-life, biodistribution and killing efficiency, which are important features when it comes to adapting and customizing patient therapy using the RevCAR system.
We herein demonstrate that both scFv- and IgG4-based RevTMs can bind, on the one hand to CEA expressing cells, and on the other hand to engineered T cells expressing the RevCAR epitopes. Similarly, we confirmed that the simultaneous binding of the RevTMs to the RevCAR T cells and the CEA expressing cells promotes a specific lysis of the target cells in vitro, together with the secretion of pro-inflammatory cytokines. Additionally, we validated that CEA expressing cells are effectively eradicated by RevCAR T cells on the presence of RevTMs in vivo. Hereby, we proved that the RevCAR system can be directed to target CEA expressing cells using RevTMs with different formats, which encourages its further development as a future treatment option for solid tumors.

  • Open Access Logo Poster
    TUMOR IMMUNOLOGY MEETS ONCOLOGY (TIMO) XVI 2022, 07.-09.07.2022, Halle, Deutschland

Permalink: https://www.hzdr.de/publications/Publ-35621
Publ.-Id: 35621


Experimental investigation of the nutation angle's effect on the flow inside a precessing cylinder

Kumar, V.; Giesecke, A.; Gundrum, T.; Pizzi, F.; Ratajczak, M.; Anders, S.; Stefani, F.

Precession-driven flows are considered as potential sources of dynamo action on Earth, ancient moon, and some asteroids. At the Helmholtz-Zentrum Dresden-Rossendorf (HZDR), a precession-driven dynamo experiment is now being constructed as part of the DRESDYN project. It is a cylinder filled with liquid sodium with a radius of 1 m and a height of 2 m. The cylinder rotates at a frequency of up to 10 Hz and precesses around the second axis at a rate of up to 1 Hz.
To gain a better understanding of the hydrodynamics of a precessing cylinder, a downscaled 1:6 water mockup with the same aspect ratio, rotation, and precession frequency was built. The typical non-axisymmetric Kelvin mode, which initially increases as the precession ratio increases, is alone not suitable for dynamo action in the experiment. However, a secondary axisymmetric mode that appears in a narrow region of the precession ratio was demonstrated to be particularly promising for dynamo action in the sodium experiment.
To predict dynamo behavior for different precession ratios and precession angles, a thorough understanding of the flow structure in the precessing cylindrical vessel is required. For that purpose, we performed a series of precession measurements on the downscaled water experiment with Ultrasonic Doppler velocimetry (UDV) at various precession angles of 60o, 75o, and 90o. We present the effect of precession angle and rotation direction (i.e. prograde or retrograde) on the dominant flow modes, and quantify this behaviour in dependence on the rotation rate, which is parameterized by the Reynolds number Re = ΩcR2/ν, and the precession ratio Po = Ωp/Ωc, where ν is the viscosity and Ωp = 2πfp is the angular frequency of the precession. The experimental results are compared with numerical simulations.

  • Poster
    9th International Symposium on Bifurcations and Instabilities in Fluid Dynamics, 16.-19.08.2022, Groningen, the Netherlands

Permalink: https://www.hzdr.de/publications/Publ-35619
Publ.-Id: 35619


The Effect of the Nutation Angle on the Flow in a Precessing Cylinder: Experimental Results

Kumar, V.; Giesecke, A.; Gundrum, T.; Pizzi, F.; Ratajczak, M.; Stefani, F.

Precession-driven flows are discussed as possible sources for dynamo action in the Earth [1], the ancient moon, and in some asteroids. A precession-driven dynamo experiment is currently under construction at Helmholtz-Zentrum Dresden-Rossendorf (HZDR) as part of the DRESDYN project. It consists of a liquid sodium filled cylinder with a radius of 1 m and a height of 2 m. The cylinder rotates at a frequency of up to 10 Hz and precesses at a frequency of up to 1 Hz around the second axis [2].
A downscaled 1:6 water mockup with the same aspect ratio and rotation and precession frequencies was developed to better understand the hydrodynamics in a precessing cylinder. The typical non-axisymmetric Kelvin mode, which initially increases as the precession ratio increases, is alone not suitable for dynamo action in the experiment. However, a secondary axisymmetric mode that appears in a narrow region of the precession ratio was demonstrated to be particularly promising for dynamo action in the sodium experiment [3].
To be able to anticipate dynamo behaviour for various precession ratios and precession angles, a complete understanding of the flow structure in the precessing cylindrical vessel is required. For that purpose, we conducted a series of precession measurements using Ultrasonic Doppler velocimetry (UDV) on the downscaled water experiment at various precession angles of 60o, 75o, and 90o. We present the effect of precession angle and rotation direction (i.e. prograde or retrograde) on the dominant flow modes, and quantify this behaviour in dependence on the rotation rate, which is parameterized by the Reynolds number Re = ΩcR2/ν, and the precession ratio Po = Ωp/Ωc, where ν is the viscosity and Ωp = 2πfp is the angular frequency of the precession. The experimental results are compared with numerical simulations [4].

  • Contribution to proceedings
    12th International PAMIR Conference - Fundamental and Applied MHD, 04.-08.07.2022, Krakow, Poland

Permalink: https://www.hzdr.de/publications/Publ-35618
Publ.-Id: 35618


NMR spectroscopy of selected aqueous systems investigated at HZDR–IRE

Kretzschmar, J.; Stumpf, T.

Nuclear magnetic resonance (NMR) spectroscopy is a powerful method for both structure elucidation of molecules and their metal complexes, and also for studying their behavior in terms of thermodynamics and kinetics, as well as reactions occurring in situ in dependence on a variety of physico-chemical parameters. In this context, NMR spectroscopy of aqueous (D₂O) solutions features some peculiarities. That is, first and foremost, the pH (pD) of the solution affects the speciation of both the molecule (ligand) and the metal ion (actinide or lanthanide) under study. Furthermore, the ligand can be subject to deuteration, and either component can undergo redox reactions.

The intracellularly occurring tripeptide glutathione (GSH) constitutes a redox equilibrium with its oxidized (dimeric) form glutathione disulfide (GSSG). Hexavalent uranium, U(VI), forms complexes with the latter over a wide pH range, while GSH reduces U(VI) to U(IV). However, the redox reaction occurs only between pH 6 and 10, i.e. close to the thiol group’s pKa, presumably due to homolytic cleavage of the S–H group in GSH’s cysteine residue. The redox reaction appears to take place intermolecularly without the need for U(VI) complexation by the reductant [1, 2].
Uranyl(VI) citrate dimeric and trimeric complexes exhibit interesting structural and (¹⁷O) NMR spectroscopic features such as superstructure formation upon varying pH or concentration, and polarization of uranyl units acting as Lewis base in metal ion coordination (O=U=O⟶Mn+) [3, 4]. Irradation of uranyl(VI) citrate by visible light yields complexes of lower valent uranium. The reaction again occurs intermolecularly, whereby in situ oxidation of excessive ligand through several intermediates can be comprehended by NMR spectroscopy.
In studies investigating the interaction of radionuclides (RNs) with a solid phase in equilibrium with an aqueous phase, the influence of organics on RN retention can be complemented by qualitative and quantitative solution NMR methods by determining their speciation (free, metal ion-bound, oxidized) and concentration in the supernatant.
NMR spectroscopy can also be utilized as a robust and elegant method for determining ligand’s pKa along with the originating site of the abstracted proton as shown for GSH/GSSG, 2-phosphonobutane-1,2,4-tricarboxylic acid (PBTC), as well as nitrilotriacetate (NTA) and ethylene glycol-bis(aminoethyl ether)-N,N,N’,N’-tetraacetic acid (EGTA) [5]. The latter two, being representatives of the so-called complexones, show Lewis acid-catalyzed in situ deuteration of the N acetyl methylene groups in NaOD media, which is applied for speciation analyses in artificial body fluids by means of ²H NMR spectroscopy as the only deuterated component.

Acknowledgement
This research received funding by the German Federal Ministry for Economic Affairs and Energy (BMWi) with-in the GRaZ II projects, nos. 02E11860B and 02E11860G, the German Federal Ministry of Education and Research (BMBF) within the RADEKOR project, no. 02NUK057A, as well as by the European Union’s Horizon 2020 research and innovation programme’s CORI project, no. 847593.

References
[1] Kretzschmar, J.; Haubitz, T.; et al. Chem. Commun., 2018, 54, 8697.
[2] Kretzschmar, J.; Strobel, A.; et al. Inorg. Chem., 2020, 59, 4244.
[3] Kretzschmar, J.; Tsushima, S.; et al. Chem. Commun., 2020, 56, 13133.
[4] Kretzschmar, J.; Tsushima, S.; et al. Inorg. Chem., 2021, 60, 7998.
[5] Kretzschmar, J.; Wollenberg, A.; et al. Molecules, 2022, 27, 4067.

Keywords: NMR spectroscopy; Uranium; Radioecology; Aqueous system; Thermodynamics; Kinetics; Redox reaction; Speciation

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Influence of the precession angle on the flow inside a precessing cylinder

Kumar, V.; Giesecke, A.; Gundrum, T.; Pizzi, F.; Ratajczak, M.; Stefani, F.

Precession driven flows are potential drivers for dynamo action in the Earth [1], the ancient moon, and some asteroids. As part of the DRESDYN project at Helmholtz-Zentrum Dresden-Rossendorf (HZDR) a precession-driven dynamo experiment is presently under construction, which consists of a liquid sodium filled cylinder with a radius of 1 m and a height of 2 m respectively. The cylinder rotates with a frequency of up to 10 Hz and precess around the second axis with a frequency of up to 1 Hz [2].
To understand the hydrodynamics in a precessing cylinder a downscaled 1:6 water mockup was built with the same aspect ratio and rotation frequencies. The typical non-axisymmetric Kelvin mode that grows as the precession ratio rises is alone not suitable for dynamo action in the experiment. However, a secondary axisymmetric mode that emerges in a small region of the precession ratio was shown to be very promising for dynamo action in the sodium experiment [3].
The ability to predict dynamo behaviour for different precession ratios and precession angles requires a thorough understanding of the flow structure in the precessing cylindrical vessel. Consequently, we have performed series of precession measurements with Ultrasonic flow velocimetry (UDV) on the downscaled water experiment with various precession angles α at 60o, 75o, 90o [4]. In this paper, we present the effect of precession angle and rotation direction (i.e. prograde or retrograde) on the dominant flow modes, and quantify this behaviour in dependence of the rotation rate parameterized by the Reynolds number Re = ΩcR2/ν and the precession ratio Po = Ωp/Ωc, with ν the viscosity and Ωp = 2πfp the angular frequency of the precession. We have not taken into account the effect of the precession angle, which changes the definition of Reynolds number. The experimental results are supported by numerical simulations.

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Permalink: https://www.hzdr.de/publications/Publ-35615
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