Publications Repository - Helmholtz-Zentrum Dresden-Rossendorf

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41396 Publications

Deep point embedding for urban classification using ALS point clouds: A new perspective from local to global

Huang, R.; Xu, Y.; Hong, D.; Yao, W.; Ghamisi, P.; Stilla, U.

Semantic interpretation of the 3D scene is one of the most challenging problems in point cloud processing, which also deems as an essential task in a wide variety of point cloud applications. The core task of semantic interpretation is semantic labeling, namely, obtaining a unique semantic label for each point in the point cloud. Despite several reported approaches, semantic labeling continues to be a challenge owing to the complexity of scenes, objects of various scales, and the non-homogeneity of unevenly distributed points. In this paper, we propose a novel method for obtaining semantic labels of airborne laser scanning (ALS) point clouds involving the embedding of local context information for each point with multi-scale deep learning, nonlinear manifold learning for feature dimension reduction, and global graph-based optimization for refining the classification results. Specifically, we address the tasks of learning discriminative features and global labeling smoothing. The key contribution of our study is threefold. First, a hierarchical data augmentation strategy is applied to enhance the learning of deep features based on the PointNet++ network and simultaneously eliminate the artifacts caused by division and sampling while dealing with large-scale datasets. Subsequently, the learned hierarchical deep features are globally optimized and embedded into a low-dimensional space with a nonlinear manifold-based joint learning method with the removal of redundant and disturbing information. Finally, a graph-structured optimization based on the Markov random fields algorithm is performed to achieve global optimization of the initial classification results that are obtained using the embedded deep features by constructing a weighted indirect graph and solving the optimization problem with graph-cuts. We conducted thorough experiments on ALS point cloud datasets to assess the performance of our framework. Results indicate that compared to other commonly used advanced classification methods, our method can achieve high classification accuracy. The overall accuracy (OA) of our approach on the ISPRS benchmark dataset can scale up to 83.2% for classifying nine semantic classes, thereby outperforming other compared point-based strategies. Additionally, we evaluated our framework on a selected portion of the AHN3 dataset, which provided OA up to 91.2%.

Permalink: https://www.hzdr.de/publications/Publ-31968
Publ.-Id: 31968


Texture-Aware Total Variation-Based Sun Glint Removal of Hyperspectral Images

Duan, P.; Lai, J.; Kang, J.; Kang, X.; Ghamisi, Pedram; Li, S.

Sun glint in hyperspectral images (HSIs) leads to undesirable spectral interference, which severely affects subsequent image interpretation, such as environmental monitoring of coastal areas. Sun glint removal methods aim to recover a high quality image without sun glint from the original image. Most methods depend on an assumption that the near infrared band is strongly absorbed by water. However, this assumption is not always reliable because the infrared radiation in shallow or turbid water can be reflected back by the seabed or sediment, rather than being fully absorbed. Therefore, the reflected infrared radiation still contains sun glint and these methods cannot sufficiently remove sun glint from HSIs. To address this problem, a texture-aware total variation (TATV)-based method is proposed to remove sun glint from HSIs. The original HSI first is formulated as a desired clean image and a sun glint image. Then, in order to remove the sun glint, we propose a variational model where the different spectral characteristics of sun glint and other surrounding materials are considered. Specifically, we propose a texture-aware total variation regularized method to heavily penalize the variation of the sun glint areas. Experiments performed on simulated and real data sets demonstrate that our method can greatly outperform other state-of-the-art methods in removing sun glint.

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Permalink: https://www.hzdr.de/publications/Publ-31967
Publ.-Id: 31967


Machine learning information fusion in Earth observation: A comprehensive review of methods, applications and data sources

Salcedo-Sanz, S.; Ghamisi, P.; Piles, M.; Werner, M.; Cuadra, L.; Moreno-Martínez, A.; Izquierdo-Verdiguier, E.; Muñoz-Marí, J.; Amirhosein, M.; Camps-Valls, G.

This paper reviews the most important information fusion data-driven algorithms based on Machine Learning (ML) techniques for problems in Earth observation. Nowadays we observe and model the Earth with a wealth of observations, from a plethora of different sensors, measuring states, fluxes, processes and variables, at unprecedented spatial and temporal resolutions. Earth observation is well equipped with remote sensing systems, mounted on satellites and airborne platforms, but it also involves in-situ observations, numerical models and social media data streams, among other data sources. Data-driven approaches, and ML techniques in particular, are the natural choice to extract significant information from this data deluge. This paper produces a thorough review of the latest work on information fusion for Earth observation, with a practical intention, not only focusing on describing the most relevant previous works in the field, but also the most important Earth observation applications where ML information fusion has obtained significant results. We also review some of the most currently used data sets, models and sources for Earth observation problems, describing their importance and how to obtain the data when needed. Finally, we illustrate the application of ML data fusion with a representative set of case studies, as well as we discuss and outlook the near future of the field.

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Permalink: https://www.hzdr.de/publications/Publ-31966
Publ.-Id: 31966


Deep Metric Learning Based on Scalable Neighborhood Components for Remote Sensing Scene Characterization

Kang, J.; Fernandez-Beltran, R.; Ye, Z.; Tong, X.; Ghamisi, P.; Plaza, A.

With the development of convolutional neural networks (CNNs), the semantic understanding of remote sensing (RS) scenes has been significantly improved based on their prominent feature encoding capabilities. While many existing deep-learning models focus on designing different architectures, only a few works in the RS field have focused on investigating the performance of the learned feature embeddings and the associated metric space. In particular, two main loss functions have been exploited: the contrastive and the triplet loss. However, the straightforward application of these techniques to RS images may not be optimal in order to capture their neighborhood structures in the metric space due to the insufficient sampling of image pairs or triplets during the training stage and to the inherent semantic complexity of remotely sensed data. To solve these problems, we propose a new deep metric learning approach, which overcomes the limitation on the class discrimination by means of two different components: 1) scalable neighborhood component analysis (SNCA) that aims at discovering the neighborhood structure in the metric space and 2) the cross-entropy loss that aims at preserving the class discrimination capability based on the learned class prototypes. Moreover, in order to preserve feature consistency among all the minibatches during training, a novel optimization mechanism based on momentum update is introduced for minimizing the proposed loss. An extensive experimental comparison (using several state-of-the-art models and two different benchmark data sets) has been conducted to validate the effectiveness of the proposed method from different perspectives, including: 1) classification; 2) clustering; and 3) image retrieval. The related codes of this article will be made publicly available for reproducible research by the community.

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Permalink: https://www.hzdr.de/publications/Publ-31965
Publ.-Id: 31965


An Efficient Deep Unsupervised Superresolution Model for Remote Sensing Images

Sheikholeslami, M. M.; Nadi, S.; Naeini, A. A.; Ghamisi, P.

Superresolution (SR) has provided an effective solution to the increasing need for high-resolution images in remote sensing applications. Among various SR methods, deep learning-based SR (DLSR) has made a significant breakthrough. However, supervised DLSR methods require a considerable amount of training data, which is hardly available in the remote sensing field. To address this issue, some research works have recently proposed and revealed the capability of deep learning in unsupervised SR. This article presents an efficient unsupervised SR (EUSR) deep learning model using dense skip connections, which boosts the reconstruction performance in parallel with the reduction of computational burden. To do this, several blocks containing densely connected convolutional layers are implemented to increase the depth of the model. Some skip connections also concatenate feature maps of different blocks to enable better SR performance. Moreover, a bottle-neck block abstracts the feature maps in fewer feature maps to remarkably reduce the computational burden. According to our experiments, the proposed EUSR leads to better results than the state-of-the-art DLSR method in terms of reconstruction quality with less computational burden. Furthermore, results indicate that the EUSR is more robust than its rival in dealing with images of different classes and larger sizes.

Permalink: https://www.hzdr.de/publications/Publ-31964
Publ.-Id: 31964


COVID-19 Outbreak Prediction with Machine Learning

Ardabili, S. F.; Mosavi, A.; Ghamisi, Pedram; Ferdinand, F.; Varkonyi-Koczy, A. R.; Reuter, U.; Rabczuk, T.; Atkinson, P. M.

Several outbreak prediction models for COVID-19 are being used by officials around the world to make informed decisions and enforce relevant control measures. Among the standard models for COVID-19 global pandemic prediction, simple epidemiological and statistical models have received more attention by authorities, and these models are popular in the media. Due to a high level of uncertainty and lack of essential data, standard models have shown low accuracy for long-term prediction. Although the literature includes several attempts to address this issue, the essential generalization and robustness abilities of existing models need to be improved. This paper presents a comparative analysis of machine learning and soft computing models to predict the COVID-19 outbreak as an alternative to susceptible–infected–recovered (SIR) and susceptible-exposed-infectious-removed (SEIR) models. Among a wide range of machine learning models investigated, two models showed promising results (i.e., multi-layered perceptron, MLP; and adaptive network-based fuzzy inference system, ANFIS). Based on the results reported here, and due to the highly complex nature of the COVID-19 outbreak and variation in its behavior across nations, this study suggests machine learning as an effective tool to model the outbreak. This paper provides an initial benchmarking to demonstrate the potential of machine learning for future research. This paper further suggests that a genuine novelty in outbreak prediction can be realized by integrating machine learning and SEIR models.

Permalink: https://www.hzdr.de/publications/Publ-31963
Publ.-Id: 31963


COVID-19 Pandemic Prediction for Hungary; A Hybrid Machine Learning Approach

Pinter, G.; Felde, I.; Mosavi, A.; Ghamisi, Pedram; Gloaguen, R.

Several epidemiological models are being used around the world to project the number of infected individuals and the mortality rates of the COVID-19 outbreak. Advancing accurate prediction models is of utmost importance to take proper actions. Due to the lack of essential data and uncertainty, the epidemiological models have been challenged regarding the delivery of higher accuracy for long-term prediction. As an alternative to the susceptible-infected-resistant (SIR)-based models, this study proposes a hybrid machine learning approach to predict the COVID-19, and we exemplify its potential using data from Hungary. The hybrid machine learning methods of adaptive network-based fuzzy inference system (ANFIS) and multi-layered perceptron-imperialist competitive algorithm (MLP-ICA) are proposed to predict time series of infected individuals and mortality rate. The models predict that by late May, the outbreak and the total morality will drop substantially. The validation is performed for 9 days with promising results, which confirms the model accuracy. It is expected that the model maintains its accuracy as long as no significant interruption occurs. This paper provides an initial benchmarking to demonstrate the potential of machine learning for future research.

Permalink: https://www.hzdr.de/publications/Publ-31962
Publ.-Id: 31962


Remote Sensing Image Classification Using Subspace Sensor Fusion

Rasti, B.; Ghamisi, P.

The amount of remote sensing and ancillary datasets captured by diverse airborne and spaceborne sensors has been tremendously increased, which opens up the possibility of utilizing multimodal datasets to improve the performance of processing approaches with respect to the application at hand. However, developing a generic framework with high generalization capability that can effectively fuse diverse datasets is a challenging task since the current approaches are usually only applicable to two specific sensors for data fusion. In this paper, we propose an accurate fusion-based technique called SubFus with capability to integrate diverse remote sensing data for land cover classification. Here, we assume that a high dimensional multisensor dataset can be represented fused features that live in a lower-dimensional space. The proposed classification methodology includes three main stages. First, spatial information is extracted by using spatial filters (i.e., morphology filters). Then, a novel low- rank minimization problem is proposed to represent the multisensor datasets in subspaces using fused features. The fused features in the lower-dimensional subspace are estimated using a novel iterative algorithm based on the alternative direction method of multipliers. Third, the final classification map is produced by applying a supervised spectral classifier (i.e., random forest) on the fused features. In the experiments, the proposed method is applied to a three-sensor (RGB, multispectral LiDAR, and hyperspectral images) dataset captured over the area of the University of Houston, the USA, and a two-sensor (hyperspectral and LiDAR) dataset captured over the city of Trento, Italy. The land-cover maps generated using SubFus are evaluated based on classification accuracies. Experimental results obtained by SubFus confirm considerable improvements in terms of classification accuracies compared with the other methods used in the experiments. The proposed fusion approach obtains 85.32% and 99.25% in terms of overall classification accuracy on the Houston (the training portion of the dataset distributed for the data fusion contest of 2018) and trento datasets, respectively.

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Permalink: https://www.hzdr.de/publications/Publ-31961
Publ.-Id: 31961


Support Vector Machine Versus Random Forest for Remote Sensing Image Classification: A Meta-Analysis and Systematic Review

Sheykhmousa, M.; Mahdianpari, M.; Ghanbari, H.; Mohammadimanesh, F.; Ghamisi, P.; Homayouni, S.

Several machine-learning algorithms have been proposed for remote sensing image classification during the past two decades. Among these machine learning algorithms, Random Forest (RF) and Support Vector Machines (SVM) have drawn attention to image classification in several remote sensing applications. This article reviews RF and SVM concepts relevant to remote sensing image classification and applies a meta-analysis of 251 peer-reviewed journal papers. A database with more than 40 quantitative and qualitative fields was constructed from these reviewed papers. The meta-analysis mainly focuses on 1) the analysis regarding the general characteristics of the studies, such as geographical distribution, frequency of the papers considering time, journals, application domains, and remote sensing software packages used in the case studies, and 2) a comparative analysis regarding the performances of RF and SVM classification against various parameters, such as data type, RS applications, spatial resolution, and the number of extracted features in the feature engineering step. The challenges, recommendations, and potential directions for future research are also discussed in detail. Moreover, a summary of the results is provided to aid researchers to customize their efforts in order to achieve the most accurate results based on their thematic applications.

Permalink: https://www.hzdr.de/publications/Publ-31960
Publ.-Id: 31960


Data Science in Economics: Comprehensive Review of Advanced Machine Learning and Deep Learning Methods

Nosratabadi, S.; Mosavi, A.; Duan, P.; Ghamisi, Pedram; Filip, F.; Band, S. S.; Reuter, U.; Gama, J.; Gandomi, A. H.

This paper provides a comprehensive state-of-the-art investigation of the recent advances in data science in emerging economic applications. The analysis is performed on the novel data science methods in four individual classes of deep learning models, hybrid deep learning models, hybrid machine learning, and ensemble models. Application domains include a broad and diverse range of economics research from the stock market, marketing, and e-commerce to corporate banking and cryptocurrency. Prisma method, a systematic literature review methodology, is used to ensure the quality of the survey. The findings reveal that the trends follow the advancement of hybrid models, which outperform other learning algorithms. It is further expected that the trends will converge toward the evolution of sophisticated hybrid deep learning models.

Permalink: https://www.hzdr.de/publications/Publ-31959
Publ.-Id: 31959


Multiscale Densely-Connected Fusion Networks for Hyperspectral Images Classification

Xie, J.; He, N.; Fang, L.; Ghamisi, P.

Convolutional neural network (CNN) has demonstrated to be a powerful tool for hyperspectral images (HSIs) classification. Previous CNN-based HSI classification methods only adopt the fixed-size patches to train the CNN model, and such single scale patches may not reflect the complex spatial structural information in the HSIs. In addition, although different layers of CNN can extract features of multiple scales, the traditional CNN model can only utilize features from the highest level for the classification task. These features, however, do not fully consider the strong complementary yet correlated information among different layers. To address these issues, in this paper, a multiscale densely-connected convolutional network (MS-DenseNet) framework is proposed to sufficiently exploit multiple scales information for the HSIs classification. Specifically, for each pixel, the MS-DenseNet, first, extracts its surrounding patches of multiple scales. These patches can separately constitute multiple scale training and testing samples. Within each specific scale sample, instead of using the forward convolutional layers, the MS-DenseNet adopts the dense blocks, which can connect each layer to other layers in a feed-forward fashion and thus can exploit the information among different layers for training and testing. Furthermore, since high correlations exist in patches of different scales, the MS-DenseNet introduces several dense blocks to fuse the multiscale information among different layers for the final HSI classification. Experimental results on several real HSIs demonstrate the superiority of the proposed MS-DenseNet over single scale-based CNN classification model and several well-known classification methods.

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Permalink: https://www.hzdr.de/publications/Publ-31958
Publ.-Id: 31958


Fusion of Dual Spatial Information for Hyperspectral Image Classification

Duan, P.; Ghamisi, P.; Kang, X.; Rasti, B.; Li, S.; Gloaguen, R.

The inclusion of spatial information into spectral classifiers for fine-resolution hyperspectral imagery has led to significant improvements in terms of classification performance. The task of spectral-spatial hyperspectral image classification has remained challenging because of high intraclass spectrum variability and low interclass spectral variability. This fact has made the extraction of spatial information highly active. In this work, a novel hyperspectral image classification framework using the fusion of dual spatial information is proposed, in which the dual spatial information is built by both exploiting pre-processing feature extraction and post-processing spatial optimization. In the feature extraction stage, an adaptive texture smoothing method is proposed to construct the structural profile (SP), which makes it possible to precisely extract discriminative features from hyperspectral images. The SP extraction method is used here for the first time in the remote sensing community. Then, the extracted SP is fed into a spectral classifier. In the spatial optimization stage, a pixel-level classifier is used to obtain the class probability followed by an extended random walker-based spatial optimization technique. Finally, a decision fusion rule is utilized to fuse the class probabilities obtained by the two different stages. Experiments performed on three data sets from different scenes illustrate that the proposed method can outperform other state-of-the-art classification techniques. In addition, the proposed feature extraction method, i.e., SP, can effectively improve the discrimination between different land covers.

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Permalink: https://www.hzdr.de/publications/Publ-31957
Publ.-Id: 31957


Spatial Analysis of Seasonal Precipitation over Iran: Co-Variation with Climate Indices

Dehghani, M.; Salehi, S.; Mosavi, A.; Nabipour, N.; Shamshirband, S.; Ghamisi, P.

Temporary changes in precipitation may lead to sustained and severe drought or massive floods in different parts of the world. Knowing the variation in precipitation can effectively help the water resources decision-makers in water resources management. Large-scale circulation drivers have a considerable impact on precipitation in different parts of the world. In this research, the impact of El Niño-Southern Oscillation (ENSO), Pacific Decadal Oscillation (PDO), and North Atlantic Oscillation (NAO) on seasonal precipitation over Iran was investigated. For this purpose, 103 synoptic stations with at least 30 years of data were utilized. The Spearman correlation coefficient between the indices in the previous 12 months with seasonal precipitation was calculated, and the meaningful correlations were extracted. Then, the month in which each of these indices has the highest correlation with seasonal precipitation was determined. Finally, the overall amount of increase or decrease in seasonal precipitation due to each of these indices was calculated. Results indicate the Southern Oscillation Index (SOI), NAO, and PDO have the most impact on seasonal precipitation, respectively. Additionally, these indices have the highest impact on the precipitation in winter, autumn, spring, and summer, respectively. SOI has a diverse impact on winter precipitation compared to the PDO and NAO, while in the other seasons, each index has its special impact on seasonal precipitation. Generally, all indices in different phases may decrease the seasonal precipitation up to 100%. However, the seasonal precipitation may increase more than 100% in different seasons due to the impact of these indices. The results of this study can be used effectively in water resources management and especially in dam operation.

Permalink: https://www.hzdr.de/publications/Publ-31956
Publ.-Id: 31956


Classification of Hyperspectral and LiDAR Data Using Coupled CNNs

Hang, R.; Li, Z.; Ghamisi, P.; Hong, D.; Xia, G.; Liu, Q.

In this article, we propose an efficient and effective framework to fuse hyperspectral and light detection and ranging (LiDAR) data using two coupled convolutional neural networks (CNNs). One CNN is designed to learn spectral-spatial features from hyperspectral data, and the other one is used to capture the elevation information from LiDAR data. Both of them consist of three convolutional layers, and the last two convolutional layers are coupled together via a parameter-sharing strategy. In the fusion phase, feature-level and decision-level fusion methods are simultaneously used to integrate these heterogeneous features sufficiently. For the feature-level fusion, three different fusion strategies are evaluated, including the concatenation strategy, the maximization strategy, and the summation strategy. For the decision-level fusion, a weighted summation strategy is adopted, where the weights are determined by the classification accuracy of each output. The proposed model is evaluated on an urban data set acquired over Houston, USA, and a rural one captured over Trento, Italy. On the Houston data, our model can achieve a new record overall accuracy (OA) of 96.03%. On the Trento data, it achieves an OA of 99.12%. These results sufficiently certify the effectiveness of our proposed model.

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Permalink: https://www.hzdr.de/publications/Publ-31955
Publ.-Id: 31955


Fusion of Multispectral LiDAR and Hyperspectral Imagery

Rasti, B.; Ghamisi, P.; Gloaguen, R.

This paper presents a technique for the fusion of multispectral LiDAR and hyperspectral data. The proposed method is based on the fusion of the features of multispectral LiDAR and hyperspectral data projected in two different subspaces. First, the spatial features are extracted from both data using morphological filters. Then, the fused features are estimated by proposing a novel constraint penalized cost function. The estimated fused features are used for the purpose of mapping. The classification accuracies obtained by applying a random forest classifier on the fused data confirm considerable improvements compared with the other methods used in the experiments.

  • Contribution to proceedings
    IEEE International Geoscience and Remote Sensing Symposium (IGARSS), 26.09.2020, Virtual (Online), Virtual (Online)
    IGARSS 2020 - 2020 IEEE International Geoscience and Remote Sensing Symposium
    DOI: 10.1109/IGARSS39084.2020.9323179
    Cited 4 times in Scopus

Permalink: https://www.hzdr.de/publications/Publ-31954
Publ.-Id: 31954


Spatial hazard assessment of the PM10 using machine learning models in Barcelona, Spain

Choubin, B.; Abdolshahnejad, M.; Moradi, E.; Querol, X.; Mosavi, A.; Shamshirband, S.; Ghamisi, P.

Air pollution, and especially atmospheric particulate matter (PM), has a profound impact on human mortality and morbidity, environment, and ecological system. Accordingly, it is very relevant predicting air quality. Although the application of the machine learning (ML) models for predicting air quality parameters, such as PM concentrations, has been evaluated in previous studies, those on the spatial hazard modeling of them are very limited. Due to the high potential of the ML models, the spatial modeling of PM can help managers to identify the pollution hotspots. Accordingly, this study aims at developing new ML models, such as Random Forest (RF), Bagged Classification and Regression Trees (Bagged CART), and Mixture Discriminate Analysis (MDA) for the hazard prediction of PM10 (particles with a diameter less than 10 µm) in the Barcelona Province, Spain. According to the annual PM10 concentration in 75 stations, the healthy and unhealthy locations are determined, and a ratio 70/30 (53/22 stations) is applied for calibrating and validating the ML models to predict the most hazardous areas for PM10. In order to identify the influential variables of PM modeling, the simulated annealing (SA) feature selection method is used. Seven features, among the thirteen features, are selected as critical features. According to the results, all the three-machine learning (ML) models achieve an excellent performance (Accuracy > 87% and precision > 86%). However, the Bagged CART and RF models have the same performance and higher than the MDA model. Spatial hazard maps predicted by the three models indicate that the high hazardous areas are located in the middle of the Barcelona Province more than in the Barcelona’s Metropolitan Area.

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Permalink: https://www.hzdr.de/publications/Publ-31953
Publ.-Id: 31953


Invariant Attribute Profiles: A Spatial-Frequency Joint Feature Extractor for Hyperspectral Image Classification

Hong, D.; Wu, X.; Ghamisi, P.; Chanussot, J.; Yokoya, N.; Zhu, X. X.

So far, a large number of advanced techniques have been developed to enhance and extract the spatially semantic information in hyperspectral image processing and analysis. However, locally semantic change, such as scene composition, relative position between objects, spectral variability caused by illumination, atmospheric effects, and material mixture, has been less frequently investigated in modeling spatial information. Consequently, identifying the same materials from spatially different scenes or positions can be difficult. In this article, we propose a solution to address this issue by locally extracting invariant features from hyperspectral imagery (HSI) in both spatial and frequency domains, using a method called invariant attribute profiles (IAPs). IAPs extract the spatial invariant features by exploiting isotropic filter banks or convolutional kernels on HSI and spatial aggregation techniques (e.g., superpixel segmentation) in the Cartesian coordinate system. Furthermore, they model invariant behaviors (e.g., shift, rotation) by the means of a continuous histogram of oriented gradients constructed in a Fourier polar coordinate. This yields a combinatorial representation of spatial-frequency invariant features with application to HSI classification. Extensive experiments conducted on three promising hyperspectral data sets (Houston2013 and Houston2018) to demonstrate the superiority and effectiveness of the proposed IAP method in comparison with several state-of-the-art profile-related techniques. The codes will be available from the website: https://sites.google.com/view/danfeng-hong/data-code.

Permalink: https://www.hzdr.de/publications/Publ-31952
Publ.-Id: 31952


Multilevel Structure Extraction-Based Multi-Sensor Data Fusion

Duan, P.; Kang, X.; Ghamisi, P.; Liu, Y.

Multi-sensor data on the same area provide complementary information, which is helpful for improving the discrimination capability of classifiers. In this work, a novel multilevel structure extraction method is proposed to fuse multi-sensor data. This method is comprised of three steps: First, multilevel structure extraction is constructed by cascading morphological profiles and structure features, and is utilized to extract spatial information from multiple original images. Then, a low-rank model is adopted to integrate the extracted spatial information. Finally, a spectral classifier is employed to calculate class probabilities, and a maximum posteriori estimation model is used to decide the final labels. Experiments tested on three datasets including rural and urban scenes validate that the proposed approach can produce promising performance with regard to both subjective and objective qualities.

Permalink: https://www.hzdr.de/publications/Publ-31951
Publ.-Id: 31951


High-Rankness Regularized Semi-Supervised Deep Metric Learning for Remote Sensing Imagery

Kang, J.; Fernández-Beltrán, R.; Ye, Z.; Tong, X.; Ghamisi, P.; Plaza, A.

Deep metric learning has recently received special attention in the field of remote sensing (RS) scene characterization, owing to its prominent capabilities for modeling distances among RS images based on their semantic information. Most of the existing deep metric learning methods exploit pairwise and triplet losses to learn the feature embeddings with the preservation of semantic-similarity, which requires the construction of image pairs and triplets based on the supervised information (e.g., class labels). However, generating such semantic annotations becomes a completely unaffordable task in large-scale RS archives, which may eventually constrain the availability of sufficient training data for this kind of models. To address this issue, we reformulate the deep metric learning scheme in a semi-supervised manner to effectively characterize RS scenes. Specifically, we aim at learning metric spaces by utilizing the supervised information from a small number of labeled RS images and exploring the potential decision boundaries for massive sets of unlabeled aerial scenes. In order to reach this goal, a joint loss function, composed of a normalized softmax loss with margin and a high-rankness regularization term, is proposed, as well as its corresponding optimization algorithm. The conducted experiments (including different state-of-the-art methods and two benchmark RS archives) validate the effectiveness of the proposed approach for RS image classification, clustering and retrieval tasks. The codes of this paper are publicly available.

Permalink: https://www.hzdr.de/publications/Publ-31950
Publ.-Id: 31950


A Multi-Sensor Fusion Framework Based on Coupled Residual Convolutional Neural Networks

Li, H.; Ghamisi, P.; Rasti, B.; Wu, Z.; Shapiro, A.; Schultz, M.; Zipf, A.

Multi-sensor remote sensing image classification has been considerably improved by deep learning feature extraction and classification networks. In this paper, we propose a novel multi-sensor fusion framework for the fusion of diverse remote sensing data sources. The novelty of this paper is grounded in three important design innovations: 1- a unique adaptation of the coupled residual networks to address multi-sensor data classification; 2- a smart auxiliary training via adjusting the loss function to address classifications with limited samples; and 3- a unique design of the residual blocks to reduce the computational complexity while preserving the discriminative characteristics of multi-sensor features. The proposed classification framework is evaluated using three different remote sensing datasets: the urban Houston university datasets (including Houston 2013 and the training portion of Houston 2018) and the rural Trento dataset. The proposed framework achieves high overall accuracies of 93.57%, 81.20%, and 98.81% on Houston 2013, the training portion of Houston 2018, and Trento datasets, respectively. Additionally, the experimental results demonstrate considerable improvements in classification accuracies compared with the existing state-of-the-art methods.

Permalink: https://www.hzdr.de/publications/Publ-31949
Publ.-Id: 31949


Creation of Gold Nanoparticles in ZnO by Ion Implantation–DFT and Experimental Studies

Cajzl, J.; Jeníčková, K.; Nekvindová, P.; Michalcová, A.; Veselý, M.; Macková, A.; Malinský, P.; Jágerová, A.; Mikšová, R.; Akhmadaliev, S.

Three different crystallographic orientations of the wurtzite ZnO structure (labeled as c-plane, a-plane and m-plane) were implanted with Au + ions using various energies and fluences to form gold nanoparticles (GNPs). The ion implantation process was followed by annealing at 600°C in an oxygen atmosphere to decrease the number of unwanted defects and improve luminescence properties. With regard to our previous publications, the paper provides a summary of theoretical and experimental results, i.e., both DFT and FLUX simulations, as well as experimental results from TEM, HRTEM, RBS, RBS/C, Raman spectroscopy and photoluminescence. From the results, it follows that in the ZnO structure, implanted gold atoms are located in random interstitial positions—experimentally, the amount of interstitial gold atoms increased with increasing ion implantation fluence. During ion implantation and subsequent annealing, the metal clusters and nanoparticles with sizes from 2 to 20 nm were formed. The crystal structure of the resulting gold was not cubic (confirmed by diffraction patterns), but it had a hexagonal close-packed (hcp) arrangement. The ion implantation of gold leads to the creation of Zn and O interstitial defects and extended defects with distinct character in various crystallographic cuts of ZnO, where significant O-sublattice disordering occurred in m-plane ZnO.

Keywords: gold; ZnO; nanoparticles; ion implantation; luminescence; DFT; RBS

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Permalink: https://www.hzdr.de/publications/Publ-31948
Publ.-Id: 31948


ComputationalRadiationPhysics/picongpu: Perfectly Matched Layer (PML) and Bug Fixes

Hübl, A.; Widera, R.; Worpitz, B.; Pausch, R.; Burau, H.; Garten, M.; Starke, S.; Grund, A.; Debus, A.; Matthes, A.; Bastrakov, S.; Steiniger, K.; Göthel, I.; Rudat, S.; Kelling, J.; Bussmann, M.

This release adds a new field absorber for the Yee solver, convolutional perfectly matched layer (PML). Compared to the still supported exponential damping absorber, PML provides better absorption rate and much less spurious reflections.

We added new plugins for computing emittance and transition radiation, particle rendering with the ISAAC plugin, Python tools for reading and visualizing output of a few plugins.

The release also adds a few quality-of-life features, including a new memory calculator, better command-line experience with new options and bash-completion, improved error handling, cleanup of the example setups, and extensions to documentation.

Please refer to our ChangeLog for a full list of features, fixes and user interface changes before getting started.

Thanks to Igor Andriyash, Sergei Bastrakov, Xeinia Bastrakova, Andrei Berceanu, Finn-Ole Carstens, Alexander Debus, Jian Fuh Ong, Marco Garten, Axel Huebl, Sophie Rudat (Koßagk), Anton Lebedev, Felix Meyer, Pawel Ordyna, Richard Pausch, Franz Pöschel, Adam Simpson, Sebastian Starke, Klaus Steiniger, René Widera for contributions to this release!

Keywords: PIConGPU; Particle-in-Cell; Laser; Plasma

  • Software in external data repository
    Publication year 2020
    Programming language: C++, Python, Shell, CMake, Dockerfile, Awk
    System requirements: Computer
    License: GPLv3+, LGPLv3+, CC-BY 4.0 (Link to license text)
    Hosted on https://github.com/ComputationalRadiationPhysics/picongpu:
    DOI: 10.5281/zenodo.3875374

Permalink: https://www.hzdr.de/publications/Publ-31947
Publ.-Id: 31947


In vitro and in vivo evaluation of fluorinated indanone derivatives as potential positron emission tomography agents for the imaging of monoamine oxidase B in the brain

Dukic-Stefanovic, S.; Lai, T. H.; Toussaint, M.; Clauß, O.; Jevtić, I. I.; Penjišević, J. Z.; Andrić, D.; Ludwig, F.-A.; Gündel, D.; Deuther-Conrad, W.; Kostić-Rajačić, S. V.; Brust, P.; Teodoro, R.

Monoamine oxidases (MAOs) play a key role in the metabolism of major monoamine neurotransmitters. In particular, the upregulation of MAO-B in Parkinson’s disease, Alzheimer’s disease and cancer augmented the development of selective MAO-B inhibitors for diagnostic and therapeutic purposes, such as the anti-parkinsonian MAO-B irreversible binder L-deprenyl (Selegiline®). Herein we report on the synthesis of novel fluorinated indanone derivatives for PET imaging of MAO-B in the brain. Out of our series, the derivatives 6, 8, 9 and 13 are amongst the most affine and selective ligands for MAO-B reported so far. For the derivative 6-((3-fluorobenzyl)oxy)-2,3-dihydro-1H-inden-1-one (6) exhibiting an outstanding affinity (Ki MAO-B = 6 nM), an automated copper-mediated radiofluorination starting from the pinacol boronic ester 17 is described. An in vitro screening in different species revealed a MAO-B region-specific accumulation of [18F]6 in rats and piglets in comparison to L-[3H]deprenyl. The pre-clinical in vivo assessment of [18F]6 in mice demonstrated the potential of indanones to readily cross the blood-brain barrier. Nonetheless, parallel in vivo metabolism studies indicated the presence of blood-brain barrier metabolites, thus arguing for further structural modifications. With the matching analytical profiles of the radiometabolite analysis from the in vitro liver microsome studies and the in vivo evaluation, the structure’s elucidation of the blood-brain barrier penetrant radiometabolites is possible and will serve as basis for the development of new indanone derivatives suitable for the PET imaging of MAO-B.

Keywords: MAO-B; PET tracers; fluorine-18; copper-mediated radiofluorination; indanone derivatives

Permalink: https://www.hzdr.de/publications/Publ-31946
Publ.-Id: 31946


Domain wall damping in ultrathin nanostripes with Dzyaloshinskii-Moriya interaction

Volkov, O.; Kronast, F.; Abert, C.; Oliveros Mata, E. S.; Kosub, T.; Makushko, P.; Erb, D.; Pylypovskyi, O.; Mawass, M.-A.; Sheka, D.; Zhou, S.; Faßbender, J.; Makarov, D.

Asymmetrically sandwiched thin magnetic layers with perpendicular anisotropy and Dzyaloshinskii-Moriya interaction (DMI) is the prospective material science platform for spin-orbitronic technologies that rely on the motion of chiral magnetic textures, like skyrmions or chiral domain walls (DWs). The dynamic performance of a DW-based racetracks is defined by the strength of DMI and the DW damping. The determination of the latter parameter is typically done based on technically challenging DW motion experiments. Here, we propose a method to access both parameters, DMI constant and DW damping, yet in static experiments by monitoring the tilt of magnetic DWs in nanostripes. We experimentally demonstrate that in perpendicularly magnetized //CrO x /Co/Pt stacks, DWs can be trapped on edge roughness in a metastable tilted state as a result of the DW dynamics driven by external magnetic field. The measured tilt can be correlated to the DMI strength and DW damping in a self-consistent way in the frame of a theoretical formalism based on the collective coordinate approach.

Keywords: Nanomagnetism; Magnetic domains; Dzyaloshinskii-Moriya interaction

Permalink: https://www.hzdr.de/publications/Publ-31945
Publ.-Id: 31945


Depressants in scheelite flotation - Mechanism of sodium carbonate and acidified water glass and the application of process mineralogy

Kupka, N.

The European Union classified tungsten as a Critical Raw Material already in 2011, due to its high economic importance and high supply risk. Tungsten occurs under two main mineral forms, scheelite (CaWO4) and wolframite ((Fe,Mn)WO4), with scheelite’s importance increasing as wolframite resources are progressively depleting. Interest in scheelite is growing fast, as publications show: 15 % of all publications on scheelite flotation since the 1950s were published in 2019. A polar salt type mineral, scheelite is semi-soluble and exhibits a negative charge, almost regardless of the flotation conditions. It is mostly hydrophilic but can easily be floated using chemical reagents, usually at a high pH of 9 to 10. Scheelite flotation has run into serious difficulties when it is associated to a carbonaceous gangue. Other calcium-bearing minerals, such as calcite (CaCO3), apatite (Ca-phosphate) and fluorite (CaF2) all exhibit similar flotation properties and are therefore classified as semi-soluble salt-type minerals. These minerals will tend to float better than scheelite under the same circumstances and not only increase reagent consumption but heavily contaminate the concentrate, making it harder and more expensive to process for the smelter. Several depressants can be used to remedy this problem, the most used one being sodium silicate. However, this reagent is imperfect and its effect can be improved by modifying it or by combining it with other depressants. As a consequence, the focus of this work is to understand the mechanism of two important depressants in scheelite flotation, sodium carbonate and acidified sodium silicate, and linking said mechanism to mineralogy. A third depressant, colloidal silica, is studied from a performance point of view.

Keywords: froth flotation; scheelite; depressants; automated mineralogy

  • Doctoral thesis
    TUBAF, 2020
    Mentor: Prof. Urs Peuker
    174 Seiten

Permalink: https://www.hzdr.de/publications/Publ-31943
Publ.-Id: 31943


Uploading data to the HepDATA repository with Python using hepdata_lib

Müller, S.

Presentation at the "STRONG2020 Meeting on the Hadronic Cross Section database"

  • Lecture (Conference) (Online presentation)
    STRONG2020 Meeting on the hadronic Cross Section database, 18.12.2020, Pisa, Italy

Permalink: https://www.hzdr.de/publications/Publ-31942
Publ.-Id: 31942


LLAMA: Compile time automatic memory layout optimization

Gruber, B. M.

Write code once and perform well on many systems.

  • Open Access Logo Poster
    Polish delegation meeting, 29.09.2020, Görlitz, Germany

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Permalink: https://www.hzdr.de/publications/Publ-31941
Publ.-Id: 31941


Nanoscale mechanics of antiferromagnetic domain walls

Hedrich, N.; Wagner, K.; Pylypovskyi, O.; Shields, B. J.; Kosub, T.; Sheka, D.; Makarov, D.; Maletinsky, P.

Antiferromagnets offer remarkable promise for future spintronics devices, where antiferromagnetic order is exploited to encode information. The control and understanding of antiferromagnetic domain walls (DWs) - the interfaces between domains with differing order parameter orientations - is a key ingredient for advancing such antiferromagnetic spintronics technologies. However, studies of the intrinsic mechanics of individual antiferromagnetic DWs remain elusive since they require sufficiently pure materials and suitable experimental approaches to address DWs on the nanoscale. Here we nucleate isolated, 180° DWs in a single-crystal of Cr2O3, a prototypical collinear magnetoelectric antiferromagnet, and study their interaction with topographic features fabricated on the sample. We demonstrate DW manipulation through the resulting, engineered energy landscape and show that the observed interaction is governed by the DW's elastic properties. Our results advance the understanding of DW mechanics in antiferromagnets and suggest a novel, topographically defined memory architecture based on antiferromagnetic DWs.

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Permalink: https://www.hzdr.de/publications/Publ-31940
Publ.-Id: 31940


Cryogenic Liquid Jets for High Repetition Rate Discovery Science

Curry, C. B.; Schoenwaelder, C.; Goede, S.; Kim, J. B.; Rehwald, M.; Treffer, F.; Zeil, K.; Glenzer, S. H.; Gauthier, M.

This protocol presents a detailed procedure for the operation of continuous, micron-sized cryogenic cylindrical and planar liquid jets. When operated as described here, the jet exhibits high laminarity and stability for centimeters. Successful operation of a cryogenic liquid jet in the Rayleigh regime requires a basic understanding of fluid dynamics and thermodynamics at cryogenic temperatures. Theoretical calculations and typical empirical values are provided as a guide to design a comparable system. This report identifies the importance of both cleanliness during cryogenic source assembly and stability of the cryogenic source temperature once liquefied. The system can be used for high repetition rate laser-driven proton acceleration, with an envisioned application in proton therapy. Other applications include laboratory astrophysics, materials science, and next-generation particle accelerators.

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Permalink: https://www.hzdr.de/publications/Publ-31939
Publ.-Id: 31939


Comparison of experimental STEM conditions for fluctuation electron microscopy

Radic, D.; Hilke, S.; Peterlechner, M.; Posselt, M.; Wilde, G.; Bracht, H.

Variable-resolution fluctuation electron microscopy (VR-FEM) data from measurements on amorphous silicon and PdNiP have been obtained at varying experimental conditions. Measurements have been conducted at identical total electron dose and with an identical electron dose normalized to the respective probe size. STEM probes of different sizes have been created by variation of the semi-convergence angle or by defocus. The results show that defocus yields a reduced normalized variance compared to data from probes created by convergence angle variation. Moreover, the trend of the normalized variance upon probe size variation differs between the two methods. Beam coherence, which affects FEM data, has been analyzed theoretically using geometrical optics on a multi-lens setup and linked to the illumination conditions. Fits to several experimental beam profiles support our geometrical optics theory regarding probe coherence. The normalized variance can be further optimized if one determines the optimal exposure time for the nanobeam diffraction patterns.

Keywords: amorphous materials; coherence; fluctuation electron microscopy; medium-range order; nanobeam diffraction

Related publications

Permalink: https://www.hzdr.de/publications/Publ-31938
Publ.-Id: 31938


Does FLASH deplete Oxygen? Experimental Evaluation for Photons, Protons and Carbon Ions.

Jansen, J.; Knoll, J.; Beyreuther, E.; Pawelke, J.; Skuza, R.; Hanley, R.; Brons, S.; Pagliari, F.; Seco, J.

Purpose: To investigate experimentally, if FLASH irradiation depletes oxygen within water for different radiation types such as photons, protons and carbon ions.
Methods: This study presents measurements of the oxygen consumption in sealed, 3D printed water phantoms during irradiation with X-rays, protons and carbon ions at varying dose rates up to 340Gy/s. The oxygen measurement was performed using an optical sensor allowing for non-invasive measurements.
Results: Oxygen consumption in water only depends on dose, dose-rate and linear energy transfer (LET) of the irradiation. The total amount of oxygen depleted per 10Gy was found to be 0.04 - 0.18% atm for 225 kV photons, 0.04 - 0.25% atm for 224 MeV protons and 0.09 - 0.17% atm for carbon ions. Consumption depends on dose-rate by an inverse power law and saturates for higher dose rates because of self-interactions of radicals. Higher dose rates yield lower oxygen consumption. No total depletion of oxygen was found for clinical doses.
Conclusions: FLASH irradiation does consume oxygen, but not enough to deplete all the oxygen present. For higher dose rates, less oxygen was consumed than at standard radiotherapy dose rates. No total depletion was found for any of the analyzed radiation types for 10Gy dose delivery using FLASH.

Permalink: https://www.hzdr.de/publications/Publ-31937
Publ.-Id: 31937


Implementation of the academic image processing pipeline ExploreASL in an outpatient center using IntelliSpace Discovery

Ganji, S.; Pinter, N.; Petr, J.; Ajtai, B.; Fritz, J.; Mechtler, L.; Husain, S.; Fischer, A.; Barkhof, F.; Mutsaerts, H.

The use of standardized image processing pipelines is continuously increasing in radiological research with developments in computing power, image processing, and machine learning techniques. Early integration of academic processing methods into clinical research workflow would accelerate the translation of promising novel MRI techniques into the clinic. However, the integration of such tools is both resource and time consuming. While most of neurological imaging takes place in outpatient centers, resource and workflow limitations of such clinics do not allow for the application of advanced image analysis. Here, we present the integration the “ExploreASL” into the PACS-connected research platform IntelliSpace Discovery.

  • Poster
    ISMRM 28th Annual Meeting & Exhibition, 14.08.2020, Virtual, Virtual
  • Contribution to proceedings
    ISMRM 28th Annual Meeting & Exhibition, 14.08.2020, Virtual, Virtual

Permalink: https://www.hzdr.de/publications/Publ-31936
Publ.-Id: 31936


Treatment efficacy of asymptomatic carotid artery stenosis patients evaluated by clinically applicable hemodynamic MRI and cognitive testing

Kaczmarz, S.; Göttler, J.; Petr, J.; Sollmann, N.; Schmitzer, L.; Hock, A.; Hansen, M.; Mouridsen, K.; Zimmer, C.; Hyder, F.; Preibisch, C.

Hemodynamic MRI is highly promising to improve treatment decisions in asymptomatic internal carotid artery stenosis (ICAS). However, treatment efficacy evaluations require clinically applicable techniques, such as dynamic susceptibility contrast (DSC) and resting-state BOLD-based evaluations of amplitude of low-frequency fluctuations (ALFF). We present data from 16 asymptomatic ICAS patients before and after treatment and 17 age-matched healthy controls measuring cerebral blood volume (CBV) and capillary transit-time heterogeneity (CTH) by DSC and ALFF with additional cognitive testing. We hypothesized recovery of hemodynamic impairments after revascularization. Our results confirmed this hypothesis for all parameters. Interestingly, at the same time cognitive function remained impaired

  • Lecture (Conference) (Online presentation)
    ISMRM 28th Annual Meeting & Exhibition, 14.08.2020, Virtual, Virtual
  • Contribution to proceedings
    ISMRM 28th Annual Meeting & Exhibition, 14.08.2020, Virtual, Virtual

Permalink: https://www.hzdr.de/publications/Publ-31935
Publ.-Id: 31935


Measurement of intra- and extra-neurite perfusion by combining ASL with the NODDI DWI model

Asllani, I.; Plaindoux, A.; Petr, J.; Woods, J.; van Osch, M.; Cercignani, M.

Intra- and extra-neurite perfusion in gray and white matter were estimated by applying a spatial linear regression algorithm on ASL images using the micro-structural anatomical information derived from the NODDI analysis of the DWI data. Baseline ASL images were acquired with 4 post-labeling delay (PLD) values in order to test the hypothesis of redistribution of ASL signal across the micro-compartments with increasing PLD. Motor activation was used to investigate the sensitivity of the method for detecting changes in perfusion at the micro-structural level.

  • Poster (Online presentation)
    ISMRM 28th Annual Meeting & Exhibition, 14.08.2020, Virtual, Virtual
  • Contribution to proceedings
    ISMRM 28th Annual Meeting & Exhibition, 14.08.2020, Virtual, Virtual

Permalink: https://www.hzdr.de/publications/Publ-31934
Publ.-Id: 31934


The long road from invention to implementation a pan-European neuroradiological survey on quantitative MRI techniques in clinical practice

Keil, V.; Smits, M.; Thust, S.; Petr, J.; Solymosi, L.; Manfrini, E.

This pan-European online survey study revealed that clinically working Neuroradiologists appreciate the additional diagnostic accuracy rendered by quantitative MRI techniques. However, the clinical implementation of many techniques is hampered by a lack of knowledge on how to acquire, post-process and interpret results of multiple quantitative MRI techniques including ASL, CEST/APT, IVIM and others. With exception of DSC and DWI in tumor imaging and stroke, the number of indications is also still limited especially regarding head/neck Radiology and neurodegenerative diseases.

  • Lecture (Conference) (Online presentation)
    ISMRM 28th Annual Meeting & Exhibition, 14.08.2020, Virtual, Virtual
  • Contribution to proceedings
    ISMRM 28th Annual Meeting & Exhibition, 14.08.2020, Virtual, Virtual

Permalink: https://www.hzdr.de/publications/Publ-31933
Publ.-Id: 31933


Differences in quantitative glioma perfusion imaging with ASL and DSC: validation with 15O-H2O PET

Petr, J.; Verburg, N.; Kuijer, J.; Koopman, T.; Keil, V.; Warnert, E.; Barkhof, F.; van den Hoff, J.; Boellaard, R.; de Witt Hamer, P.; Mutsaerts, H.

While agreement between ASL, DSC, and PET perfusion is well established in healthy volunteers, an analogous comparison in gliomas is still missing and more challenging. We compared ASL and DSC perfusion measurements with the gold-standard of 15 O-H 2 O-PET perfusion measurements in eight patients diagnosed with gliomas. We showed the importance of normalization to the contralateral hemisphere, and identified several examples of different regional perfusion as assessed with ASL and DSC and interpreted them using the PET reference.

  • Lecture (Conference) (Online presentation)
    ISMRM 28th Annual Meeting & Exhibition, 14.08.2020, Virtual, Virtual
  • Contribution to proceedings
    ISMRM 28th Annual Meeting & Exhibition, 14.08.2020, Virtual, Virtual

Permalink: https://www.hzdr.de/publications/Publ-31932
Publ.-Id: 31932


Arterial spin labeling signal in the Sagittal Sinus as hemodynamic proxy parameter in patients with sickle cell disease

Afzali-Hashemi, L.; Vaclavu, L.; Petr, J.; Wood, J.; Biemond, B.; Nederveen, A.; Mutsaerts, H.

Higher sagittal sinus signal is present in the ASL images of patients with sickle cell disease (SCD). The purpose of this study was to assess if the signal in the sagittal sinus is correlated with clinical parameters and if this is affected by the vasoactive stimulus. The sagittal sinus signal was measured in patients with SCD and in healthy controls. Signal in sagittal sinus of the SCD patients were significantly correlated with clinical parameters including

  • Poster
    ISMRM 28th Annual Meeting & Exhibition, 14.08.2020, Virtual, Virtual
  • Contribution to proceedings
    ISMRM 28th Annual Meeting & Exhibition, 14.08.2020, Virtual, Virtual

Permalink: https://www.hzdr.de/publications/Publ-31931
Publ.-Id: 31931


Nonlinear plasmonic response in GaAs/InGaAs core/shell nanowires.

Rana, R.; Balaghi, L.; Fotev, I.; Schneider, H.; Helm, M.; Dimakis, E.; Pashkin, O.

We show nonlinear plasmonic response in GaAs/In0.2Ga0.8As nanowires using high field terahertz pulses. With increasing THz field, plasmon resonance is redshifted, and spectral weight decreases indicating an inhomogeneous intervalley electron scattering across the nanowire.

Keywords: Intense Terahertz pulses; Nanowires; Plasmon

  • Poster (Online presentation)
    The 22nd International Conference on Ultrafast Phenomena (UP 2020), 16.-19.11.2020, Shanghai, China

Permalink: https://www.hzdr.de/publications/Publ-31930
Publ.-Id: 31930


ExploreQC: A toolbox for MRI quality control in the EPAD multicentre study

Lorenzini, L.; Ingala, S.; Wottschel, V.; Wink, A. M.; Kuijer, J.; Sudre, C. H.; Haller, S.; Molinuevo, J. L.; Gispert, J. D.; Cash, D. M.; Thomas, D. L.; Vos, S.; Petr, J.; Wolz, R.; Pernet, C.; Waldman, A.; Barkhof, F.; Mutsaerts, H. J. M. M.; Epad, C.

Magnetic Resonance Imaging (MRI) of the brain is prone to artefacts that may worsen image quality and subsequent analyses. Despite the growing number of large-scale multi-institutional imaging studies, standardized approaches for defining inclusion and exclusion criteria on the basis of image data quality are still lacking and quality assessment is often based on visual inspection. We introduce ExploreQC, a MATLAB-based toolbox which implements a semi-automatic pipeline to assess QC metrics, select the most relevant parameters, and to derive informed inclusion thresholds.

  • Open Access Logo Poster (Online presentation)
    Alzheimer's Association International Conference, 27.07.2020, Virtual, Virtual
    DOI: 10.1002/alz.041952
  • Open Access Logo Abstract in refereed journal
    Alzheimer's & Dementia 16(2020), e041952
    DOI: 10.1002/alz.041952

Permalink: https://www.hzdr.de/publications/Publ-31929
Publ.-Id: 31929


ASL perfusion MRI in the follow-up of pediatric brain tumors

Verschuren, S.; Petr, J.; Mutsaerts, H. J.; Plasschaert, S.; Wijnen, J.; Lequin, M.; Wiegers, E.

ASL perfusion MRI in the follow-up of pediatric brain tumors

Permalink: https://www.hzdr.de/publications/Publ-31928
Publ.-Id: 31928


Accumulation of ferromanganese crusts derived from carrier-free 10Be/9Be

Lachner, J.; Ploner, M.; Steier, P.; Sakaguchi, A.; Usui, A.

The occurrence of 10Be in natural archives is commonly used to date their formation and growth on time scales of million years. Accelerator Mass Spectrometry (AMS) can perform a direct measurement of the 10Be/9Be ratio. The carrier-free method, in which no 9Be carrier is added to the original sample, is especially suitable for 10Be/9Be ratio determination in the marine environment. By normalizing the 10Be content to 9Be, temporal variations of Be uptake processes into the archive are eliminated.

Here, we present a simple method for the chemical extraction of beryllium from ferromanganese (FeMn) crusts or nodules, the measurement procedure, and the first carrier-free 10Be/9Be measurements at the 3 MV AMS facility VERA. Several tests of chemical methods are discussed including different options to short-cut and accelerate the procedure for special cases. Results from FeMn crust 237KD from cruise VA13/2 in the Pacific ocean show the known 10Be/9Be distribution with depth that is commonly related to a changing growth rate of the archive. In this context we discuss the potential influence of diffusion and adsorption processes on the age models of FeMn crusts that are based on radioactive nuclides such as 10Be and 230Th. Including an open-system behavior for these isotopes in the description of their profiles allows interpreting the accumulation of crusts with a constant growth rate over millions of years and does not require the assumption of abrupt growth changes.

Keywords: 10Be; Carrier-free 10Be/9Be; AMS; VERA; Ferromanganese crusts

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Permalink: https://www.hzdr.de/publications/Publ-31927
Publ.-Id: 31927


Material requirements for pulsed magnets at the HLD

Zherlitsyn, S.

es hat kein Abstrakt vorgelegen

  • Lecture (Conference) (Online presentation)
    2020 Virtual MRS Spring/ Fall Meeting, 27.11.-04.12.2020, Boston, USA

Permalink: https://www.hzdr.de/publications/Publ-31926
Publ.-Id: 31926


Antisite disorder in the battery material LiFePO4

Werner, J.; Neef, C.; Koo, C.; Zvyagin, S.; Ponomaryov, O.; Klingeler, R.

We report detailed magnetometry and high-frequency electron spin resonance (HF-ESR) measurements which allow detailed investigation on Li-Fe antisite disorder in single-crystalline LiFePO4, i.e., exchange of Fe2+ and Li+ ions. The data imply that magnetic moments of Fe2+ ions at Li positions do not participate in long-range antiferromagnetic order in LiFePO4 but form quasifree moments. Anisotropy axes of the magnetic moments at antisite defects are attached to the main crystallographic directions. The local character of these moments is confirmed by associated linear resonance branches detected by HF-ESR studies. Magnetic anisotropy shows up in significant zero-field splittings of Δ = 220(3) GHz, Δ` ∼ 50 GHz, and a highly anisotropic g factor, i.e., ga = 1.4, gb = 2.0, and gc = 6.3. We demonstrate a general method to precisely determine Fe-antisite disorder in LiFePO4 from magnetic studies which implies a density of paramagnetic Fe2+ ions at Li positions of 0.53%.

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Permalink: https://www.hzdr.de/publications/Publ-31925
Publ.-Id: 31925


Elastic response to the first-order magnetization process of U3Cu4Ge4

Gorbunov, D.

Es hat kein Abstrakt vorgelegen.

  • Invited lecture (Conferences) (Online presentation)
    ARHMF2020 & KINKEN Materials Science School 2020 for Young Scientists, 01.-03.12.2020, Sendai, Japan

Permalink: https://www.hzdr.de/publications/Publ-31924
Publ.-Id: 31924


Data for: A UV laser test facility for precise measurement of gas parameters in gaseous detectors

Fan, X.

It contains the data measured by the device and the simulation data.

Keywords: UV laser

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Permalink: https://www.hzdr.de/publications/Publ-31923
Publ.-Id: 31923


Biplots for Compositional Data Derived from Generalised Joint Diagonalization Methods

Mueller, U.; Tolosana Delgado, R.; Grunsky, E. C.; McKinley, J. M.

Biplots constructed from principal components of a compositional data set are an established means to explore its features. Principal Component Analysis (PCA) is also used to transform a set of spatial variables into spatially decorrelated factors. However, because no spatial structures are accounted for in the transformation the application of PCA is limited. In geostatistics and blind source separation a variety of different matrix diagonalization methods have been developed with the aim to provide spatially or temporally decorrelated factors. Just as PCA, many of these transformations are linear and so lend themselves to the construction of biplots. In this contribution we consider such biplots for a number of methods (MAF, UWEDGE and RJD transformations) and discuss how and if they can contribute to our understanding of relationships between the components of regionalized compositions. A comparison of the biplots with the PCA biplot commonly used in compositional data analysis for the case of data from the Northern Irish geochemical survey shows that the biplots from MAF and UWEDGE are comparable as are those from PCA and RJD. The biplots emphasize different aspects of the regionalized composition: for MAF and UWEDGE the focus is the spatial continuity, while for PCA and RJD it is variance explained. The results indicate that PCA and MAF combined provide adequate and complementary means for exploratory statistical analysis.

Keywords: Semivariogram matrices; Spatial decorrelation; Structural analysis; Geochemical data

Permalink: https://www.hzdr.de/publications/Publ-31922
Publ.-Id: 31922


Data for: Mapping the stray fields of a micromagnet using spin centers in SiC

Bejarano, M.; Trindade Goncalves, F. J.; Hollenbach, M.; Hache, T.; Hula, T.; Berencen, Y.; Faßbender, J.; Helm, M.; Astakhov, G.; Schultheiß, H.

We utilized the following methods to obtain the presented data: optically detected magnetic resonance (ODMR), photoluminescence spectroscopy, and micromagnetic simulations in Mumax3. The experimental data were obtained on the sample which is labeled as: "HPSI 4H-SiC 30 Magnon Q #2". On that sample we investigated magnetic ellipses, sized 8 micrometer x 2 micrometer, made of Permalloy, that lie on top of a silicon carbide substrate. The measured data for all measurements (including ALL parameters) are included in the uploaded primary data subdirectories. The uploaded data is organized in folders according to the figures in the paper. Each folder contains the experimental data, together with the MuMax3 definition files, all the possible possible scripts used for evaluation and all figures included in the paper. This is the final version with the reviewers' corrections.

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Permalink: https://www.hzdr.de/publications/Publ-31921
Publ.-Id: 31921


CaTeNA – Climatic and Tectonic Natural Hazards in Central Asia Final virtual workshop September 24-25 2020

Barbosa, N.; Bloch, W.; Crosetto, S.; Haberland, C.; Jarihani, B.; Kakar, N.; Metzger, S.; Mohadjer, S.; Orunbaev, S.; Ratschbacher, L.; Schurr, B.; Strecker, M.; Wang, X.

CaTeNA – Climatic and Tectonic Natural Hazards in Central Asia – is an interdisciplinary, international project funded by the German Ministry of Education and Research to study natural hazards in Central Asia. Central Asia is one of the most tectonically active regions of the world and is influenced by both the west wind zone and monsoon. CaTeNA is examining the two most serious natural hazards arising from these conditions: Earthquakes and mass movements. The project goal is to better understand the underlying processes and triggering factors and to better estimate the resulting risks. For this purpose, CaTeNA localises tectonic faults and determines deformation rates and their changes. Focus is put on two of the most active fault systems, the Main Pamir Thrust and the Darvaz Fault crossing Tajikistan and Kyrgyzstan. We try to estimate recurrence intervals of large earthquakes and to understand their relationship to mass movements using paleo-seismology, geomorphology and remote sensing. The current deformation field is characterised and quantified using the methods of space geodesy and seismology. The results will be incorporated into the openly accessible Central Asian Tectonic Database developed within the project, making it accessible to the public, stakeholders and decision-makers. They form the basis for a more accurate estimation of the risk for earthquakes and landslides. Another important project goal is the development and implementation of a dynamic risk assessment for landslides, including high-resolution, model-based precipitation and snowmelt maps. This allows for improved estimation of the effects of geological hazards on inhabited areas and traffic infrastructure. Direct and efficient risk communication is achieved through interactive visualisation based on a dynamic multilingual web GIS platform. This is an essential step on the path to an early-warning system that takes into account the most important triggering factors. This data repository provides pdf files and recorded videos of talks presented during the final online workshop of the project.

Keywords: climatic natural hazard; tectonic natural hazard; coupling mechanism; central asia

  • Open Access Logo Lecture (others) (Online presentation)
    CaTeNA – Climatic and Tectonic Natural Hazards in Central Asia Final virtual workshop, 24.-25.09.2020, Potsdam, Germany
    DOI: 10.2312/gfz.catena.2020

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Permalink: https://www.hzdr.de/publications/Publ-31920
Publ.-Id: 31920


Window-based morphometric indices as predictive variables for landslide susceptibility models

Barbosa, N.; Andreani, L.; Gloaguen, R.; Ratschbacher, L.

Identification of areas prone to landslides is essential to mitigate associated risks. This is usually achieved using landslide susceptibility models, which estimate landslide likelihood given local terrain conditions and the location of known past events. Detailed databases covering different conditioning factors are paramount to produce reliable susceptibility maps. However, thematic data from developing countries are scarce. As a result, susceptibility models often rely on morphometric parameters derived from widely-available digital elevation models. In most cases, simple parameters such as slope, aspect, and curvature, computed using a moving window of 3{$\times$}3 pixels, are used. Recently, the use of window-based morphometric indices as an additional input has increased. These rely on a user-defined observation window size. In this contribution, we examine the influence of observation window size when using window-based morphometric indices as core predictive variables for landslide susceptibility assessment. We computed a variety of models that include morphometric indices calculated with different window sizes, and compared the predictive capabilities and reliability of the resulting predictions. All models are based on the random forest algorithm. The results improved significantly when each window-based morphometric index was calculated with a different and meaningful observation window. The sensitivity analysis highlights both the highly-informative observation windows and the impact of their selection on the model performance. We also stress the importance of evaluating landslide susceptibility results using different adapted metrics for predictive performance and reliability.

Keywords: landslide susceptibility model; morphometric indices; observation window; random forest; Tajik-Tian Shan

Permalink: https://www.hzdr.de/publications/Publ-31918
Publ.-Id: 31918


Improving landslide susceptibility models using morphometric indices: Influence of the observation window in the reliability of the results.

Barbosa Mejia, L. N.; Andreani, L.; Gloaguen, R.

Estimation of landslide susceptibility in mountainous areas is a prerequisite for risk assessment and contingency planning. The susceptibility to landslide is modelled based on thematic layers of information such as geomorphology, hydrology, or geology, where detailed characteristics of the area are depicted. The growing use of machine learning techniques to identify complex relationships among a high number of variables decreased the time required to distinguish areas prone to landslides and increased the reliability of the results. However, numerous countries lack detailed thematic databases to feed in the models. As a consequence, susceptibility assessment often relies heavily on geomorphic parameters derived from Digital Elevation Models. Simple parameters such as slope, aspect and curvature, calculated under a moving window of 3x3-pixels are mostly used. Furthermore, advanced morphometric indices such as topographic position index or surface roughness are increasingly used as additional input parameters. These indices are computed under a bigger window of observation usually defined by the researcher and the goal of the study. While these indices proved to be useful in capturing the overall morphology of an entire slope profile or regional processes, little is known on how the selection of the moving window size is relevant and affects the output landslide susceptibility model.

In order to address this question, we analysed how the predicting capabilities and reliability of landslide susceptibility models were impacted by the morphometric indices and their window of observation. For this purpose, we estimate the landslide susceptibility of an area located in Tajikistan (SW Tien Shan) using a Random Forest algorithm and different input datasets. Predicting factors include commonly used 3x3-pixel morphometrics, environmental, geological and climatic variables as well as advanced morphometric indices to be tested (surface roughness, local relief, topographic position index, elevation relief ratio and surface index). Two approaches were selected to address the moving window size. First, we chose a common window of observation for all the morphometric indices based on the study area valley’s characteristics. Second, we defined an optimal moving window(s) for each morphometric index based on the importance ranking of models that include moving windows from a range of 300 to 15000 m for each index. A total of 20 models were iteratively created, started by including all the moving windows from all the indices. Predicting capabilities were evaluated by the receiver operator curve (ROC) and Precision-Recall (PR). Additionally, a measure of reliability is proposed using the standard deviation of 50 iterations. The selection of different moving windows using the feature importance resulted in better predicting capabilities models than assigning an optimal for all. On the other hand, using a single different moving window per morphometric index (eg. most important ranked by random forest) decreases the evaluating metrics (a drop of PR from 0.88 to 0.85). Landslide susceptibility models can thus be improved by selecting a variety of meaningful (physically and methodological) windows of observation for each morphometric index. A 3x3-pixel moving window is not recommended because it is too small to capture the morphometric signature of landslides.

Keywords: Landslide susceptibility; morphometry; machine learning; random forest

Permalink: https://www.hzdr.de/publications/Publ-31917
Publ.-Id: 31917


Impact of laser polarization on q-exponential photon tails in nonlinear Compton scattering

Kämpfer, B.; Titov, A.

Non-linear Compton scattering of ultra-relativistic electrons traversing high-intensity laser pulses generates also hard photons. These photon high-energy tails are considered for parameters in reach at the forthcoming experiments LUXE and E-320. We consider the invariant differential cross sections dσ/du between the IR and UV regions and analyze the impact of the laser polarization and find q-deformed exponential shapes. (The variable u is the light-cone momentum-transfer from initial electron to final photon.) Optical laser pulses of various durations are compared with the monochromatic laser beam model which uncovers the laser intensity parameter in the range ξ=1⋯10. Some supplementary information is provided for the azimuthal final-electron/photon distributions and the photon energy-differential cross sections.

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Permalink: https://www.hzdr.de/publications/Publ-31915
Publ.-Id: 31915


Improved accuracy in high-frequency AC transport measurements in pulsed high magnetic fields

Mitamura, Y.; Watanuki, R.; Kampert, W. A. G.; Förster, T.; Matsuo, A.; Onimaru, T.; Onozaki, N.; Amou, Y.; Wakiya, K.; Matsumoto, K. T.

We show theoretically and experimentally that accurate transport measurements are possible even within the short time provided by pulsed magnetic fields. For this purpose, a new method has been devised, which removes the noise component of a specific frequency from the Signal by taking a linear combination of the results of numerical phase detection using multiple integer periods. We also established a method to unambiguously determine the phase rotation angle in AC transport measurements using a frequency range of tens of kilohertz. We revealed that the dominant noise in low-frequency transport measurements in pulsed magnetic fields is the electromagnetic induction caused by mechanical vibrations of wire loops in inhomogeneous magnetic fields. These results strongly suggest that accurate transport measurements in short-pulsed magnets are possible when mechanical vibrations are well suppressed.

Permalink: https://www.hzdr.de/publications/Publ-31914
Publ.-Id: 31914


How Hyperspectral Image Unmixing and Denoising Can Boost Each Other

Rasti, B.; Koirala, B.; Scheunders, P.; Ghamisi, P.

Hyperspectral linear unmixing and denoising are highly related hyperspectral image (HSI) analysis tasks. In particular, with the assumption of Gaussian noise, the linear model assumed for the HSI in the case of low-rank denoising is often the same as the one used in HSI unmixing. However, the optimization criterion and the assumptions on the constraints are different. Additionally, noise reduction as a preprocessing step in hyperspectral data analysis is often ignored. The main goal of this paper is to study experimentally the influence of noise on the process of hyperspectral unmixing by: (1) investigating the effect of noise reduction as a preprocessing step on the performance of hyperspectral unmixing; (2) studying the relation between noise and different endmember selection strategies; (3) investigating the performance of HSI unmixing as an HSI denoiser; (4) comparing the denoising performance of spectral unmixing, state-of-the-art HSI denoising techniques, and the combination of both. All experiments are performed on simulated and real datasets.

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Permalink: https://www.hzdr.de/publications/Publ-31912
Publ.-Id: 31912


Multicaloric effects in metamagnetic Heusler Ni-Mn-In under uniaxial stress and magnetic field

Gràcia-Condal, A.; Gottschall, T.; Pfeuffer, L.; Gutfleisch, O.; Planes, A.; Manosa, L.

The world’s growing hunger for artificial cold, on the one hand, and the ever more stringent climate targets, on the other, pose an enormous challenge to mankind. Novel, efficient, and environmentally friendly refrigeration technologies based on solid-state refrigerants can offer a way out of the problems arising from climate-damaging substances used in conventional vapor-compressors. Multicaloric materials stand out because of their large temperature changes, which can be induced by the application of different external stimuli such as a magnetic, electric, or a mechanical field. Despite the high potential for applications and the interesting physics of this group of materials, few studies focus on their investigation by direct methods. In this paper, we report on the advanced characterization of all relevant physical quantities that determine the multicaloric effect of a Ni-Mn-In Heusler compound. We have used a purpose-designed calorimeter to determine the isothermal entropy and adiabatic temperature changes resulting from the combined action of magnetic field and uniaxial stress on this metamagnetic shape-memory alloy. From these results, we can conclude that the multicaloric response of this alloy by appropriate changes of uniaxial stress and magnetic field largely outperforms the caloric response of the alloy when subjected to only a single stimulus. We anticipate that our findings can be applied to other multicaloric materials, thus inspiring the development of refrigeration devices based on the multicaloric effect

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Permalink: https://www.hzdr.de/publications/Publ-31911
Publ.-Id: 31911


Field-Modulated Anomalous Hall Conductivity and Planar Hall Effect in Co3Sn2S2 Nanoflakes

Yang, S.-Y.; Noky, J.; Gayles, J.; Dejene, F. K.; Sun, Y.; Doerr, M.; Scurschii, I.; Felser, C.; Nawaz Ali, M.; Liu, E.; Parkin, S. S. P.

Time-reversal-symmetry-breaking Weyl semimetals (WSMs) have attracted great attention recently because of the interplay between intrinsic magnetism and topologically nontrivial electrons. Here, we present anomalous Hall and planar Hall effect studies on Co3Sn2S2 nanoflakes, a magnetic WSM hosting stacked Kagome lattice. The reduced thickness modifies the magnetic properties of the nanoflake, resulting in a 15-time larger coercive field compared with the bulk, and correspondingly modifies the transport properties. A 22% enhancement of the intrinsic anomalous Hall conductivity (AHC), as compared to bulk material, was observed. A magnetic field-modulated AHC, which may be related to the changing Weyl point separation with magnetic field, was also found. Furthermore, we showed that the PHE in a hard magnetic WSM is a complex interplay between ferromagnetism, orbital magnetoresistance, and chiral anomaly. Our findings pave the way for a further understanding of exotic transport features in the burgeoning field of magnetic topological phases.

Permalink: https://www.hzdr.de/publications/Publ-31910
Publ.-Id: 31910


HIF2alpha-associated pseudohypoxia promotes radioresistance in pheochromocytoma: insights from 3D models

Seifert, V.; Richter, S.; Bechmann, N.; Bachmann, M.; Ziegler, C. G.; Pietzsch, J.; Ullrich, M.

Pheochromocytomas and paragangliomas (PCCs/PGLs) are rare neuroendocrine tumors arising from chromaffin tissue located in the adrenal or in ganglia of the sympathetic or parasympathetic nervous system. Treatment of non-resectable or metastatic PCCs/PGLs is still limited to palliative measures, including somatostatin type 2 receptor radionuclide therapy with [177Lu]Lu-DOTA-TATE as one of the most effective approaches to date. Nevertheless, metabolic and molecular determinants of radiation response in PCCs/PGLs have not yet been characterized. This study investigates the effects of hypoxia-inducible factor 2 alpha (HIF2α) on the susceptibility of PCCs/PGLs to radiation treatments using spheroids grown from genetically engineered mouse pheochromocytoma (MPC) cells. Expression of Hif2α was associated with significantly increased resistance of MPC spheroids to external X-ray irradiation and exposure to beta particle-emitting [177Lu]LuCl3 compared to Hif2α-deficient controls. Exposure to [177Lu]LuCl3 provided increased long-term control of MPC spheroids compared to single-dose external X-ray irradiation. This study provides first experimental evidence that HIF2α-associated pseudohypoxia contributes to a radioresistant phenotype of PCCs/PGLs. Furthermore, external irradiation and [177Lu]LuCl3 exposure of MPC spheroids provide surrogate models for radiation treatments to further investigate metabolic and molecular determinants of radiation responses in PCCs/PGLs and to evaluate effects of neo-adjuvant, in particular, radiosensitizing treatments in combination with targeted radionuclide therapies.

Keywords: paraganglioma; radionuclide therapy; lutetium-177; spheroid control dose; SCD50; spheroid re-growth; irradiation; X-ray; radioresistance

Permalink: https://www.hzdr.de/publications/Publ-31909
Publ.-Id: 31909


Nanometer-Thick Bismuth Nanocrystal Films for Sensoric Applications

Pilidi, A.; Tzanis, A.; Helm, T.; Arfanis, M.; Falaras, P.; Speliotis, T.

The present article is concerned with investigations of the structural, surface morphological, and magnetotransport properties of DC magnetron-sputtered nanometer-thick Bi nanocrystal films on Si(111) substrates. Crystal structure and surface morphology were studied with X-ray diffraction, Raman spectroscopy, field-emission scanning electron microscopy, and atomic force microscopy. For the samples deposited at the melting point of Bi, 271 °C, equilibrium crystals formed and according to Wulff theorem acquire a specific shape determined by the surface tension. These crystals were investigated for different film thicknesses and deposition temperatures varying from 25 to 300 °C. Furthermore, magnetotransport characterization was carried out in steady and pulsed magnetic fields of up to 9 and 70 T, respectively. At low temperatures, clear weak antilocalization behavior is observed, attributed to 2D conduction channels. A nonlinear Hall resistance is also confirmed, ascribed to the coexistence of two types of carriers (p and n). This study contributes to the elucidation of the transport properties of the Bi thin films and opens new perspectives for their exploitation in modern applications such as sensorics.

Permalink: https://www.hzdr.de/publications/Publ-31908
Publ.-Id: 31908


Allianz Initiative: Positionspapier Digitale Dienste für die Wissenschaft – wohin geht die Reise?

Konrad, U.; Förstner, K.; Reetz, J.; Wannemacher, K.; Kett, J.; Mannseicher, F.

Aufgrund des informationstechnologischen Fortschritts, der immer stärkeren, domänenübergreifenden Vernetzung in Wissenschaft und Forschung sowie der Notwendigkeit, gemeinsam Dienste und Ressourcen zu nutzen, werden von den Akteuren in Forschung und Wissenschaft zunehmend verteilte digitale Dienste verwendet. Der Fokus dieser Handreichung liegt auf den wissenschaftlichen Informationsdiensten, zu denen man u. a. Werkzeuge für kollaboratives Arbeiten, für die Aufbereitung und Analyse von Daten sowie Dienste zum wissenschaftlichen Publizieren, aber auch Dienste für die Entwicklung von Forschungssoftware zählen kann. Dabei zielen die Fragen nach der Art der geforderten bzw. wirklich verwendeten Diensten, der Vor- und Nachteile der gegenwärtigen Nutzung sowie der eigenverantwortlichen Bereitstellung dieser Dienste unter dem Aspekt der (finanziellen) Ressourcen-
Effizienz.

Keywords: Research Software; Open Science; Open Source; Digital Transformation; Information Technology

Permalink: https://www.hzdr.de/publications/Publ-31907
Publ.-Id: 31907


Feature Extraction for Hyperspectral Imagery: The Evolution From Shallow to Deep: Overview and Toolbox

Rasti, B.; Hong, D.; Hang, R.; Ghamisi, P.; Kang, X.; Chanussot, J.; Benediktsson, J. A.

Hyperspectral images (HSIs) provide detailed spectral information through hundreds of (narrow) spectral channels (also known as dimensionality or bands), which can be used to accurately classify diverse materials of interest. The increased dimensionality of such data makes it possible to significantly improve data information content but provides a challenge to conventional techniques (the so-called curse of dimensionality) for accurate analysis of HSIs. Feature extraction (FE), a vibrant field of research in the hyperspectral community, evolved through decades of research to address this issue and extract informative features suitable for data representation and classification. The advances in FE were inspired by two fields of research—the popularization of image and signal processing along with machine (deep) learning—leading to two types of FE approaches: the shallow and deep techniques. This article outlines the advances in these approaches for HSI by providing a technical overview of state-of-the-art techniques, offering useful entry points for researchers at different levels (including students, researchers, and senior researchers) willing to explore novel investigations on this challenging topic. In more detail, this article provides a bird’s eye view of shallow [both supervised FE (SFE) and unsupervised FE (UFE)] and deep FE approaches, with a specific focus on hyperspectral FE and its application to HSI classification. Additionally, this article compares 15 advanced techniques with an emphasis on their methodological foundations and classification accuracies. Furthermore, to push this vibrant field of research forward, an impressive amount of code and libraries are shared on GitHub, which can be found in [131].

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Permalink: https://www.hzdr.de/publications/Publ-31906
Publ.-Id: 31906


Oscillatory thermal-inertial flows in liquid metal rotating convection

Vogt, T.; Horn, S.; Aurnou, J.

We present the first detailed thermal and velocity field characterization of convection in a rotating cylindrical tank of liquid gallium, which has thermophysical properties similar to those of planetary core fluids. Our laboratory experiments, and a closely associated direct numerical simulation, are all carried out in the regime prior to the onset of steady convective modes. This allows us to study the oscillatory convective modes, sidewall modes and broadband turbulent flow that develop in liquid metals before the advent of steady columnar modes. Our thermo-velocimetric measurements show that strongly inertial, thermal wind flows develop, with velocities reaching those of comparable non-rotating cases. Oscillatory bulk convection and wall modes coexist across a wide range of our experiments, along with strong zonal flows that peak in the Stewartson layer, but that extend deep into the fluid bulk in the higher supercriticality cases. The flows contain significant time-mean helicity that is anti-symmetric across the midplane, demonstrating that oscillatory liquid metal convection contains the kinematic components to sustain system-scale dynamo generation.

Permalink: https://www.hzdr.de/publications/Publ-31905
Publ.-Id: 31905


Data for: "Multi Optical Sensor Fusion for Mineral Mapping of Core Samples"

Rasti, B.; Ghamisi, P.; Seidel, P.; Lorenz, S.; Gloaguen, R.

Geological objects are characterized by a high complexity inherent to a strong compositional variability at all scales and usually unclear class boundaries. Therefore, dedicated processing schemes are required for the analysis of such data for mineral mapping. On the other hand, the variety of optical sensing technology reveals different data attributes and therefore multi-sensor approaches are adapted to solve such complicated mapping problems. In this paper, we devise an adapted multi-optical sensor fusion (MOSFus) workflow which takes the geological characteristics into account. The proposed processing chain exhaustively covers all relevant stages, including data acquisition, preprocessing, feature fusion, and mineral mapping. The concept includes i) a spatial feature extraction based on morphological profiles on RGB data with high spatial resolution, ii) a specific noise reduction applied on the hyperspectral data that assumes mixed sparse and Gaussian contamination and iii) a subsequent dimensionality reduction using a sparse and smooth low rank analysis. The feature extraction approach allows to fuse heterogeneous data at variable resolutions, scales, and spectral ranges as well as improve classification substantially. The last step of the approach, an SVM classifier, is robust to unbalanced and sparse training sets and is particularly efficient with complex imaging data. We evaluate the performance of the procedure with two different multi-optical sensor datasets. The results demonstrate the superiority of this dedicated approach over common strategies.

Keywords: Multi-sensor data; optical sensor; hyperspectral; hyperspectral mixed sparse and Gaussian noise reduction (HyMiNoR); spectral imaging; data fusion; feature extraction; dimensionality reduction; support vector machine (SVM); sparse and smooth low-rank analysis (SSLRA); orthogonal total variation component analysis (OTVCA); mineral exploration

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Permalink: https://www.hzdr.de/publications/Publ-31904
Publ.-Id: 31904


Flow Control Based on Feature Extraction in Continuous Casting Process

Abouelazayem, S.; Glavinic, I.; Wondrak, T.; Hlava, J.

The flow structure in the mold of a continuous steel caster has a significant impact on the quality of the final product. Conventional sensors used in industry are limited to measuring single variables such as the mold level. These measurements give very indirect information about the flow structure. For this reason, designing control loops to optimize the flow is a huge challenge. A solution for this is to apply non-invasive sensors such as tomographic sensors that are able to visualize the flow structure in the opaque liquid metal and obtain information about the flow structure in the mold. In this paper, ultrasound Doppler velocimetry (UDV) is used to obtain key features of the flow. The preprocessing of the UDV data and feature extraction techniques are described in detail. The extracted flow features are used as the basis for real time feedback control. The model predictive control (MPC) technique is applied, and the results show that the controller is able to achieve optimum flow structures in the mold. The two main actuators that are used by the controller are the electromagnetic brake and the stopper rod. The experiments included in this study were obtained from a laboratory model of a continuous caster located at the Helmholtz-Zentrum Dresden Rossendorf (HZDR).

Keywords: industrial control; industrial process tomography; model predictive control; ultrasound doppler velocimetry

Permalink: https://www.hzdr.de/publications/Publ-31903
Publ.-Id: 31903


A UV laser test facility for precise measurement of gas parameters in gaseous detectors

Fan, X.; Naumann, L.; Siebold, M.; Stach, D.; Kämpfer, B.

This work is devoted to the development of a UV laser test facility for calibration of gaseous detectors. We applied multiple methods to achieve a micrometer scale accuracy for the laser test facility and provide dedicated investigations for laser ionization in the gaseous detector. With the well-controlled laser ionization and remote DAQ system, we can operate the calibration of gaseous detectors and precise measurement of gas parameters at the micrometer scale related to the detector’s field geometry.

Keywords: UV Laser

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Permalink: https://www.hzdr.de/publications/Publ-31902
Publ.-Id: 31902


Geometrically driven chiral effects in curvilinear antiferromagnetic spin chains

Pylypovskyi, O.; Kononenko, D.; Yershov, K.; Roessler, U.; Tomilo, A.; Faßbender, J.; van den Brink, J.; Makarov, D.; Sheka, D.

Antiferromagnets are technologically promising materials for spintronic and spinorbirtonic devices [1]. An efficient manipulation of antiferromagnetic textures requires the presence of the Dzyaloshinskii-Moriya interaction (DMI), which is present in crystals of special symmetry, and thus limits the number of available materials. In contrast to antiferromagnets, it is already established that in ferromagnetic thin films and nanowires chiral responses can be tailored relying on curvilinear geometries [2].

Here, we explore curvature effects in curvilinear antiferromagnets [3]. We demonstrate theoretically that intrinsically achiral curvilinear antiferromagnetic spin chains behave as a biaxial chiral helimagnet with a curvature-tunable anisotropy and DMI. In contrast to ferromagnetic spin chains, this system possesses the hard-axis anisotropy stemming from the dipolar interaction, which allows to observe the effects of geometry even in chains with small curvature and torsion. The geometry-driven easy axis anisotropy determines the homogeneous antiferromagnetic state at low curvatures and the gap for spin waves. The geometry-driven DMI determines the helimagnetic phase transition and leads to the appearance of the region with the negative group velocity at the dispersion curve.

[1] V. Baltz et al., Rev. Mod. Phys. 90, 015005 (2018)
[2] R. Streubel et al., J. Phys. D.: Appl. Phys. 49, 363001 (2016)
[3] O. V. Pylypovskyi, D. Y. Kononenko et al., Nano Lett. 20, 8157 (2020)

  • Contribution to proceedings
    Magnetism at the Nanoscale: Imaging ‐ Fabrication – Physics, 06.-08.01.2021, Virtual Conference, Virtual Conference

Permalink: https://www.hzdr.de/publications/Publ-31901
Publ.-Id: 31901


Parallel computing of elastic magnetic systems at the nanoscale

Tomilo, A.; Pylypovskyi, O.; Yershov, K.; Sheka, D.

Intensive research in the area of nanoscaled physics opens new possibilities for the construction and fabrication of nanoscale devices. A numerical experiment is a powerful tool to analyze complex systems and flexibly check analytical predictions in addition to experimental validation. Therefore usage of parallel
calculation is required to decrease the time of simulation.

  • Contribution to proceedings
    Sixth International Conference on High Performance Computing (HPC-UA 2020), 06.-07.11.2020, Virtual Conference, Virtual Conference

Permalink: https://www.hzdr.de/publications/Publ-31900
Publ.-Id: 31900


Stabilization of Skyrmion States by a Gradient of Curvature in Ferromagnetic Shells

Pylypovskyi, O.; Makarov, D.; Kravchuk, V.; Saxena, A.; Sheka, D.

Skyrmions represent a class of chiral magnetic textures with unique properties relevant for spintronic and spin-orbitronic applications [1]. Geometrical curvature can be used as an efficient mean to tailor chiral and anisotropic responses of thin ferromagnetic shells [2-4]. This was recently confirmed by quantifying the strength of the Dzyaloshinskii-Moriya interaction (DMI) in curved nanostripes [5]. Furthermore, there are numerous predictions of the stabilization of curvature-driven of small-radius skyrmions in spherical shells [6] and an appearance of skyrmion lattices as the ground state in intrinsically chiral curvilinear thin films [7].

Here, we demonstrate a new pathway of stabilizing Neel skyrmion and skyrmionium states relying on the gradient of curvature using a magnetic thin film hosting a circular nanoindentation [8]. These skyrmion states can be formed in a material even without an intrinsic DMI. We propose a physical picture of this effect, which is related to the pinning of a chiral magnetic domain wall at the bend of a nanoindentation. Geometry of the film is described by two principal curvatures k1(r), describing film geometry in radial direction, and k2(r) inversely proportional to the distance from origin. In this respect, the spatial inhomogeneity of the curvature-induced DMI governing by k1(r) is responsible for the stabilization of the skyrmion state. The lateral dimensions of the stabilized chiral magnetic textures are varied in a broad range by engineering the size of the nanoindentation. We describe the stability condition of skyrmion states. Furthermore, on the fundamental side, we put forth a general analytical framework allowing us to map a complex problem of the description of a magnetic texture at a surface of revolution to a standard planar problem with modified constants of DMI and magnetic anisotropy. In this respect, our model predicts a new mechanism of pinning of magnetic domain walls in planar ferromagnetic films with intrinsic DMI on inhomogeneities of the DMI.

[1] A. Fert, N. Reyren, V. Cros, Nat. Rev. Mater., Vol. 2, 17031 (2017)
[2] R. Streubel, P. Fischer, F. Kronast et al., J. Phys. D: Appl. Phys. Vol. 49, 363001 (2016)
[3] O. Pylypovskyi, V. Kravchuk, D. Sheka et al., Phys. Rev. Lett. Vol. 114, 197204 (2015)
[4] Y. Gaididei, A. Goussev, V. Kravchuk et al., J. Phys. A: Mat. and Theor. Vol. 50, 385401 (2017)
[5] Volkov, Kakay, Kronast et al., Phys. Rev. Lett. Vol. 123, 077201 (2019)
[6] V. Kravchuk, U. K. Röβler, O. M. Volkov et al., Phys. Rev. B. 94, 144402 (2016)
[7] V. Kravchuk, D. Sheka, A. Kákay et al., Phys. Rev. Lett. Vol. 120, 067201 (2018)
[8] O. Pylypovskyi, D. Makarov, V. Kravchuk et al., Phys. Rev. Appl. Vol. 10, 064057 (2018)

  • Contribution to proceedings
    2020 Virtual MRS Fall Meeting, 28.11.-04.12.2020, Virtual Conference, Virtual Conference

Permalink: https://www.hzdr.de/publications/Publ-31899
Publ.-Id: 31899


Experimental observation of exchange-driven chiral effects in parabolic stripes

Volkov, O.

Broken magnetic symmetry is a key aspect in condensed matter physics and in particular in magnetism. It results in the appearance of chiral effects, e.g. topological Hall effect [1] and non-collinear magnetic textures including chiral domain walls and skyrmions [2,3]. These chiral structures are in the heart of novel concepts for magnonics [4], antiferromagnetic spintronics [5], spin-orbitronics [6] and oxitronics [7]. The main origin of the chiral symmetry breaking and thus for the magnetochiral effects in magnetic materials is associated to an antisymmetric exchange interaction, the intrinsic Dzaloshinskii-Moriya interaction (DMI). At present, tailoring of DMI is done rather conventionally by optimizing materials, either doping a bulk single crystal or adjusting interface properties of thin films and multilayers. A viable alternative to the conventional material screening approach can be the exploration of the interplay between geometry and topology. This interplay is of fundamental interest throughout many disciplines in condensed matter physics, including thin layers of superconductors [8] and superfluids [9], nematic liquid crystals [10], cell membranes [11], semiconductors [12]. In the emergent field of curvilinear magnetism chiral effects are ssociated to the geometrically broken inversion symmetries [13]. Those appear in curvilinear architectures of even conventional materials. There are numerous exciting theoretical predictions of exchange and magnetostatically-driven curvature effects, which do not rely on any specific modification of the
intrinsic magnetic properties, but allow to create non-collinear magnetic textures in a controlled manner by tailoring local curvatures and shapes [14,15]. Until now the predicted chiral effects due to curvatures remained a neat theoretical abstraction. Here, we demonstrate the very first experimental confirmation of the existence of the curvature-induced chiral interaction with exchange origin in a conventional soft ferromagnetic material [16]. It is experimentally explored the theoretical predictions, that the magnetisation reversal of flat parabolic stripes shows a two step process. At the first switching event, a domain wall pinned by the curvature induced exchange-driven DMI is expelled leading to a magnetisation state homogeneous along the parabola’s long axis. Measuring the depinning field enables to quantify the effective exchange-driven DMI interaction constant. The magnitude of the effect can be tuned by the parabola’s curvature. It is found that the strength of the exchange-induced DMI interaction for the experimentally realised geometries is remarkably strong, namely ≈ 0.4 mJ/m 2 , compared the surface induced DMI. The presented study legitimates the predictive power of full-scale micromagnetic simulations to design the properties of ferromagnets through their geometry, thus stabilising chiral textures.

[1] N. Nagaosa, et al., Nature Nanotech. 8, 899 (2013)
[2] U. K. Rößler, et al., Nature 442, 797 (2006)
[3] A. Fert, et al., Nature Rev. Mat. 2, 17031 (2017)
[4] A. V. Chumak, et al., Nature Physics 11, 453 (2015)
[5] T. Jungwirth, et al., Nature Nanotech. 11, 231 (2016)
[6] I. M. Miron, et al., Nature 476, 189 (2011)
[7] V. Garcia, et al., Nature 460, 81 (2009)
[8] J. Tempere, et al., Phys. Rev. B 79, 134516 (2009)
[9] H. Kuratsuji, Phys. Rev. E 85, 031150 (2012)
[10] T. Lopez-Leon, et al., Nature Physics 7, 391 (2011)
[11] H. T. McMahon, et al., Nature 438, 590 (2005)
[12] C. Ortix, Phys. Rev. B 91, 245412 (2015)
[13] Y. Gaididei, et al., Phys. Rev. Lett. 112, 257203 (2014)
[14] J. A. Otálora, et al., Phys. Rev. Lett. 117, 227203 (2016)
[15] V. P. Kravchuk, et al., Phys. Rev. Lett. 120, 067201 (2018)
[16] O. M. Volkov, et al., Phys. Rev. Lett. 123, 077201 (2019)

Keywords: Ferromagnetism; Curvilinear magnetism

  • Contribution to proceedings
    2020 MRS Virtual Spring/Fall Meeting & Exhibit, 27.11.-04.12.2020, Boston, Massachusetts, USA
    Proceedings of the 2020 MRS Virtual Spring/Fall Meeting & Exhibit

Permalink: https://www.hzdr.de/publications/Publ-31898
Publ.-Id: 31898


Domain Wall Tilt and Enhancement of the Walker Limit in Stripes with Dzyaloshinskii-Moriya Interaction and Perpendicular Anisotropy

Pylypovskyi, O.; Kravchuk, V.; Volkov, O.; Faßbender, J.; Sheka, D.; Makarov, D.

The efficiency of manipulation of domain walls and skyrmions in ferromagnetic racetracks with perpendicular anisotropy determines perspectives of development of data storage and logic devices relying on spintronic and spin-orbitronic concepts [1, 2]. The domain wall dynamics is dependent on its orientation with respect to the racetrack axis. In-plane fields [3], edge roughness [4] and current [5] result in the domain wall tilt in samples, possessing Dzyaloshinskii-Moriya interaction (DMI). Here, we show theoretically, that the tilt can appear in equilibrium and describe the domain wall dynamics under the action of external field. We consider a thin biaxial stripe with DMI of interfacial type [6]. The main easy axis of anisotropy is perpendicular to the plane, and the direction of the second easy axis lies in the stripe plane under the angle α to the stripe axis. While the shape anisotropy results in α = 0, a general case α ≠ 0 can appear under the influence of other effects, e.g crystalline structure [7]. While the second easy axis defines the preferable in-plane magnetization within the domain wall, the DMI forces the domain wall being perpendicular to the magnetization gradient. The competition between these two energy contributions and the domain wall tension results in the unidirectional tilt of the whole domain wall. If the DMI is weak enough, there is an additional metastable domain wall state, tilted into the opposite direction. The symmetry break is observed not only for static magnetization texture, but also in the domain wall dynamics under the action of external magnetic field. The domain wall reveals fast and slow motion regimes for the opposite signs of A. The maximum of the Walker field and Walker velicities is determined by the angle A of the second easy axis anisotropy and does not coincide with a shape-induced anisotropy direction A=0. The domain wall possesses the switch of the magnetization direction inside the domain wall in the slow motion regime, which results in the faster motion.

[1] K.-S. Ryu, L. Thomas, S.-H. Yang et al., Nat. Nanotech., Vol. 8, 527 (2013)
[2] O. Pylypovskyi, D. Sheka, V. Kravchuk et al., Sci. Rep. Vol. 6, 23316 (2016)
[3] C. Muratov, V. Slastikov, A. Kolesnikov et al., Phys. Rev. B. Vol. 96, 134417 (2017)
[4] E. Martinez, S. Emori, N. Perez et al. J. Appl. Phys. Vol. 115, 213909 (2014)
[5] O. Boulle, S. Rohart, L. Buda-Prejbeanu et al., Phys. Rev. Lett. Vol. 111, 217203 (2013)
[6] O. Pylypovskyi, V. Kravchuk, O. Volkov et al., J. Phys. D. (2020), DOI:10.1088/1361-6463/ab95bd
[7] M. Heide, G. Bihlmayer, S. Blügel, Pys. Rev. B, Vol. 78, p. 140403 (2008).

  • Contribution to proceedings
    MMM 2020 Virtual Conference, 02.-06.11.2020, Virtual Conference, Virtual Conference

Permalink: https://www.hzdr.de/publications/Publ-31897
Publ.-Id: 31897


Curvature-driven Chiral Effects in Nanomagnetism

Volkov, O.

The structural inversion symmetry plays an important role in low-dimensional nanomagnets, due to its strong influence on magnetic and electrical properties. It can lead to the appearance of chiral effects, such as the topological Hall effect [1], or to the formation of chiral noncollinear magnetic textures, as skyrmions [2] and chiral domain walls (DWs) [3]. These chiral structures can be the key components for realizing novel concepts for magnonics [4], antiferromagnetic spintronics [5], spin-orbitronics [6], and oxitronics [7]. So far, the main chiral symmetry breaking effect considered as being the origin for the presence of chiral noncollinear magnetic textures is the intrinsic Dzyaloshinskii-Moriya interaction (DMI) [8,9], which appears in certain magnetic crystals in which the unit cell lacks inversion symmetry, such as the gyrotropic magnetic crystals, or appear typically in ultrathin films or bilayers due to the inversion symmetry breaking on the film interface [3]. At present, tailoring of DMI is done by optimizing materials, either doping a bulk single crystal or adjusting interface properties of thin films and multilayers.

A viable alternative to the conventional material screening approach can be the exploration of the interplay between geometry and topology. This interplay is of fundamental interest throughout many disciplines in condensed matter physics, including thin layers of superconductors [10] and superfluids [11], nematic liquid crystals [12], cell membranes [13], semiconductors [14]. In the emergent field of curvilinear magnetism chiral effects are associated to the geometrically broken inversion symmetries [15]. Those appear in curvilinear architectures of even conventional materials. There are numerous exciting theoretical predictions of exchange- and magnetostatically-driven curvature effects, which do not rely on any specific modification of the intrinsic magnetic properties, but allow to create non-collinear magnetic textures in a controlled manner by tailoring local curvatures and shapes [16,17]. Until now the predicted chiral effects due to curvatures remained a neat theoretical abstraction.

Very recently, we provided the very first experimental confirmation of the existence of the curvature-induced chiral interaction with exchange origin in a conventional soft ferromagnetic material. It is experimentally explored the theoretical predictions, that the magnetisation reversal of flat parabolic stripes shows a two step process [18,19]. At the first switching event, a domain wall pinned by the curvature induced exchange-driven DMI is expelled leading to a magnetisation state homogeneous along the parabola's long axis. Measuring the depinning field enables to quantify the effective exchange-driven DMI interaction constant. The magnitude of the effect can be tuned by the parabola's curvature. It is found that the strength of the exchange-induced DMI interaction for the experimentally realised geometries is remarkably strong, namely ~0.4 mJ/m2, compared the surface induced DMI. The presented study legitimates the predictive power of full-scale micromagnetic simulations to design the properties of ferromagnets through their geometry, thus stabilising chiral textures. We explore these curvilinear magnetic thin films for the realization of novel artificial magnetoelectric materials based on curvilinear helimagnets embedded in piezoelectric matrix [20], to enable the geometrical tuning of the magnetochirality in curvilinear 1D architectures [21], tailoring of magnetic states in flat nanospirals [22] and as components of shapeable magnetoelectronics for interactive wearables [23].

[1] N. Nagaosa, et al., Nature Nanotech. 8, 899 (2013)
[2] U. K. Rößler, et al., Nature 442, 797 (2006)
[3] A. Fert, et al., Nature Rev. Mat. 2, 17031 (2017)
[4] A. V. Chumak, et al., Nature Physics 11, 453 (2015)
[5] T. Jungwirth, et al., Nature Nanotech. 11, 231 (2016)
[6] I. M. Miron, et al., Nature 476, 189 (2011)
[7] V. Garcia, et al., Nature 460, 81 (2009)
[8] I. Dzyaloshinsky, J. Phys. Chem. Solids 4, 241 (1958).
[9] T. Moriya, Phys. Rev. Lett. 4, 228 (1960).
[10] J. Tempere, et al., Phys. Rev. B 79, 134516 (2009)
[11] H. Kuratsuji, Phys. Rev. E 85, 031150 (2012)
[12] T. Lopez-Leon, et al., Nature Physics 7, 391 (2011)
[13] H. T. McMahon, et al., Nature 438, 590 (2005)
[14] C. Ortix, Phys. Rev. B 91, 245412 (2015)
[15] Y. Gaididei, et al., Phys. Rev. Lett. 112, 257203 (2014)
[16] J. A. Otálora, et al., Phys. Rev. Lett. 117, 227203 (2016)
[17] V. P. Kravchuk, et al., Phys. Rev. Lett. 120, 067201 (2018)
[18] O. Volkov et al., PRL 123, 077201 (2019).
[19] O. Volkov et al., PSS-RRL 13, 1800309 (2019).
[20] O. Volkov et al., J. Phys. D: Appl. Phys. 52, 345001 (2019).
[21] O. Volkov et al., Scientific Reports 8, 866 (2018).
[22] M. Nord, et al., Small 1904738 (2019).
[23] J. Ge, et al., Nature Comm. 10, 4405 (2019).

Keywords: Ferromagnetism; Curvilinear magnetism; Chiral effects

  • Invited lecture (Conferences) (Online presentation)
    MMM 2020 Virtual Conference, 02.-06.11.2020, Palm Beach, Florida, USA

Permalink: https://www.hzdr.de/publications/Publ-31896
Publ.-Id: 31896


Effects of Geometry on Curvilinear Spin Chains

Kononenko, D.; Pylypovskyi, O.; Yershov, K.; Roessler, U.; Tomilo, A.; Faßbender, J.; van den Brink, J.; Makarov, D.; Sheka, D.

Curvilinear magnetism is of great fundamental and practical interest whose rapid development is inspired by novel experimental technologies and wide potential applications [1]. A general approach for description of curvilinear ferromagnets [2] has been recently developed and used for thin wires and shells uncovering magnetochiral effects in statics and dynamics [1,3]. Besides intensive research of ferromagnetic materials, their antiferromagnetically ordered (AFM) counterparts are promising candidates for spintronics applications by their low sensitivity to external fields and ultra high eigenfrequencies [4]. Here, we present a general approach for description of AFM textures in curvilinear spin chains [5]. We show that the magnetic dipole-dipole interaction in these systems can be reduced to a hard-axis anisotropy along the chain. Lagrangian of the curvilinear AFM spin chain in continuum limit corresponds to the biaxial chiral helimagnet. Helix geometry shows existence of two equilibrium magnetic states depending on values of curvature and torsion: (i) homogeneous state in the local reference frame, it is typical for helices with the curvature larger than torsion; and (ii) periodic state is quasi-homogeneous in the laboratory reference frame. For specific case of the AFM flat chain there is the only ground state, with the order parameter being oriented perpendicular to the chain plane. We show that in curvilinear system transverse and longitudinal magnon modes in the AFM helix and ring are coupled due to geometry-induced Dzyaloshinskii–Moriya interaction.

[1] R. Streubel, J. Lee, D. Makarov et al, J. Phys. D, 49, 363001, (2016); A. Fernández-Pacheco et al, Nat. Comm., Vol. 8, p. 15756 (2017).
[2] Y. Gaididei, V. P. Kravchuk, D. D. Sheka, Phys. Rev. Lett. 112, 257203 (2014); D. D. Sheka, V. P. Kravchuk, Y. Gaididei, J. Phys. A, Vol. 48, p. 125202 (2015).
[3] O. V. Pylypovskyi, D. D. Sheka, V. P. Kravchuk et al, Sci. Rep. Vol. 6, p. 23316 (2016); O. V. Pylypovskyi, D. Makarov, V. P. Kravchuk et al, Phys. Rev. Applied, Vol. 10, p. 064057 (2018)
[4] V. Balz, A. Manchon, M. Tsoi et al, Rev. Mod. Phys., Vol. 90, p. 015005 (2018)
[5] D. Y. Kononenko, O. V. Pylypovskyi, K. V. Yershov et al., arXiv:2005.05835 (2020)

  • Contribution to proceedings
    MMM 2020 Virtual Conference, 02.-06.11.2020, Virtual Conference, Virtual Conference

Permalink: https://www.hzdr.de/publications/Publ-31895
Publ.-Id: 31895


Magnetostatics-Induced Symmetry Breaking Effects in Curvilinear Shells

Sheka, D.; Pylypovskyi, O.; Landeros, P.; Kakay, A.; Makarov, D.

The behavior of any physical system is governed by the order parameter, determined by the geometry of the physical space of the object, namely their dimensionality and curvature. Usually, the effects of curvature are identified using local interactions only, e.g. local spin-orbit- or curvature-induced Rashba and Dzyaloshinskii-Moriya interactions in condensed matter [1]. Lack of the framework, involving both, local and non-local interactions impedes the description of the essentially micromagnetic textures like magnetic domains, skyrmion-bubbles and vortices. Here, we present a micromagnetic theory of curvilinear ferromagnetic shells [2]. New chiral effects, originating from the magnetostatic interaction, can appear in such systems. They manifest themselves even in statics and are essentially nonlocal. This is in contrast to conventional Dzyaloshinskii--Moriya interaction (material intrinsic or curvature-induced, stemming from the exchange). The physical origin is in a non-zero mean curvature of a shell and non-equivalence between the top and bottom surfaces of the shell. To describe the new effects, we split a conventional volume magnetostatic charge into two terms: (i) magnetostatic charge, governed by the tangent to the sample’s surface, and (ii) geometrical charge, given by the normal component of magnetization and the mean curvature. We classify the interplay between the symmetry of the shell, its local curvature and magnetic textures and apply the proposed formalism to analyze magnetic textures in corrugated shells with perpendicular anisotropy.

[1] R. Streubel, J. Lee, D. Makarov et al, J. Phys. D, 49, 363001, (2016);
[2] O. V. Pylypovskyi, D. D. Sheka, V. P. Kravchuk et al, Sci. Rep. Vol. 6, p. 23316 (2016); O. M. Volkov, D. D. Sheka, Y. Gaididei et al, Sci. Rep. Vol. 8, p. 866 (2018).
[3] D. D. Sheka, O. V. Pylypovskyi, P. Landeros et al., Comm. Phys. 3, 128 (2019), DOI:10.1038/s42005-020-0387-2

  • Contribution to proceedings
    MMM 2020 Virtual Conference, 02.-06.11.2020, Virtual Conference, Virtual Conference

Permalink: https://www.hzdr.de/publications/Publ-31894
Publ.-Id: 31894


From stripes to bubbles: Deterministic transformation of magnetic domain patterns in Co/Pt multilayers induced by laser helicity

Novakovic-Marinkovic, N.; Mawass, M.-A.; Volkov, O.; Makushko, P.; Dieter Engel, W.; Makarov, D.; Kronast, F.

The optical control of magnetism offers an attractive possibility to manipulate small magnetic domains for prospective memory devices on ultrashort time scales. Here, we report on the local deterministic transformation of the magnetic domain pattern from stripes to bubbles in out-of-plane magnetized Co/Pt multilayers controlled only by the helicity of ultrashort laser pulses. Relying on the experimentally determined average size of stripe domains and the magnetic layer thickness, we calculate the temperature and characteristic fields at which the stripe-bubble transformation occurs. Furthermore, we demonstrate that in the narrow range of the laser power, the helicity induces a drag on domain walls.

Keywords: Ferromagnetism; Magnetic domains; Magnetization switching; Ultrafast megnetic effects; Multilayer thin films

Permalink: https://www.hzdr.de/publications/Publ-31893
Publ.-Id: 31893


PET measured hypoxia and MRI parameters in re-irradiated head and neck squamous cell carcinomas: findings of a prospective pilot study

Rogasch, J.; Beck, M.; Stromberger, C.; Hofheinz, F.; Ghadjar, P.; Wust, W.; Budach, V.; Amthauer, H.; Tinhofer, I.; Furth, C.; Walter-Rittel, T.; Zschaeck, S.

Background: Tumor hypoxia measured by dedicated tracers like [18F]fluoromisonidazole (FMISO) is a well-established prognostic factor in head and neck squamous cell carcinomas (HNSCC) treated with definitive chemoradiation (CRT). However, prevalence and characteristics of positron emission tomography (PET) measured hypoxia in patients with relapse after previous irradiation is missing. Here we report imaging findings of a prospective pilot study in HNSCC patients treated with re-irradiation.

Methods: In 8 patients with recurrent HNSCC, diagnosed at a median of 18 months after initial radiotherapy/CRT, [18F]fluorodeoxyglucose (FDG)-PET/CT (n=8) and FMISO-PET/MRI (n=7) or FMISO-PET/CT (n=1) were performed. Static FMISO-PET was performed after 180 min. MRI sequences in PET/MRI included diffusion-weighted imaging with apparent diffusion coefficient (ADC) values and contrast enhanced T1w imaging (StarVIBE). Lesions (primary tumor recurrence, 4; cervical lymph node, 1; both, 3) were delineated on FDG-PET and FMISO-PET data using a background-adapted threshold-based method. SUVmax and SUVmean in FDG- and FMISO-PET were derived, as well as maximum tumor-to-muscle ratio (TMRmax) and hypoxic volume with 1.6-fold muscle SUVmean (HV1.6) in FMISO-PET. Intensity of lesional contrast enhancement was rated relative to contralateral normal tissue. Average ADC values were derived from a 2D region of interest in the tumor.

Results: In FMISO-PET, median TMRmax was 1.7 (range: 1.1-1.8). Median HV1.6 was 0.05 ml (range: 0-7.3 ml). Only in 2/8 patients, HV1.6 was ≥1.0 ml. In FDG-PET, median SUVmax was 9.3 (range: 5.0-20.1). On contrast enhanced imaging four lesions showed decreased and four lesions increased contrast enhancement compared to non-pathologic reference tissue. Median average ADC was 1,060 ×106 mm2/s (range: 840-1,400 ×106 mm2/s).

Conclusions: This pilot study implies that hypoxia detectable by FMISO-PET may not be as prevalent as expected among loco-regional recurrent HNSCC. ADC values were only mildly reduced, and contrast enhancement was variable. The results require confirmation in larger sample sizes.

Keywords: radiotherapy; head and neck squamous cell carcinoma; hypoxia; FMISO; FDG; PET

Permalink: https://www.hzdr.de/publications/Publ-31892
Publ.-Id: 31892


Depth distribution of irradiation-induced dislocation loops in an Fe-9Cr model alloy irradiated with Fe ions: The effect of ion energy

Vogel, K.; Chekhonin, P.; Kaden, C.; Hernández-Mayoral, M.; Akhmadaliev, S.; Bergner, F.

It is generally accepted that the microstructure of ion-irradiated Fe-based alloys does not only depend on the local level of displacement damage and the initial microstructure. Other factors such as the vicinity of a surface and the injected ions also play a role and may give rise to peculiar depth dependencies of the irradiated microstructure. Some investigators reported a band-like appearance indicating depth ranges of relatively uniform microstructure clearly distinguished from other ranges. Clarification is important for at least two purposes: first, to identify a depth range suitable for gaining meaningful information about the behaviour of materials exposed to neutron irradiation and, second, to correctly interpret results obtained by methods, such as nanoindentation, that integrate over extended depth ranges. A variation of the ion energy is expected to gain additional insight. In this work, two samples of Fe-9%Cr were irradiated at 300 °C with Fe2+ ions, one sample using 1 MeV ions and another sample using 5 MeV ions. Calculations using the binary collision code SRIM indicate displacement damage peaks at depths of 0.3 and 1.3 µm for ion energies of 1 and 5 MeV, respectively. The depth distribution of irradiation-induced dislocation loops was studied by cross-sectional scanning transmission electron microscopy (STEM). Loops visible in the STEM images were found to be arranged within two bands with the positions of these bands depending on the profiles of displacement damage and injected interstitials. The first and second band exhibit noticeably different number densities and mean sizes of the loops. For the 5 MeV irradiation, an extended range between the sample surface and the first band was observed, where decoration of pre¬existing line dislocations with loops is dominant. This microstructure resembles cases reported for neutron irradiation. For the 1 MeV irradiation, such a range does not exist. Estimates characterizing the loop size and number density in the distinct depth ranges are provided.

Keywords: Fe-9Cr; Ion irradiation; Scanning TEM; Dislocation loops

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Permalink: https://www.hzdr.de/publications/Publ-31891
Publ.-Id: 31891


Dataset for the publication "Depth distribution of irradiation-induced dislocation loops in an Fe-9Cr model alloy irradiated with Fe ions: The effect of ion energy"

Vogel, K.; Chekhonin, P.; Bergner, F.

The dataset covers the raw/processed data required to reproduce the findings derived in the publication "Depth distribution of irradiation-induced dislocation loops in an Fe-9Cr model alloy irradiated with Fe ions: The effect of ion energy" by K. Vogel, P. Chekhonin, C. Kaden, M. Hernández-Mayoral, S. Akhmadaliev and F. Bergner. The whole set of original figures included in the publication is included as TIFF files. Supplementary material is provided as follows:

  • G385_xMeV_loop_count.pptx: Powerpoint files related to the estimation of the loop concentrations for the 1 MeV and 5 MeV irradiations,
  • Image_FIB_Position_Final.pptx: Powerpoint file showing the way how the 5 MeV FIB lamella was taken,
  • Loop_size_xMeV_Slicey.xlsx: Excel files related to the sizing of loops utilized to derive the histograms of the loops sizes,
  • Thickness_Profile_CBED_5MeV.xlsx: Thickness measurement for 5 MeV using the method of CBED.

Keywords: Fe-9Cr; Ion irradiation; Cross-sectional scanning transmission electron microscopy (STEM)

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Permalink: https://www.hzdr.de/publications/Publ-31890
Publ.-Id: 31890


Data for: "MicroTCA.4 based low level RF for continuous wave mode operation at the ELBE accelerator"

Kuntzsch, M.; Steinbrück, R.; Zenker, K.

This data is used in the publication "MicroTCA.4 based low level RF for continuous wave mode operation at the ELBE accelerator". The README.md includes all the information about which data set was used for which figure. The paper only shows the raw  data and numbers deduced from the data. No post processing like cleaning was done.

Keywords: ELBE; ChimeraTK; MicroTCA.4; LLRF; OPC UA

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Permalink: https://www.hzdr.de/publications/Publ-31889
Publ.-Id: 31889


Metal processes and applications - an overview

Meskers, C. E. M.

As background to the other chapters a short overview of each metals’ physical properties, production process, applications and recycling is given. One way of approaching the elements is through their place in the periodic table of elements, which can be used to predict physical and chemical properties and behavior. Each group in the periodic table corresponds to a section in this chapter. Still how the metals relate to each other for a particular property is not directly apparent from the periodic table. They can be ranked based on density or melting point or strength which are important for structural applications. But metals are not only used for that. Some are used because of their ability to form alloys and improve alloy properties, to catalyze reactions or to conduct electricity or heat. The application also determines the purity of the metal. Whereas for ferroalloys a purity above 90% suffices, semiconductors such as silicon or germanium require over 9N purity. Extensive refining is necessary to achieve such purity. Another way to group the metals is by the method or equipment to produce and refine them.
This chapter is also suitable for a systematic approach. The linkages and similarities between the different metals become apparent, providing valuable insights for primary production (mining), recycling, residue treatment, technology development, alloy and product design, substitution, etc.
The metal wheel (figure2) is a key tool for this. It visualizes the interconnectedness between metals, which is particularly relevant for metallurgists in the context of metal refining and the circular economy. It applies to metals from primary resources, production rejects and end-of-life products, and residues generated within (metal) production and recycling processes. The metal wheel summarizes this chapter, and is also a guidance when designing products and assessing recycling possibilities of metal-containing products.

Keywords: metals; extractive metallurgy; processing; applications; recycling

  • Book chapter
    Engh, Thorvald Abel; Sigworth, Geoffrey K.; Kvithyld, Anne: Principles of Metal Refining and Recycling, UK: Oxford University Press, 2022, 9780198811923, 450-541

Permalink: https://www.hzdr.de/publications/Publ-31888
Publ.-Id: 31888


Ni-Co 2021 - the 5th international symposium on nickel and cobalt

Anderson, C.; Goodall, G.; Gostu, S.; Gregurek, D.; Lundstrom, M.; Meskers, C. E. M.; Nicol, S.; Peuraniemi, E.; Tesfaye, F.; Tripathy, P. K.; Wang, S.; Zhang, Y.

Proceedings of the international symposium on nickel and cobalt organised by The Minerals, Metals and Materials Society (TMS) and Metallurgy & Materials Society (MetSoc) of the Canadian Institute of Mining, Metallurgy and Petroleum (CIM)

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Permalink: https://www.hzdr.de/publications/Publ-31887
Publ.-Id: 31887


The effect of the particle parameters of morphology and wettability in ultrafine particle flotation and froth fractionation

Sygusch, J.; Rudolph, M.

Froth flotation is well-established and efficient in the selective separation of valuable particles from unwanted material with sizes ranging from 10 µm to 200 µm. However, when it comes to the separation of ultrafine particles (< 10 µm) there are still some challenges, or rather opportunities. This research is part of the German research foundation priority programme DFG-SPP 2045 “MehrDimPart” aiming at developing a method for the separation of ultrafine particles based on multiple particle properties. Amongst such properties are wettability, morphology (shape or roughness) and size with applications not only in mineral processing but in general chemical engineering.
In order to study the effect of particle morphology on ultrafine particle flotation, three differently shaped fractions are used for testing, e.g. spherical particles, elongated particles and irregularly shaped particle fragments. Said particles are analysed for their wettability, which is varied by esterification using alcohols with differing alkyl chain lengths, through contact angle measurements. The particle size and shape properties are assessed by a combination of scanning electron microscopy, laser diffraction and optical microscopy.
Flotation tests are carried out using a novel flotation device that was designed especially for the flotation of ultrafine particles, combining advantages from machine-type froth flotation and column flotation.
Besides introducing a new concept of ultrafine particle flotation and froth fractionation, the study is contributing to the common understanding of flotation and the impact of different complex particle properties.

Keywords: Ultrafine particles; Flotation; Surface modification; Esterification of glass; Hydrophobisation

  • Contribution to proceedings
    International Mineral Processing Congress 2020, 18.-22.10.2020, Cape Town, South Africa
    Proceedings of the International Mineral Processing Congress 2020

Permalink: https://www.hzdr.de/publications/Publ-31885
Publ.-Id: 31885


Numerical ferromagnetic resonance experiments in nano-sized elements

Kai, W.; Körber, L.; Stienen, S.; Lindner, J.; Farle, M.; Kákay, A.

This dataset contains the raw data for our paper "Numerical ferromagnetic resonance experiments in nano-sized elements" published in IEEE Magnetic Letters. It is organized in folders according to the figures in the paper. Each folder contains the experimental and numerical data, together with the MuMax3 definition files and possible scripts used for evaluation.

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Permalink: https://www.hzdr.de/publications/Publ-31884
Publ.-Id: 31884


High denticity oxinate-linearbackbone chelating ligand for diagnostic radiometal ions [111In]In3+ and [89Zr]Zr4+

Southcott, L.; Wang, X.; Wharton, L.; Yang, H.; Radchenko, V.; Kubeil, M.; Stephan, H.; Jaraquemada-Pelaez, M.; Orvig, C.

Advances in nuclear medicine depend on chelating ligands that form highly stable and kinetically inert complexes with relevant radiometal ions for use in diagnosis or therapy. A new potentially decadentate ligand, H5decaox, was synthesised to incorporate two 8-hydroxyquinoline moieties on either end of a diethylene triamine backbone decorated with three carboxylic acids, one at each N atom of the backbone. Metal complexation was assessed using nuclear magnetic resonance (NMR) spectroscopy and high-resolution massspectrometry (HR-MS) with In3+, Zr4+ and La3+. Solution thermodynamic studies provided the stepwise protonation constants and metal formation constants, indicating a high affinity for both In3+ and Zr4+ (pIn = 32.3 and pZr = 34.7), and density functional theory (DFT) calculations provided insight to the coordination environments with either metal ion.Concentration dependent radiolabeling experiments with [111In]InCl3 and [89Zr]ZrCl4 showed promise as quantitative radiolabeling (>95%) occurred at micromolar concentrations, under mild, near-physiological conditions of pH 7 and room temperature for 30 minutes. Serum stability of both radiometal complexes was investigated and the
[111In]In(decaox) complex remained 91% intact after 24 hours while the [89Zr]Zr(decaox) complex was 86% intact over the same time, comparable to other chelating ligands previously assessed with the same methods. The high radiolabeling yields, limited serum protein transchelation and structural insight of [89Zr]Zr(decaox) complex suggests a promising fit between the oxinate-containing ligand and the Zr4+ ion, setting the stage for further investigations with a functionalised version of the chelator for its potential in PET imaging.

Permalink: https://www.hzdr.de/publications/Publ-31883
Publ.-Id: 31883


A metabolic switch regulates the transition between growth and diapause in C. elegans

Penkov, S.; Raghuraman, B. K.; Erkut, C.; Oertel, J.; Galli, R.; Ackerman, E. J. M.; Vorkel, D.; Verbavatz, J. M.; Koch, E.; Fahmy, K.; Shevchenko, A.; Kurzchalia, T. V.

Background Metabolic activity alternates between high and low states during different stages of an organism's life cycle. During the transition from growth to quiescence, a major metabolic shift often occurs from oxidative phosphorylation to glycolysis and gluconeogenesis. We use the entry of Caenorhabditis elegans into the dauer larval stage, a developmentally arrested stage formed in response to harsh environmental conditions, as a model to study the global metabolic changes and underlying molecular mechanisms associated with growth to quiescence transition. Results Here, we show that the metabolic switch involves the concerted activity of several regulatory pathways. Whereas the steroid hormone receptor DAF-12 controls dauer morphogenesis, the insulin pathway maintains low energy expenditure through DAF-16/FoxO, which also requires AAK-2/AMPK alpha. DAF-12 and AAK-2 separately promote a shift in the molar ratios between competing enzymes at two key branch points within the central carbon metabolic pathway diverting carbon atoms from the TCA cycle and directing them to gluconeogenesis. When both AAK-2 and DAF-12 are suppressed, the TCA cycle is active and the developmental arrest is bypassed. Conclusions The metabolic status of each developmental stage is defined by stoichiometric ratios within the constellation of metabolic enzymes driving metabolic flux and controls the transition between growth and quiescence.

Keywords: microcalorimetry

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Permalink: https://www.hzdr.de/publications/Publ-31882
Publ.-Id: 31882


Laser-plasma proton acceleration with a combined gas-foil target

Levy, D.; Bernert, C.; Rehwald, M.; Andriyash, I. A.; Assenbaum, S.; Kluge, T.; Kroupp, E.; Obst-Huebl, L.; Pausch, R.; Schulze-Makuch, A.; Zeil, K.; Schramm, U.; Malka, V.

Laser-plasma proton acceleration was investigated in the target normal sheath acceleration regime with a target composed of a gas layer and a thin foil. The laser's shape, duration, energy and frequency are modified as it propagates in the gas, altering the laser-solid interaction leading to proton acceleration. The modified properties of the laser were assessed by both numerical simulations and by measurements. The 3D particle-in-cell simulations have shown that a nearly seven-fold increase in peak intensity at the foil plane is possible. In the experiment, maximum proton energies showed high dependence on the energy transmission of the laser through the gas and a lesser dependence on the size and shape of the pulse. At high gas densities, where high intensity was expected, laser energy depletion and pulse distortion suppressed proton energies. At low densities, with the laser focused far behind the foil, self-focusing was observed and the gas showed a positive effect on proton energies. The promising results of this first exploration motivate further study of the target.

Keywords: laser plasma; TNSA; self focusing; PIConGPU

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Permalink: https://www.hzdr.de/publications/Publ-31881
Publ.-Id: 31881


Status Report of GaN photocathode

Schaber, J.; Xiang, R.; Teichert, J.; Arnold, A.; Ryzhov, A.; Murcek, P.; Zwartek, P.; Ma, S.

Particle accelerators are always looking for new materials which can promise high quantum efficiency, a long lifetime and good vacuum stability, fast response time and low thermal emittance. Semiconductors such as GaN as novel materials for photocathodes are showing an enormous potential.
Activated with a thin alkali metal layer, like caesium (Cs), p-GaN has the ability to lower the surface work function to produce a negative electron affinity (NEA). Requirements on the instrumentation is to avoid any oxygen contamination before, during and after the activation with caesium, so the activation process takes place in a UHV chamber.
At the beginning of 2020 the first activation of GaN on sapphire substrate was successfully done and meanwhile more activations could be implemented. The activation process is influenced by many parameters like Cs-flux, heat-cleaning temperature, conductivity, anode material, vacuum and the substrate. All of these parameters have an influence on the photocathodes quality and its lifetime, which are studied and compared.

Keywords: GaN photocathode; III-V semiconductor; caesium activation; NEA cathode; Quantum efficiency

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  • Open Access Logo Lecture (others) (Online presentation)
    High Brightness Electron beams generated from novel THermal resistant photocathodes (BETH) 2nd Collaboration Meeting, 10.07.2020, Siegen, Deutschland

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Permalink: https://www.hzdr.de/publications/Publ-31880
Publ.-Id: 31880


Status Report of ELBE and GaN

Xiang, R.; Teichert, J.; Arnold, A.; Ryzhov, A.; Murcek, P.; Zwartek, P.; Ma, S.; Schaber, J.

The SRF Gun has been running stabile using a magnesium cathode in the last year. Over 200 hours beam time have been provided in CW operation in 2019.
The magnesium bulk cathodes work routinely in ELBE and are polished and chemical cleaned before inserting them into the SRF Gun II, where they are again cleaned with an UV drive laser. Magnesium cathodes derives usually quantum effeciencies (QE) between 0.3 to 0.5% in SRF Gun II and offer a low risk of contaminations and an extreme long lifetime. The UV drive laser cleaning can be repeated several times to guarantee an high quality working cathode.
However, the particle accelerator community is always looking for new materials which can promise high quantum efficiency, a long lifetime and good vacuum stability, fast response time and low thermal emittance. Semiconductors such as GaN as novel materials for photocathodes are showing an enormous potential.
GaN is a semi-conductive material and well known for its high QE when illuminated with UV light. For the activation only caesium is required.
At the beginning of 2020 the first activation of GaN on sapphire substrate was successfully done. At first the GaN is heat treated at 610°C for 15 min and then activated with caesium to form a negative electron affinity surface. With 0.5 % quantum efficiency the first activation is all in all a successfully step for further promising GaN photocathodes.

Keywords: GaN; photocathode; SRF Gun; III-V semiconductor photocathode; Mg cathode

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  • Open Access Logo Lecture (others)
    High Brightness Electron beams generated from novel THermal resistant photocathodes (BETH) Meeting, 20.-21.01.2020, Siegen, Deutschland

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Permalink: https://www.hzdr.de/publications/Publ-31879
Publ.-Id: 31879


C. elegans possess a general program to enter cryptobiosis that allows dauer larvae to survive different kinds of abiotic stress

Gade, V. R.; Traikov, S.; Oertel, J.; Fahmy, K.; Kurzchalia, T. V.

All organisms encounter abiotic stress but only certain organisms are able to cope with extreme conditions and enter into cryptobiosis (hidden life). Previously, we have shown that C. elegans dauer larvae can survive severe desiccation (anhydrobiosis), a specific form of cryptobiosis. Entry into anhydrobiosis is preceded by activation of a set of biochemical pathways by exposure to mild desiccation. This process called preconditioning induces elevation of trehalose, intrinsically disordered proteins, polyamines and some other pathways that allow the preservation of cellular functionality in the absence of water. Here, we demonstrate that another stress factor, high osmolarity, activates similar biochemical pathways. The larvae that acquired resistance to high osmotic pressure can also withstand desiccation. In addition, high osmolarity significantly increases the biosynthesis of glycerol making larva tolerant to freezing. Thus, to survive abiotic stress, C. elegans activates a combination of genetic and biochemical pathways that serve as a general survival program.

Keywords: calorimetry; anhydrobiosis; metabolic monitoring; osmmotic stress

Permalink: https://www.hzdr.de/publications/Publ-31878
Publ.-Id: 31878


Current status of the simulations on Wu et al. using fbpic and PIConGPU

Pausch, R.; Döpp, A.

A brief summary to drive a discussion regarding the Wu et al. paper and a possible reply to it.

Keywords: PIConGPU; LWFA; PWFA; fbpic

  • Lecture (others)
    hybrid meeting, 06.02.2020, Paris, France

Permalink: https://www.hzdr.de/publications/Publ-31877
Publ.-Id: 31877


Data for: "First-principles modeling of plasmons in aluminum under ambient and extreme conditions"

Ramakrishna, K.; Cangi, A.; Dornheim, T.; Vorberger, J.; Baczewski, A.

The theoretical understanding of plasmon behavior is crucial for an accurate interpretation of inelastic
scattering diagnostics in many experiments. We highlight the utility of linear-response time-dependent density
functional theory (LR-TDDFT) as a first-principles framework for consistently modeling plasmon properties.
We provide a comprehensive analysis of plasmons in aluminum from ambient to warm dense matter conditions
and assess typical properties such as the dynamical structure factor, the plasmon dispersion, and the plasmon
lifetime. We compare our results with scattering measurements and with other TDDFT results as well as models
such as the random phase approximation, the Mermin approach, and the dielectric function obtained using static
local field corrections of the uniform electron gas parametrized from path-integral Monte Carlo simulations. We
conclude that results for the plasmon dispersion and lifetime are inconsistent between experiment and theories
and that the common practice of extracting and studying plasmon dispersion relations is an insufficient procedure
to capture the complicated physics contained in the dynamic structure factor in its full breadth.
 

Keywords: Warm dense matter; TDDFT

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Permalink: https://www.hzdr.de/publications/Publ-31876
Publ.-Id: 31876


Probing ultrafast magnetic-field generation by current filamentation instability in femtosecond relativistic laser-matter interactions

Raj, G.; Kononenko, O.; Gilljohann, M. F. F.; Doche, A.; Davoine, X.; Caizergues, C.; Chang, Y.-Y.; Couperus Cabadağ, J. P.; Debus, A.; Ding, H.; Förster, M.; Goddet, J.-P.; Heinemann, T.; Kluge, T.; Kurz, T.; Pausch, R.; Rousseau, P.; San Miguel Claveria, P.; Schöbel, S.; Siciak, A.; Steiniger, K.; Tafzi, A.; Yu, S.; Hidding, B.; Martinez De La Ossa, A.; Irman, A.; Karsch, S.; Döpp, A.; Schramm, U.; Gremillet, L.; Corde, S.

The current filamentation instability is a key phenomenon underpinning various processes in astrophysics, laboratory laser-plasma, and beam-plasma experiments. Here we show that the ultrafast dynamics of this instability can be explored in the context of relativistic laser-solid interactions through deflectometry by low-emittance, highly relativistic electron bunches from a laser wakefield accelerator. We present experimental measurements of the femtosecond timescale generation of strong magnetic-field fluctuations, with a measured line-integrated B field of 2.70±0.39kTμm. Three-dimensional, fully relativistic particle-in-cell simulations demonstrate that such fluctuations originate from the current filamentation instability arising at submicron scales around the irradiated target surface, and that they grow to amplitudes strong enough to broaden the angular distribution of the probe electron bunch a few tens of femtoseconds after the laser pulse maximum. Our results open a branch of physics experiments investigating the femtosecond dynamics of laser-driven plasma instabilities by means of synchronized, wakefield-accelerated electron beams.

Keywords: current filamentation; laser plasma

Permalink: https://www.hzdr.de/publications/Publ-31875
Publ.-Id: 31875


Review on the Compositional Variation of Eudialyte-Group Minerals in the Ilímaussaq Complex (South Greenland)

Marks, M. A. W.; Eggenkamp, H. G. M.; Atanasova, Petya; Mundel, F.; Kümmel, S.; Hagen, M.; Wenzel, T.; Markl, G.

We review the compositional variation of eudialyte-group minerals (EGM) from the Ilímaussaq complex in South Greenland. Investigated samples cover all major rock units and associated pegmatites and aplites. The whole data set (>3000 analyses from>250 samples) exhibits variable XMn (0.1–0.5), REE (0.2–1.7 apfu), Nb (0.1–0.4), and Cl contents (0.4–1.6 apfu). Most EGM compositions are Na-rich (13–15 apfu), while deviations to Na-rich but also to Na-poor compositions occur because of a combination of primary features (peralkalinity, water activity) and secondary alteration. During magma evolution, REE contents in EGM cores generally increase and reach their highest contents in the most evolved rock units of the complex. This points to the moderate compatibility of REE in EGM and a bulk D (cEGM/cmelt) value of <1 during magma differentiation. Chlorine contents in EGM cores continuously decrease, and are lowest at the rims of individual crystals, suggesting a continuous decrease of Cl activity in the magmas by large-scale EGM and sodalite extraction during the orthomagmatic stage and water enrichment during the late-magmatic stage. The overall variations of XMn across stratigraphy are only minor and likely influenced bythe co-crystallization of sodic pyroxene and amphibole (c.f. aegirine, arfvedsonite) and local phaseproportions. Similarly, Nb and Ti contents are influenced by co-crystallizing aenigmatite, rinkite, and others. Their presence buffers Ti and Nb contents to rather constant and low values, while their absence may cause variable enrichment on a local scale. Very low Sr contents (<0.1 apfu) in magmatic EGM from Ilímaussaq are related to the basaltic nature of the parental magmas of the complex, as large-scale plagioclase fractionation occurred prior to the formation of the Ilímaussaq magmas, effectively removing Sr from the system. This is in line with very strong negative Eu anomalies in EGM from Ilímaussaq. Consistently, Sr contents in EGM from alkaline complexes, for which foiditic parental magmas are assumed, are much higher and, in such cases, negative Eu anomalies aregenerally absent.

Keywords: Ilimaussaq; differentiation; eudialyte-group minerals; mineral chemistry

Permalink: https://www.hzdr.de/publications/Publ-31874
Publ.-Id: 31874


PIConGPU - a highly-parallel 3D3V particle-in-cell code

Pausch, R.; Bastrakov, S.; Debus, A.; Garten, M.; Huebl, A.; Marre, B.-E.; Meyer, F.; Steinger, K.; Widera, R.; Bussmann, M.

This talk will introduce the basic concepts of how particle-in-cell codes model plasma dynamics and discuss their implementation in the open-source code PIConGPU, focusing on how parallelism can be exploited to enable efficient scaling on today's largest HPC systems. Furthermore, the problem of IO limitations with larger simulations is discussed and the plugin method for in-situ data analysis in PIConGPU is presented to overcome these limitations. Finally, an overview of different physics cases simulated with PIConGPU is presented, ranging from small-scale laser-plasma accelerators to plasma jets in astrophysics.

Keywords: PIConGPU; LWFA; TNSA; alpaka; ISAAC; KHI

  • Lecture (others) (Online presentation)
    CASUS Seminar, 08.09.2020, Görlitz, Deutschland
  • Lecture (others)
    Seminar Series 'Hardware & Numerics', 24.11.2020, Dresden, Deutschland

Permalink: https://www.hzdr.de/publications/Publ-31873
Publ.-Id: 31873


Changes in Halogen (F, Cl, Br, and I) and S Ratios inRock-Forming Minerals as Monitors for MagmaticDifferentiation, Volatile-Loss, and HydrothermalOverprint: The Case for Peralkaline Systems

Eggenkamp, H. G. M.; Marks, M. A. W.; Atanasova, Petya; Wenzel, T.; Markl, G.

We determined the halogen (F, Cl, Br, and I) and sulfur (S) concentrations in Cl-rich rock-forming minerals from five peralkaline complexes. We investigated sodalite (N=42), eudialyte-group minerals (N=84), and tugtupite (N=8) from representative rock samples derived from Ilímaussaq (South Greenland), Norra Kärr (Sweden), Tamazeght (Morocco), Lovozero, and Khibina (Russian Federation). Taken together, sodalite and eudialyte-group minerals dominate the Cl and Br budget of the investigated rocks. For F, however, several other phases (e.g., amphibole, fluorite, villiaumite, and minerals of the rinkite group and the apatite supergroup) are additional sinks, and parts of the S may be scavenged in generally rare sulfides. The investigated minerals contain Cl at the wt.% level, F and S concentrations are in the hundreds to thousands of μg/g-range, Br is less common (0.2–200μg/g) and I is rare (mostly well below 1μg/g). Normalized to Cl, sodalite prefers Br relative to eudialyte-group minerals, while F is always enriched in the latter. Our data show that both F and S may represent important components in eudialyte-group minerals, sometimes at similar levels as Cl, which normally dominates. Sulfur reveals redox-dependent behavior: Under reduced crystallization conditions, S is more compatible in eudialyte-group minerals (EGM) than in sodalite, which flips to the opposite under water-rich and presumably more oxidized conditions. We investigate the applicability of F/Cl, Br/Cl, and S/Cl ratios in these minerals in peralkaline systems to better understand the interplay of magmatic differentiation, fluid loss and hydrothermal overprint. Similar to apatite in metaluminous systems, fractionation of sodalite, and eudialyte-group minerals in peralkaline magmas leads to decreasing Br/Cl ratios. The data presented in this study bear implications for the mineral chemistry and compositional variation of sodalite and especially EGM in general. Volatile components in EGM that are not normally considered, such as F and S, can reach concentrations of thousands of μg/g. Especially in the case of F, with its low atomic weight, the results obtained in this study indicate that it is very significant for formulae calculations, neutral charge-balance, and similar aspects at such concentration levels. This study demonstrates that halogen contents and ratios are sensitive monitors for a variety of processes in magmatic-hydrothermal systems, including magmatic fractionation, volatile loss, and fluid–rock interaction.

Keywords: eudialyte group minerals; sodalite; tugtupite; chloride; fluoride; bromide; sulfur; Ilímaussaq; peralkaline rocks

Permalink: https://www.hzdr.de/publications/Publ-31872
Publ.-Id: 31872


Design study for a compact laser-driven source for medical x-ray fluorescence imaging

Brümmer, T.; Debus, A.; Pausch, R.; Osterhoff, J.; Grüner, F.

Thomson scattering sources with their hard x-ray pencil beams represent a promising candidate to drive high-resolution X-ray Fluorescence Imaging (XFI). As XFI is a scanning imaging modality, it specifically requires pencil-beam geometries along with a high beam mobility. In combination with laser-wakefield acceleration (LWFA) such sources could provide the compactness needed for a future transition into clinical application. A sufficient flux within a small bandwidth could enable in-vivo high-sensitivity XFI for early cancer diagnostics and pharmacokinetic imaging. We thus report on a specific all-laser driven source design directed at increasing the photon number within the bandwidth and opening angle defined by XFI conditions. Typical parameters of driver lasers and electron bunches from LWFA are utilized and controlled within realistic parameter regions on the basis of appropriate beam optics. An active plasma lens is implemented for chromatic focal control of the bunch. Source performance limits are identified and compared to existing x-ray sources with regard to their potential to be implemented in future clinical XFI.

Keywords: Thomsons scattering; x-ray; light source; ClaRa2

Permalink: https://www.hzdr.de/publications/Publ-31871
Publ.-Id: 31871


Uranium(VI) reduction by a sulphate-reducing microorganism in Opalinus Clay pore water

Hilpmann, S.; Drobot, B.; Steudtner, R.; Bok, F.; Stumpf, T.; Cherkouk, A.

1 Introduction
Clay formations are potential host rocks for the long-term storage of high-level radioactive waste in a deep geological repository in Germany, besides salt and crystalline rock. A multi-barrier system is fa-vored, consisting of the technical (container with the waste), the geotechnical (sealing and backfilling material, e.g. bentonite) and the geological barrier (host rock) to isolate it from the biosphere.
Different studies showed that sulphate-reducing microorganisms, especially Desulfosporosinus species, occur in various clay formations, as well as in bentonite [1,2]. Desulfosporosinus hippei DSM 8344 is an anaerobic spore-forming microorganism isolated from permafrost soil [3] and a close phylogenetic relative of the Desulfosporosinus species detected in clay formations. Therefore, this strain was selected to study the reduc-tion of uranium(VI) to the less mobile uranium(IV).

2 Results
A time-dependent experiment in artificial Opalinus Clay pore water [4] (100 µM uranium(VI), pH 5.5) revealed a 95 % removal of uranium from the supernatant within 24 h. The corresponding microscopy of live/dead stained cells showed the formation of agglomerates and an increasing number of dead cells within the incubation time. The black colouring of the agglomerates already provided hints of the occur-ring reduction of uranium(VI).
Different aqueous species including uranyl(VI) lactate and uranyl(VI) carbonate complexes are present in the supernatant, as determined by time-resolved laser-induced luminescence spectroscopy. The assign-ment of the different species was possible by comparison with reference spectra. While the amount of the uranyl(VI) lactate complex decreased with the incubation time, the uranyl(VI) carbonate fraction re-mained almost constant. This leads to the assumption, that the cells reduce only the uranyl(VI) lactate complex. This conclusion can be supported by the fact that the reduction process did not take place in bicarbonate buffer, where the uranyl(VI) carbonate complexes are dominant, using the same microor-ganism.
The comparison of the UV/VIS band positions of the dissolved cell pellets with the spectra of pure uranium(IV) and uranyl(VI) samples provides clear evidence of the formed uranium(IV). Furthermore, bands of uranyl(VI) occur in the spectrum, as well. Therefore, a combination of a sorption and reduction processes is assumed. These findings offer new insights into the microbe-actinide interactions relevant to high-level radioactive waste disposal in clay rock.

The authors gratefully acknowledge the funding provided by the German Federal Ministry of Education and Research (BMBF) (Grant 02NUK053E) and The Helmholtz Association (Grant SO-093).

References
[1] A. Bagnoud et al., “Reconstructing a hydrogen-driven microbial metabolic network in Opalinus Clay rock”, Nat. Commun. 7, 1–10 (2016)
[2] N. Matschiavelli et al., “The year-long development of microorganisms in uncompacted Bavarian bentonite slurries at 30 °C and 60 °C”, Environ. Sci. Technol. 53, 10514–10524 (2019).
[3] A. Vatsurina et al., “Desulfosporosinus hippei sp. nov., a mesophilic sulfate-reducing bacterium isolated from permafrost”, Int. J. Syst. Evol. Microbiol. 58, 1228–1232 (2008).
[4] P. Wersin et al. “Biogeochemical processes in a clay formation in situ experiment: Part A - Overview, experimental design and water data of an experiment in the Opalinus Clay at the Mont Terri Underground Research Laboratory, Switzerland”, Appl. Geochemistry 26, 931–953 (2011).

Keywords: uranium(VI) reduction; sulphate-reducing bacteria; clay rock

  • Lecture (Conference) (Online presentation)
    Tage der Standortauswahl Freiberg 2021, 11.-12.02.2021, Freiberg, Deutschland
  • Poster (Online presentation)
    Tage der Standortauswahl Freiberg 2021, 11.-12.02.2021, Freiberg, Deutschland

Permalink: https://www.hzdr.de/publications/Publ-31870
Publ.-Id: 31870


Wire-mesh sensor data set of gas-water flow in a horizontal pipe

de Assis Dias, F.; Pipa, D. R.; Morales, R. E. M.; Da Silva, M. J.

Wire-mesh sensor raw data of gas-water pipe flow. The experiments were performed at the Federal University of Paraná in a setup located at the NUEM (Núcleo de Escoamento Multifásico). The flow loop is composed of a horizontal pipe of 26 mm inner diameter and 9 m long. The data set are measurements of wire-mesh sensors with the following resolutions: 12x12, 8x8, 6x6, 4x4 and 2x2.

Keywords: wire-mesh sensor; multiphase flow

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Permalink: https://www.hzdr.de/publications/Publ-31869
Publ.-Id: 31869


First-principles modeling of plasmons in aluminum under ambient and extreme conditions

Ramakrishna, K.; Cangi, A.; Dornheim, T.; Vorberger, J.

The numerical modeling of plasmon behavior is crucial for an accurate interpretation of inelastic scattering diagnostics in many experiments. We highlight the utility of linear-response time-dependent density functional theory (LR-TDDFT) as an appropriate first-principles framework for a consistent modeling of plasmon properties. We provide a comprehensive analysis of plasmons from ambient throughout warm dense conditions and assess typical properties such as the dynamical structure factor, the plasmon dispersion, and the plasmon width. We compare them with experimental measurements in aluminum accessible via x-ray Thomson scattering and with other dielectric models such as the Lindhard model, the Mermin approach based on parametrized collision frequencies, and the dielectric function obtained using static local field corrections of the uniform electron gas parametrized from path integral Monte Carlo simulations both at the ground state and at finite temperature. We conclude with the remark that the common practice of extracting and employing plasmon dispersion relations and widths is an insufficient procedure to capture the complicated physics contained in the dynamic structure factor in its full breadth.

Keywords: Warm dense matter

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Permalink: https://www.hzdr.de/publications/Publ-31868
Publ.-Id: 31868


Attenuating the fermion sign problem in path integral Monte Carlo simulations using the Bogoliubov inequality and thermodynamic integration

Dornheim, T.; Invernizzi, M.; Hirshberg, B.; Vorberger, J.

Accurate thermodynamic simulations of correlated fermions using path integral Monte Carlo (PIMC) methods are of paramount importance for many applications such as the description of ultracold atoms, electrons in quantum dots, and warm-dense matter. The main obstacle is the fermion sign problem (FSP), which leads to an exponential increase in computation time both with increasing the system-size and with decreasing temperature. Very recently, Hirshberg et al.[J. Chem. Phys. 152, 171102 (2020)] have proposed to alleviate the FSP based on the Bogoliubov inequality. In the present work, we extend this approach by adding a parameter that controls the perturbation, allowing for an extrapolation to the exact result. In this way, we can also use thermodynamic integration to obtain an improved estimate of the fermionic energy. As a test system, we choose electrons in 2D and 3D quantum dots and find in some cases a speed-up exceeding 10^ 6, as compared to standard PIMC, while retaining a relative accuracy of ~0.1%. Our approach is quite general and can readily be adapted to other simulation methods.

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Permalink: https://www.hzdr.de/publications/Publ-31866
Publ.-Id: 31866


Finite-size effects in the reconstruction of dynamic properties from ab initio path integral Monte Carlo simulations

Dornheim, T.; Vorberger, J.

We systematically investigate finite-size effects in the dynamic structure factor S(q,ω) of the uniform electron gas obtained via the analytic continuation of ab initio path integral Monte Carlo data for the imaginary-time density–density correlation function F(q,τ). Using the recent scheme by Dornheim et al. [Phys. Rev. Lett. 121, 255001 (2018)], we find that the reconstructed spectra are not afflicted with any finite-size effects for as few as N=14 electrons both at warm dense matter (WDM) conditions and at the margins of the strongly correlated electron liquid regime. Our results further corroborate the high quality of our current description of the dynamic density response of correlated electrons, which is of high importance for many applications in WDM theory and beyond.

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Permalink: https://www.hzdr.de/publications/Publ-31865
Publ.-Id: 31865


Effective Static Approximation: A Fast and Reliable Tool for Warm-Dense Matter Theory

Dornheim, T.; Cangi, A.; Ramakrishna, K.; Böhme, M.; Tanaka, S.; Vorberger, J.

We present an effective static approximation (ESA) to the local field correction (LFC) of the electron gas that enables highly accurate calculations of electronic properties like the dynamic structure factor S(q,ω), the static structure factor S(q), and the interaction energy v. The ESA combines the recent neural-net representation by T. Dornheim et al., [J. Chem. Phys. 151, 194104 (2019)] of the temperature-dependent LFC in the exact static limit with a consistent large wave-number limit obtained from quantum Monte Carlo data of the on-top pair distribution function g(0). It is suited for a straightforward integration into existing codes. We demonstrate the importance of the LFC for practical applications by reevaluating the results of the recent x-ray Thomson scattering experiment on aluminum by Sperling et al. [Phys. Rev. Lett. 115, 115001 (2015)]. We find that an accurate incorporation of electronic correlations in terms of the ESA leads to a different prediction of the inelastic scattering spectrum than obtained from state-of-the-art models like the Mermin approach or linear-response time-dependent density functional theory. Furthermore, the ESA scheme is particularly relevant for the development of advanced exchange-correlation functionals in density functional theory.

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Permalink: https://www.hzdr.de/publications/Publ-31864
Publ.-Id: 31864


Pump-probe response of correlated materials under high pressures

Pashkin, O.

Time-resolved optical spectroscopy is a very powerful tool for studying the photoinduced phase transitions and ultrafast dynamics in strongly correlated electronic systems. We reinforce this method by combining it with the high-pressure technique which allows to tune the strength of electronic correlations and Fermi surface nesting in a system. Several application examples for the investigation of the pressure-induced phenomena such as the metallization in VO2 and the suppression of the charge-density wave in CeTe3 and the spin-density wave in BaFe2As2 will be discussed.

  • Lecture (others) (Online presentation)
    Elasto-Q-Mat Colloquia, 10.12.2020, Mainz, Deutschland

Permalink: https://www.hzdr.de/publications/Publ-31863
Publ.-Id: 31863


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