Publications Repository - Helmholtz-Zentrum Dresden-Rossendorf

"Online First" included
Approved and published publications
Only approved publications

41397 Publications

Therapeutic Potential of Nitric Oxide releasing Selective Estrogen Receptor Modulators (NO-SERMs) in Malignant Melanoma

Bechmann, N.; Calsina, B.; Richter, S.; Pietzsch, J.

Malignant melanoma has a steadily increasing incidence, but treatment options are still limited and prognosis for patients, especially for men, is poor. To investigate whether targeting estrogen receptor (ER) signaling is a valid therapeutic approach, we retrospectively analyzed ER gene expression profiles in 448 melanoma patients. High ERα gene expression was associated with improved overall survival (HR=0.881; 95% Cl=0.793-0.979, p=0.018) and increased with tumor stage, while ERβ gene expression did not change with tumor progression. This seemingly protective function of ERα led us to speculate that specific targeting of ERβ has a therapeutic benefit in malignant melanoma. A new type of ERβ-selective ER modulator with a nitric oxide (NO•) releasing moiety (NO-SERM 4d) significantly reduced the pro-metastatic behavior of two melanoma cell lines (A2058 and MelJuso). Epithelial-mesenchymal transition in melanoma is consistent with a switch from E- to N-cadherin expression, mediating the invasive phenotype. NO-SERM 4d reduced N-cadherin expression and impaired spheroid formation in A2058 cells. In addition, growth of A2058 spheroids was significantly reduced, confirming the anti-tumorigenic potential of NO-SERM 4d. Targeting ERβ signaling combined with targeted NO• release represents a promising therapeutic approach in malignant melanoma that has potential to prevent metastatic spread and reduce tumor growth.

Keywords: bifunctional drugs; cadherins; epithelial-mesenchymal transition; nitric oxide donors; skin cancer; selective estrogen receptor modulators (SERMs); metastasis; tamoxifen; tumor spheroid model

Downloads

Permalink: https://www.hzdr.de/publications/Publ-33643
Publ.-Id: 33643


Laser-driven proton acceleration at Draco PW: a novel platform for ultra-high dose rate radiobiology

Brack, F.-E.; Kroll, F.; Beyreuther, E.; Jansen, J.; Karsch, L.; Kraft, S.; Leßmann, E.; Metzkes-Ng, J.; Pawelke, J.; Reimold, M.; Schlenvoigt, H.-P.; Schramm, U.; Szabo, R.; Umlandt, M. E. P.; Ziegler, T.; Zeil, K.

Background and Aims
After the rediscovery of the normal tissue sparing FLASH effect of high dose rate radiation, research activities on this topic have been revived. But especially for protons, the portfolio of accelerators capable of performing studies at ultra-high dose rates is limited. Laser-plasma accelerators (LPA) can generate extremely intense proton bunches of many 10 MeV kinetic energy. In combination with dedicated dose delivery systems, LPA proton sources facilitate peak dose rates well above 10^8 Gy/s in a pulse structure regime complementary to conventional accelerators.

Methods
The reliable generation of proton spectra beyond 60 MeV at DRACO-PW [Ziegler et al, SciRep2021], combined with a dedicated energy selective pulsed magnet beam transport system [Brack et al, SciRep2020], allows tailored sample-specific dose distributions. Adapted on-shot dosimetry enables the required spectral monitoring of every proton bunch. Two irradiation series on volumetric biological samples were performed at DRACO-PW, accompanied by reference irradiations at the University Proton Therapy Dresden.

Results
The first small animal pilot study at a laser-driven proton source was conducted successfully. The mouse-ear tumor model’s requirements [Beyreuther et al, PLoS One2018] were fulfilled and verified at high precision (+/- 5%) concerning predefined dose value and conformity. Complementary, a study investigating dose-rate effects such as FLASH was performed irradiating zebrafish embryos with above 10^9 Gy/s.

Conclusions
We present a laser-based irradiation platform at the DRACO-PW facility that enables systematic radiobiological studies, laying the foundations for further studies at LPA sources exploring ultra-high dose-rate effects, such as FLASH, over previously unreachable parameter space.

Keywords: FLASH; Laser-driven protons; Ultra high dose rate

  • Lecture (Conference) (Online presentation)
    FLASH Radiotherapy & Particle Therapy, 01.-03.12.2021, Vienna, Austria

Permalink: https://www.hzdr.de/publications/Publ-33642
Publ.-Id: 33642


Towards a sampling protocol for the resource assessment of critical raw materials in tailings storage facilities

Blannin, R.; Frenzel, M.; Tolosana Delgado, R.; Gutzmer, J.

Resource estimates are crucial to assess the economic potential of tailings storage facilities (TSF) for re-mining and the extraction of critical raw materials. However, a lack of consensus exists on best practices in sampling for this purpose. This study aims to address this gap by assessing different sampling schemes for the resource classification of TSFs. To do so, one layer of a TSF was sampled with regular and nested grids of varying sizes and additional random holes. Systematic spatial trends in the data were fitted with low-order polynomial functions of the coordinates and the grayscale values of a historical aerial photograph of the same layer of the TSF. Variography was performed on the trend residuals, and exponential or Gaussian variogram models were fitted. Universal Sequential Gaussian Simulation was then used to produce 1000 realisations of the potential ground truth. The optimum sampling strategy was investigated by re-sampling these realisations with varying sample densities and configurations and using geostatistical modelling of the re-sampled data to assess uncertainties on the estimated metal tonnages. Robust estimates of metal tonnages can be achieved at relatively low sampling densities, particularly with regular grids. When historical image information is used, spatial variability is better reproduced, and a lower number of samples is required to reach a certain confidence level. Furthermore, an approach to approximate expected errors on grades/tonnages estimated with a given sampling scheme was developed to assess whether further sampling is required. Overall, the findings of this study have clear and transferrable implications for the best-practice sampling and modelling of TSFs and their critical raw materials resource.

Keywords: Tailings storage facility; Sampling; Geostatistics; Error; Modelling; Mineral Resources and Reserves

Permalink: https://www.hzdr.de/publications/Publ-33641
Publ.-Id: 33641


Predictive modelling of mineralogical and textural properties of tailings using geochemical data

Blannin, R.; Frenzel, M.; Gutzmer, J.

Tailings deposits pose a significant threat to the environment and/or contain residual metal contents that may be of economic interest. The mineralogical and textural properties of the tailings dictate both processing behaviour and potential for acid mine drainage. Automated Scanning Electron Microscope-based image analyses enable valuable quantitative mineralogical and textural data to be obtained. Such methods are, however, time and cost intensive. This study investigates the extent to which geochemical data can be related to mineralogical and textural data of tailings materials. Models based on the dominant components (PCs) from principal component analysis were tested for mineral abundance, particle and mineral grain size distributions (PSD, GSD), and degree of liberation. Sedimentary-style deposition of the tailings is represented by the main trend between PCs 1 and 2. This being the dominant process in the tailings, PC 1 is a robust estimator for mineral contents, PSD and mineral GSDs. Degree of liberation is less well constrained by the PCs. This study clearly demonstrates that prediction of mineralogical and textural parameters of tailings with geochemical data is possible. Considering that the dominant processes should be the same in similarly deposited tailings deposits, these findings are widely applicable.

  • Open Access Logo Contribution to proceedings
    16th SGA Biennial Meeting 2022, 28.-31.03.2022, Rotorua, New Zealand

Permalink: https://www.hzdr.de/publications/Publ-33640
Publ.-Id: 33640


Fully characterised and online monitored beamline for high dose rate laser proton irradiation experiments at Draco PW

Brack, F.-E.; Kroll, F.; Gaus, L.; Bernert, C.; Beyreuther, E.; Cowan, T.; Karsch, L.; Kraft, S.; Leßmann, E.; Metzkes-Ng, J.; Pawelke, J.; Rehwald, M.; Reimold, M.; Schlenvoigt, H.-P.; Schramm, U.; Sobiella, M.; Umlandt, M. E. P.; Ziegler, T.; Zeil, K.

Laser-driven proton pulse provide unique properties in terms of pulse structure (ns) and instantaneous dose rate (10^9 Gy/s) but - inherently broadband and highly divergent - pose a challenge to established beamline concepts on the path to application-adapted irradiation field formation, particularly for three-dimensional cases. We present the successful implementation and characterisation of a highly efficient and tuneable dual pulsed solenoid beamline at the Draco PW facility[1] to generate volumetric dose distribution tailored to specific applications[2].
The vast experimental scope and already successfully performed studies range from systematic volumetric in-vivo tumour irradiations in a dedicated mouse model (with a stable mean dose delivery of ±10 % and a spatial dose homogeneity of ±5 % over a cylindrical volume of 5 mm diameter and height) to high-dose-rate irradiations in the FLASH regime (using proton peak dose rates of up to 10^9 Gy/s with about 20 Gy/shot homogeneously over a cylindrical sample volume of 4.5 mm diameter and 3 mm height) as well as particle diagnostics commissioning (with a multitude of spatial and spectral dose distributions).
The beamline setup is complemented by a complex beam monitoring and dosimetry detector suite adapted to the ultra-high dose rate pulses and is in its unique synergy and redundancy capable of %-level precision dose delivery to samples as required for systematic irradiation studies. In addition to established radiochromic film dosimetry, the detector suite includes saturation-corrected (transmission) ionisation chambers [3] as well as screen and bulk scintillator setups, partly with tomographic reconstruction capabilities for 3D dose distribution retrieval. Moreover, non-invasive, single-shot-capable online time-of-flight-based spectral characterisation of filtered proton pulses has proven a powerful tool for beam monitoring as well as dosimetric purposes.
In this presentation the complex and versatile dose delivery system of laser-driven protons at the Draco PW using pulsed solenoids will be discussed. Its characterisation, technological development and improvement as well as the dosimetry suite as a vital part of the precise dose delivery will be addressed, while the presentation by U. Schramm covers recent experimental activities in detail.
[1] T. Ziegler, et al., Proton beam quality enhancement by spectral phase control of a PW-class laser system, https://arxiv.org/abs/2007.11499 (2020)
[2] Brack, et al., Spectral and spatial shaping of laser-driven proton beams using a pulsed high-field magnet beamline, SciRep, 10:9118, (2020)
[3] Gotz M, et al., A new model for volume recombination in plane‐parallel chambers in pulsed fields of high dose‐per‐pulse. Phys Med Biol., 62: 8634, (2017)

  • Invited lecture (Conferences) (Online presentation)
    SPIE 2021 ALPA, 21.04.2021, Prague, Czech Republic
  • Lecture (others) (Online presentation)
    LPA online seminar, 10.03.2021, Dresden, Germany

Permalink: https://www.hzdr.de/publications/Publ-33639
Publ.-Id: 33639


Dataset in paper 'FISHMORPH: A global database on morphological traits of freshwater fishes'

Brosse, S.; Charpin, N.; Su, G.; Toussaint, A.; Herrera-R, G. A.; Tedesco, P. A.; Villéger, S.

This dataset is publiched in the paper "FISHMORPH: A global database on morphological traits of freshwater fishes" in Global Ecology and Biogeography (doi.org/10.1111/geb.13395). The FISHMORPH database includes 10 morphological traits measured on 8,342 freshwater fish species, covering 48.69% of the world freshwater fish fauna. It provides the most comprehensive database on fish morphological traits to date. It represents an essential source of information for ecologists and environmental managers seeking to consider morphological patterns of fish faunas throughout the globe, and for those interested in current and future impacts of human activities on the morphological structure of fish assemblages. 

Related publications

Downloads

Permalink: https://www.hzdr.de/publications/Publ-33638
Publ.-Id: 33638


QE and life time of GaN photocathodes for SRF gun-II at HZDR

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

Negative electron affinity (NEA) GaAs- and GaN-based photocathodes are used in modern night vison detectors and light emitting diodes. GaAs semiconductors are already used as electron sources in particle accelerators and well- studied. Like GaAs, GaN belongs to the
III-V semiconductor group. It is assumed that GaN, like GaAs, shows enormous potential as a novel electron source for particle accelerators.

P-type GaN on a substrate material (sapphire, silicon, copper or SiC) is activated by a thin layer of caesium and illuminated by ultra-violet (UV) light to observe the gained photocurrent.
To produce an NEA surface and thus highest QE, it is necessary to remove any residual impurities on the GaN surface. Therefore, GaN is chemical cleaned and vacuum thermal cleaned before it is caesium-activated. The aim of the thermal treatment is to gain an atomically clean surface.
With a comparison of different substrate materials, chemical pre-cleaning, thermal treatment, and activation parameters (e.g. caesium-flux), the quantum efficiency, lifetime and the re-activation of the photocathode is studied. Additionally, the morphology and surface composition of the GaN is examined by XPS, AFM, SEM and EDX.

Keywords: GaN photocathode; Quantum efficiency

Related publications

  • Open Access Logo Poster (Online presentation)
    Photocathode Physics Photoinjector (P3) workshop, 10.-13.10.2021, Stanford, USA

Downloads

Permalink: https://www.hzdr.de/publications/Publ-33637
Publ.-Id: 33637


Outcrop sensing for the exploration of REEs and lithium

Lorenz, S.; Booysen, R.; Thiele, S. T.; Zimmermann, R.; Kirsch, M.; Gloaguen, R.

Non-invasive technologies are key to ensure the sustainable exploration and mining of critical materials such as lithium and rare earth elements (REE), which are needed to fuel battery, magnet, and photovoltaic technologies for the transition towards low-carbon economies (Simandl, 2014; Heredia et al., 2020). Innovative sensing methods such as hyperspectral imaging allow the remote identification and high spatial resolution mapping of characteristic light-material interactions (“spectral fingerprints”) indicative of specific minerals and raw materials. These maps can be produced rapidly to support geological investigations during both exploration and mining. Accurate positioning of the spectral information in 3D space allows creating digital twins of outcrops and mines and integrating the spectral mapping results with other data such as from drill-cores or geochemical sampling. However, the low concentration and generally subtle spectral features associated with Li-bearing minerals and REEs present challenges for spectral mapping at the outcrop scale and, as a result, past approaches tended to use indirect methods based on, for example, mineral associations (Cardoso-Fernandes et al., 2020).

Direct mapping of REE and Li-minerals abundances is possible using high-resolution, high-quality spectral data and appropriate correction techniques. Sensor miniaturisation and development of new platforms now allow rapid data collection across large areas. These advances, combined with novel radiometric and geometric correction workflows (e.g., Thiele et al., 2021), recently allowed the direct detection of REE- and Li-bearing minerals at outcrop scale, using close-range ground-based (Boesche et al., 2015; Booysen et al., 2021) and drone-borne platforms (Booysen et al., 2020).

Two case studies of open pit mines, one from Siilinjärvi, Finland, (Fig. 1), the second from Uis, Namibia (Fig. 2) demonstrate direct 3D mapping of REE and Li mineralization. First, we captured ground-based photographs that were used for structure-from-motion, multi-view-stereo (SfM-MVS) photogrammetry to create digital 3D models/point clouds. We also acquired terrestrial hyperspectral data using a Specim AisaFENIX hyperspectral line scanner (push-broom scanner). The sensor covers the electromagnetic spectrum from 350 to 2500 nm over 384 spatial pixels and creates a datacube by steady rotation on a tripod. The resulting panoramic scan covers the important spectral features for both REE (578 nm, 740 nm and 799 nm for neodymium) and Li-bearing minerals (1593 nm and 1839 nm for cookeite, and 1538 nm, 1766 nm and 1850 nm for montebrasite). However, the results are subject to immense geometric distortion as well as radiometric influences that complicate spectral mapping, spatial localization, and scaling. We applied the processing workflow of Thiele et al. (2021) to perform accurate re-projection in original 3D space, as well as important radiometric and topographic corrections by combining the hyperspectral scans with the photogrammetric 3D point clouds. We subsequently mapped the occurrence of REEs and Li-bearing minerals based on their subtle characteristic spectral absorptions, and validated the occurrences by field sampling and mineralogical and elemental analysis.

Innovative remote sensing approaches allow us to rapidly create accurate digital twins of mine faces and natural geological outcrops. The 3D point clouds provide information on geological structure and can be populated with an arbitrary number of point-specific, high-dimensional spectral attributes to create so-called “hyperclouds”. Accurate processing and correction of the contained spectral information enables us to directly map the subtle spectral features indicative of Li- and REE-bearing minerals. Efficient remote mapping, even in complex terrains, is highly beneficial not only for initial targeting, but also for monitoring ore extraction, thus facilitating both exploration and optimized extraction.

We thank AfriTin and Yara Oy for support during field work, access to the mine site, and geological information and geochemical data.

  • Contribution to proceedings
    Critical Minerals: From discovery to supply chain, 16.-18.11.2021, online, online
  • Invited lecture (Conferences) (Online presentation)
    Critical Minerals: From discovery to supply chain, 16.-18.11.2021, online, online

Permalink: https://www.hzdr.de/publications/Publ-33636
Publ.-Id: 33636


Data publication: Precise measurement of gas parameters in a realistic RPC configuration: the currently used R134a gas and a potential alternative eco-gas

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

Theses data are taken during the measurement and folded to support the research in the related publication.

Keywords: Resistive Plate Chambers; Townsend coefficient; Electron drift velocity; HFO

Related publications

Downloads

Permalink: https://www.hzdr.de/publications/Publ-33635
Publ.-Id: 33635


Performance Portability with alpaka

Stephan, J.

The alpaka library is a header-only C++14 abstraction library for accelerator development. Its aim is to provide performance portability across accelerators through the abstraction (not hiding!) of the underlying levels of parallelism. In this lecture we will cover the basics of how to program HPC applications with alpaka in a portable yet performant way and have a look at the software ecosystem surrounding alpaka.

Keywords: alpaka; HPC; CUDA; parallel programming; performance portability; C++; GPU; heterogeneous computing; accelerator programming

  • Open Access Logo Lecture (others)
    Twelfth INFN International School on: "Architectures, tools and methodologies for developing efficient large scale scientific computing applications" (ESC 2021), 04.-09.10.2021, Bertinoro, Italia

Downloads

Permalink: https://www.hzdr.de/publications/Publ-33634
Publ.-Id: 33634


The Potential of Machine Learning for a More Responsible Sourcing of Critical Raw Materials

Ghamisi, P.; Rafiezadeh Shahi, K.; Duan, P.; Rasti, B.; Lorenz, S.; Booysen, R.; Thiele, S.; Contreras, I. C.; Kirsch, M.; Gloaguen, R.

The digitization and automation of the raw material sector is required to attain the targets set by the Paris Agreements and support the sustainable development goals defined by the United Nations. While many aspects of the industry will be affected, most of the technological innovations will require smart imaging sensors. In this review, we assess the relevant recent developments of machine learning for the processing of imaging sensor data. We first describe the main imagers and the acquired data types as well as the platforms on which they can be installed. We briefly describe radiometric and geometric corrections as these procedures have been already described extensively in previous works. We focus on the description of innovative processing workflows and illustrate the most prominent approaches with examples. We also provide a list of available resources, codes, and libraries for researchers at different levels, from students to senior researchers, willing to explore novel methodologies on the challenging topics of raw material extraction, classification, and process automatization.

Related publications

Downloads

Permalink: https://www.hzdr.de/publications/Publ-33633
Publ.-Id: 33633


Unsupervised Data Fusion with Deeper Perspective: A Novel Multi-Sensor Deep Clustering Algorithm

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

The ever-growing developments in technology to capture different types of image data (e.g., hyperspectral imaging and Light Detection and Ranging (LiDAR)-derived digital surface model (DSM)), along with new processing techniques, have led to a rising interest in imaging applications for Earth observation. However, analyzing such datasets in parallel, remains a challenging task. In this paper, we propose a multi-sensor deep clustering (MDC) algorithm for the joint processing of multi-source imaging data. The architecture of MDC is inspired by autoencoder (AE)-based networks. The MDC paradigm includes three parallel networks, a spectral network using an autoencoder structure, a spatial network using a convolutional autoencoder structure, and lastly, a fusion network that reconstructs the concatenated image information from the concatenated latent features from the spatial and spectral network. The proposed algorithm combines the reconstruction losses obtained by the aforementioned networks to optimize the parameters (i.e., weights and bias) of all three networks simultaneously. To validate the performance of the proposed algorithm, we use two multi-sensor datasets from different applications (i.e., geological and rural sites) as benchmarks. The experimental results confirm the superiority of our proposed deep clustering algorithm compared to a number of state-of-the-art clustering algorithms. The code will be available at: https://github.com/Kasra2020/MDC.

Related publications

Downloads

Permalink: https://www.hzdr.de/publications/Publ-33632
Publ.-Id: 33632


Data Alb/SSTR2 ligands

Wodtke, R.

Raw data to MST, NMR, PET and evaluations

Related publications

Downloads

Permalink: https://www.hzdr.de/publications/Publ-33631
Publ.-Id: 33631


The Niederschlag fluorite-(barite) deposit, Erzgebirge/Germany—a fluid inclusion and trace element study

Haschke, S.; Gutzmer, J.; Wohlgemuth-Ueberwasser, C. C.; Krämer, D.; Burisch, M.

The Niederschlag fluorite-barite vein deposit in the Western Erzgebirge, Germany, has been actively mined since 2013. We present the results of a first comprehensive study of the mineralogy, petrography, fluid inclusions, and trace element geochemistry of fluorite related to the Niederschlag deposit. Two different stages of fluorite mineralization are recognized. Stage I fluorite is older, fine-grained, associated with quartz, and forms complex breccia and replacement textures. Conversely, the younger Stage II fluorite is accompanied by barite and often occurs as banded and coarse crystalline open-space infill. Fluid inclusion and REY systematics are distinctly different for these two fluorite stages. Fluid inclusions in fluorite I reveal the presence of a low to medium saline (7–20% eq. w (NaCl+CaCl2)) fluid with homogenization temperatures of 140–180 °C, whereas fluorite II inclusions yield distinctly lower (80–120 °C) homogenization temperatures with at least two high salinity fluids involved (18–27% eq. w (NaCl+CaCl2)). In the absence of geochronological data, the genesis of the earlier generation of fluorite-quartz mineralization remains enigmatic but is tentatively related to Permian magmatism in the Erzgebirge. The younger fluorite-barite mineralization, on the other hand, has similarities to many fluorite-barite-Pb-Zn-Cu vein deposits in Europe that are widely accepted to be related to the Mesozoic opening of the northern Atlantic Ocean.

Keywords: Fluorite; Microthermometry; Fluid inclusions; Rare earth elements; Geochemistry; Metallogenesis; Erzgebirge

Permalink: https://www.hzdr.de/publications/Publ-33630
Publ.-Id: 33630


Gold and silver deportment in sulphide ores - a case study of the Freiberg epithermal Ag-Pb-Zn district, Germany

Swinkels, L. J.; Burisch, M.; Rossberg, C. M.; Oelze, M.; Gutzmer, J.; Frenzel, M.

Deportment data is essential for the planning of mining and minerals processing operations. This need is particularly tangible for deposits of noble metals, such as gold and silver. Therefore, the current paucity of published gold and silver deportment data for individual ore deposits and districts – and the concomitant lack of understanding how this relates to salient geological and mineralogical features of these deposits – is surprising. In the present study, we apply a combination of bulk geochemistry, laser ablation-inductively coupled plasma-mass spectrometry, electron microprobe analysis, and mineral liberation analysis to gold- and silver-rich samples from the epithermal Freiberg Ag-Pb-Zn district, to investigate variability in gold and silver deportments, as well as the corresponding geological/mineralogical controls. The results show that the main carriers of gold are electrum and arsenopyrite, whereas silver is mostly hosted by Ag-sulfosalts (pyrargyrite, miargyrite, polybasite) and fahlore (freibergite). Deportments vary greatly between samples. These variations can be related to the relative abundances of different minerals within the samples, which in turn reflect their spatio-temporal position within the district. Comparisons with other epithermal Ag-Pb-Zn districts similar to Freiberg indicate that the results presented here are of general significance.

Keywords: metal deportment; geometallurgy; automated mineralogy; Freiberg

Permalink: https://www.hzdr.de/publications/Publ-33629
Publ.-Id: 33629


Bis(amido)bis(oxinate)diamine ligands for theranostic radiometals

Southcott, L.; Whetter, J. N.; Wharton, L.; Patrick, B. O.; Zarschler, K.; Kubeil, M.; Stephan, H.; Jaraquemada-Pelaez, M. D. G.; Orvig, C.

With the interest in radiometal-containing diagnostic and therapeutic pharmaceuticals burgeoning, appropriate ligands to coordinate completely and stably said radiometals is essential. Reported here are two novel, bis(amido)bis(oxinate)diamine ligands, H2amidohox and H2amidoC3hox, that combine two 8-hydroxyquinoline with two amide donor groups and differ by one carbon in their 1,2-ethylenediaminevs. 1,3-diaminopropane backbones, respectively. Both ligands have been thoroughly studied via metal complexation, solution thermodynamics and radiolabeling with three radiometal ions: [nat/64Cu]Cu2+,
[nat/111In]In3+, and [nat/203Pb]Pb2+. X-ray crystallography determined the structures of the hexacoordinated Cu2+-ligand complexes, indicating a better fit of Cu2+ to the H2amidohox binding pocket. Concentration dependent radiolabeling with [64Cu]Cu2+ was quantitative as low as 1 μM with H2amidohox and 10 μM
with H2amidoC3hox within 5 minutes at room temperature. However, [64Cu][Cu(amidohox)] maintained higher kinetic inertness against a superoxide dismutase enzyme-challenge assay and ligand challengescompared to the [64Cu][Cu(amidoC3hox)] counterpart. Similarly, H2amidohox had significantly higher
radiochemical conversion with both [111In]In3+ (97% at 1 μM) and [203Pb]Pb2+ (97% at 100 μM) under mild conditions compared to H2amidoC3hox (76% with [111In]In3+ at 1 μM and 0% with [203Pb]Pb2+). By studying non-radioactive and radioactive complexation with both ligands, a comprehensive understanding of the coordination differences between two- and three-carbon diamine backbones is discussed. Overall, the ethylenediamine backbone of H2amidohox proves to be superior with rapid radiolabeling and kinetic inertness towards competing ligands and proteins.

Keywords: [nat/111In]In3+; [nat/64Cu]Cu2+; [nat/203Pb]Pb2+; solution thermodynamic studies; coordination chemistry; theranostics

Permalink: https://www.hzdr.de/publications/Publ-33627
Publ.-Id: 33627


A Multi-Sensor Subspace-based Clustering Algorithm Using RGB and Hyperspectral Data

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

In this work, we introduce a multi-sensor subspace-based clustering algorithm that benefits from fine spectral-resolution hyperspectral images (HSIs) and fine spatial resolution RGB images. In order to extract spatial information, a hidden Markov random field (HMRF) is employed on the fine spatial-resolution RGB image, whereas, spectral information is derived from an HSI using an advanced sparse subspace clustering algorithm. The proposed algorithm is validated on two real geological data sets. The experimental results in this study show that the proposed algorithm outperforms the state-of-the-art clustering algorithms in terms of clustering accuracy.

Keywords: Hyperspectral images; RGB images; UAV data; Hidden Markov random field; Spectral-spatial clustering; Sparse representation; Data fusion

Permalink: https://www.hzdr.de/publications/Publ-33626
Publ.-Id: 33626


When is the Right Time to Apply Denoising?

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

Remote sensing data is contaminated with different types of noise that can severely affect the analysis of this data. Generally, in modern treatment chains of satellite and aerial data, denoising techniques are applied to atmospherically corrected images prior to further analysis (e.g., classification). However, since the noise contaminates the measured radiance at the sensor, it can influence the atmospheric correction in itself and consequently the remaining of the processing chain. In this paper, we compare the performance of a denoising technique, when applied before or after atmospheric correction. Our observations challenge the current de facto paradigm of denoising in a processing chain of spaceborne and airborne remotely sensed images.

Related publications

Downloads

Permalink: https://www.hzdr.de/publications/Publ-33625
Publ.-Id: 33625


Determination of high-time resolution mineral dust concentration in real-time by optical absorption measurements

Ivančič, M.; Ježek, I.; Rigler, M.; Gregorič, A.; Alföldy, B.; Podlipec, R.; Drinovec, L.; Pikridas, M.; Unga, F.; Sciare, J.; Yus-Díez, J.; Pandolfi, M.; Griša, M.

Mineral dust is an important natural source of aerosols and significantly influences air quality (Querol et al.,
Environ. Int., 2019) and the global radiation budget (Schepanski, Geosci., 2018). Frequent dust intrusions are
observed in the Mediterranean region (Ealo et al., Atmos. Chem. Phys., 2016; Pikridas et al., Atmos. Environ.,
2018) and Central Europe (Collaud Coen et al., Atmos. Chem. Phys., 2004; Schauer et al., Aerosol Air Qual.
Res., 2016), with high potential to cause exceedances of daily PM10 levels. To separate the influence of
anthropogenic and natural contribution to the PM10 levels, the new method was developed within the DNAAP
project (Detection of non-anthropogenic air pollution – http://www.aerosol.si/dnaap/).
Dust weakly absorbs light in the near ultra-violet and short wavelengths of the visible range, while the light
absorption of dust in longer wavelengths from the visible and near infra-red range is negligible. We used
filter-based photometer Aethalometer AE33 (Drinovec et al., Atmos. Meas. Tech., 2015) to measure the light
absorption at seven wavelengths, from 370 to 950 nm. The mineral dust is not the only light-absorbing aerosol
in the air. Black carbon (BC), a unique primary tracer for combustion emissions, strongly absorbs light across
the entire visual, near infra-red and near ultra-violet spectral range. Since optical absorption of mineral dust is
weaker than the optical absorption of black carbon, the coarse mode mineral particles have to be concentrated
using the high-volume virtual impactor (VI). The method is based on the optical absorption measurements of
the two sample streams, sampling particle size below 1 µm and sample stream with the concentrated coarse
mode particles, where mineral dust contribution is substantial. Experimental configuration includes two
Aethalometers AE33 with different size selective inlets: VI inlet for sampling coarse aerosol mode (mostly
mineral dust) and PM1 inlet for sampling fine mode of aerosols (mainly BC). The optical absorption of mineral
dust can be determined by subtracting the absorption of fine aerosol fraction (PM1) from the absorption of
aerosol sampled by the VI, taking into account the enhancement factor of VI setup (Drinovec et al., Atmos.
Meas. Tech., 2020). The mineral dust mass concentration is then calculated using mass absorption cross-section
(MAC) for dust which could be site and source-region specific.
The results from the measurement campaigns performed at six locations in the Mediterranean region will be
presented. The measurements took place in NE Spain (Barcelona – BCN, Montseny – MSY, Montsec – MSA),
on Cyprus (Nicosia – NI, Agia Marina Xyliatou – AMX), and in Slovenia (Ljubljana – LJ). Two year-long
datasets will be presented, focusing on the analyses of aerosol optical properties of PM1 and VI fractions. The
results were validated using low time resolution chemical specification of offline filters and a statistical
approach where dust was extracted from PM10 measurements for dust intrusions periods determined by models
and back-trajectory studies. For better understanding, helium ion microscopy (HIM) was applied to study the
microscopic differences between mineral dust and black carbon captured on the AE33 filter tapes.
This work was supported by SPIRIT Slovenia – Public Agency for Entrepreneurship, Internationalization,
Foreign Investments and Technology, project DNAAP.

Related publications

  • Lecture (Conference)
    DUST 2021, 04.-07.10.2021, Torre Cintola Conference Centre, MONOPOLI, Italy

Permalink: https://www.hzdr.de/publications/Publ-33623
Publ.-Id: 33623


Hyperspectral Image Analysis: From conventional model-based algorithms towards deep learning data-driven ones

Rasti, B.

Hyperspectral image analysis has considerably evolved during the past decades. The conventional model-based image processing and machine learning techniques are not efficient for hyperspectral image analysis, therefore, other advanced models such as spatial- spectral models were proposed to boost the hyperspectral analysis. Recent advances in ma- chine learning i.e., deep learning (DL) confirm that if an adequate amount of training data is supplied then DL-based algorithms outperform the conventional (shallow) ones. However, the available training data is often limited in hyperspectral imaging, therefore, the advan- tage of DL-based algorithms compared with shallow ones remains an open question. In this paper, we address this issue for two vibrant fields in hyperspectral image analysis i.e., Unmixing and Feature Extraction for Classification.

  • Invited lecture (Conferences) (Online presentation)
    OSA Optical Sensors and Sensing Congress 2021, 21.07.2021, Virtual, Virtual

Permalink: https://www.hzdr.de/publications/Publ-33619
Publ.-Id: 33619


UnDIP: Hyperspectral Unmixing Using Deep Image Prior

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

In this article, we introduce a deep learning-based technique for the linear hyperspectral unmixing problem. The proposed method contains two main steps. First, the endmembers are extracted using a geometric endmember extraction method, i.e., a simplex volume maximization in the subspace of the data set. Then, the abundances are estimated using a deep image prior. The main motivation of this work is to boost the abundance estimation and make the unmixing problem robust to noise. The proposed deep image prior uses a convolutional neural network to estimate the fractional abundances, relying on the extracted endmembers and the observed hyperspectral data set. The proposed method is evaluated on simulated and three real remote sensing data for a range of SNR values (i.e., from 20 to 50 dB). The results show considerable improvements compared to state-of-the-art methods. The proposed method was implemented in Python (3.8) using PyTorch as the platform for the deep network and is available online: https://github.com/BehnoodRasti/UnDIP.

Downloads

Permalink: https://www.hzdr.de/publications/Publ-33617
Publ.-Id: 33617


SUnCNN: Sparse Unmixing Using Unsupervised Convolutional Neural Network

Rasti, B.; Koirala, B.

In this letter, we propose a sparse unmixing technique using a convolutional neural network (SUnCNN) for hyperspectral images. SUnCNN is the first deep learning-based technique proposed for sparse unmixing. It uses a deep convolutional encoder-decoder to generate the abundances relying on a spectral library. We reformulate the sparse unmixing into an optimization over the deep network's parameters. Therefore, the deep network learns in an unsupervised manner to map a fixed input into the sparse optimum abundances. Additionally, SUnCNN holds the sum-to-one constraint using a softmax activation layer. The proposed method is compared with the state-of-the-art using two synthetic datasets and one real hyperspectral dataset. The overall results confirm that the proposed method outperforms the other ones in terms of signal to reconstruction error (SRE). Additionally, SUnCNN shows visual superiority for both real and synthetic datasets compared with the competing techniques. The proposed method was implemented in Python (3.8) using PyTorch as the platform for the deep network and is available online: https://github.com/BehnoodRasti/SUnCNN.

Downloads

  • Secondary publication expected

Permalink: https://www.hzdr.de/publications/Publ-33616
Publ.-Id: 33616


OptFus: Optical Sensor Fusion For The Classification of Multi-source Data: Application to Mineralogical Mapping

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

We propose a new fusion-based classification technique for optical multi-source remote sensing images called OptFus. OptFus is developed to merge and process optical imagery having different spatial and spectral resolutions. The spatial features are extracted using morphological filters from the RGB data containing high spatial resolution. A feature fusion technique is developed to combine all the sensor data in a subspace using a common set of representative features. Finally, the fused features are classified using a Support Vector Machine to ensure a robust supervised spectral classification. The proposed method is designed to allocate varying weights to the data from various imaging sensors in the fusion process. OptFus is applied to two multi-source optical datasets captured from geological drill-core samples. The classification accuracy demonstrates considerable improvements compared to the state-of-the-art. A Matlab implementation of OptFus is available online: https://github.com/BehnoodRasti/OptFus.

Downloads

  • Secondary publication expected

Permalink: https://www.hzdr.de/publications/Publ-33615
Publ.-Id: 33615


Testing approximations in a Kohn-Sham average-atom model

Callow, T. J.

I present some results for an average-atom model derived from first principles. In particular, I compare different choices of boundary condition and exchange-correlation functional and examine their impact on the equation-of-state data and mean ionization state.

  • Poster (Online presentation)
    41st Workshop on High-Energy-Density Physics with laser and Ion beams, 01.-05.02.2021, Hirschegg, Österreich

Permalink: https://www.hzdr.de/publications/Publ-33614
Publ.-Id: 33614


First-principles derivation of an average-atom model from the many-body Hamiltonian of coupled electrons and ions

Callow, T. J.; Hansen, S. B.; Kraisler, E.; Gross, E.; Cangi, A.

In simulations of the warm dense matter regime, it is typical to use a combined finite-temperature Kohn-Sham density-functional theory (KS-DFT) and molecular dynamics approach. However, in KS-DFT, (i) scaling worsens with increasing temperature, and (ii) temperature dependence is usually neglected in the exchange-correlation (XC) functional. We present a derivation from first-principles which reduces the full many-body Hamiltonian to an average-atom model in the dilute gas limit, which significantly reduces the computational cost of the KS-DFT calculation. We also show preliminary results including a comparison of temperature-dependent and zero-temperature XC functionals.

  • Lecture (Conference) (Online presentation)
    APS March Meeting 2021, 15.-19.03.2021, Virtual, USA

Permalink: https://www.hzdr.de/publications/Publ-33613
Publ.-Id: 33613


First-principles derivation and properties of density-functional average-atom models

Callow, T. J.

I demonstrate the key steps in a first-principles derivation of a density-functional average-atom model, and show the importance of the boundary condition used to solve the Kohn-Sham equations on results.

  • Poster
    17th International Conference on the Physics of Non-Ideal Plasmas, 20.-24.09.2021, Dresden, Deutschland

Permalink: https://www.hzdr.de/publications/Publ-33612
Publ.-Id: 33612


First-principles derivation and limitations of Kohn–Sham average-atom models

Callow, T. J.

In this talk, I present a first-principles derivation of an average-atom model, which is solved using Kohn-Sham density-functional theory. I also demonstrate the impact of various assumptions and approximations of the model, such as the boundary condition and exchange-correlation functional, on various properties such as mean ionization state. I consider some possible causes of error in the model, specifically self-interaction and density-driven errors. Finally, I introduce our new open-source average-atom code for matter under extreme conditions, atoMEC.

  • Invited lecture (Conferences)
    Average atom models for warm dense matter workshop, UC Berkeley, 28.-29.06.2021, Berkeley, USA

Permalink: https://www.hzdr.de/publications/Publ-33611
Publ.-Id: 33611


Pulse shape degradation from optical surface modulations in a spherical Öffner stretcher

Siebold, M.; Albach, D.; Hornung, M.; Löser, M.; Schramm, U.

We introduce an Öffner stretcher for the diode-pumped Petawatt laser system PENELOPE developed at the HZDR. Spectral and temporal aspects of the stretcher system with large aperture spherical mirrors (600 mm and 250 mm) are analyzed with respect to pulse shape and pulse contrast ratio.

  • Poster (Online presentation)
    Advanced Solid State Lasers (ASSL), 03.-07.10.2021, Washington, DC, USA

Permalink: https://www.hzdr.de/publications/Publ-33610
Publ.-Id: 33610


Density-functional average-atom model for first-principles simulations of warm dense matter

Callow, T. J.

The warm dense matter regime is notoriously challenging from a computational modelling perspective, since a quantum mechanical description is required for large length and time scales, at temperatures well above the ground-state. Average-atom (AA) models reduce the many-body system of interacting electrons and nuclei to an effective ‘average’ atom, with relevant properties typically computed via Kohn–Sham density-functional theory (KS-DFT): this approach has clear computational advantages relative to full ab initio KS-DFT (or alternative) simulations. However, there is some uncertainty regarding the accuracy and predictive capabilities of AA models. In this talk, I will present a first principles derivation of a KS-AA model, carefully analysing the assumptions made and terms neglected in this approach. The results obtained from our model highlight the importance of the choice of boundary conditions and the significance of the self-interaction error. I will discuss the implications of these findings for future developments in AA models.

  • Lecture (others) (Online presentation)
    AMCP seminar (atoms, molecules, clusters and plasmas), Universität Rostock, 01.06.2021, Rostock, Deutschland

Permalink: https://www.hzdr.de/publications/Publ-33609
Publ.-Id: 33609


Image Restoration for Remote Sensing: Overview and Toolbox

Rasti, B.; Chang, Y.; Dalsasso, E.; Denis, L.; Ghamisi, P.

Remote sensing provides valuable information about objects or areas from a distance in either active (e.g., RADAR and LiDAR) or passive (e.g., multispectral and hyperspectral) modes. The quality of data acquired by remotely sensed imaging sensors (both active and passive) is often degraded by a variety of noise types and artifacts. Image restoration, which is a vibrant field of research in the remote sensing community, is the task of recovering the true unknown image from the degraded observed image. Each imaging sensor induces unique noise types and artifacts into the observed image. This fact has led to the expansion of restoration techniques in different paths according to each sensor type. This review paper brings together the advances of image restoration techniques with particular focuses on synthetic aperture radar and hyperspectral images as the most active sub-fields of image restoration in the remote sensing community. We, therefore, provide a comprehensive, discipline-specific starting point for researchers at different levels (i.e., students, researchers, and senior researchers) willing to investigate the vibrant topic of data restoration by supplying sufficient detail and references. Additionally, this review paper accompanies a toolbox to provide a platform to encourage interested students and researchers in the field to further explore the restoration techniques and fast-forward the community. The toolboxes are provided in https://github.com/ImageRestorationToolbox.

Downloads

Permalink: https://www.hzdr.de/publications/Publ-33608
Publ.-Id: 33608


Dual Graph Convolutional Network for Hyperspectral Image Classification With Limited Training Samples

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

Due to powerful feature extraction capability, convolutional neural networks (CNNs) have been widely used for hyperspectral image (HSI) classification. However, because of a large number of parameters that need to be trained, sufficient training samples are usually required for deep CNN-based methods. Unfortunately, limited training samples are a common issue in the remote sensing community. In this study, a dual graph convolutional network (DGCN) is proposed for the supervised classification of HSI with limited training samples. The first GCN fully extracts features existing in and among HSI samples, while the second GCN utilizes label distribution learning, and thus, it potentially reduces the number of required training samples. The two GCNs are integrated through several iterations to decrease interclass distances, which leads to a more accurate classification step. Moreover, a new idea entitled multiscale feature cutout is proposed as a regularization technique for HSI classification (DGCN-M). Different from the regularization methods (e.g., dropout and DropBlock), the proposed multiscale feature cutout could randomly mask out multiscale region sizes in a feature map, which further reduces the overfitting problem and yields consistent improvement. Experimental results on the four popular hyperspectral data sets (i.e., Salinas, Indian Pines, Pavia, and Houston) indicate that the proposed method obtains good classification performance compared to state-of-the-art methods, which shows the potential of GCN for HSI classification.

Downloads

Permalink: https://www.hzdr.de/publications/Publ-33607
Publ.-Id: 33607


A comprehensive transferability evaluation of U-Net and ResU-Net for landslide detection from Sentinel-2 data (case study areas from Taiwan, China, and Japan)

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

Earthquakes and heavy rainfalls are the two leading causes of landslides around the world. Since they
often occur across large areas, landslide detection requires rapid and reliable automatic detection
approaches. Currently, deep learning (DL) approaches, especially different convolutional neural
network and fully convolutional network (FCN) algorithms, are reliably achieving cutting-edge
accuracies in automatic landslide detection. However, these successful applications of various DL
approaches have thus far been based on very high-resolution satellite images (e.g., GeoEye and
WorldView), making it easier to achieve such high detection performances. In this study, we use freely
available Sentinel-2 data and ALOS digital elevation model to investigate the application of two wellknown FCN algorithms, namely the U-Net and residual U-Net (or so-called ResU-Net), for landslide
detection. To our knowledge, this is the first application of FCN for landslide detection only from freely
available data. We adapt the algorithms to the specific aim of landslide detection, then train and test
with data from three different case study areas located in Western Taitung County (Taiwan), Shuzheng
Valley (China), and Eastern Iburi (Japan). We characterize three different window size sample patches
to train the algorithms. Our results also contain a comprehensive transferability assessment achieved
through different training and testing scenarios in the three case studies. The highest f1-score value of
73.32% was obtained by ResU-Net, trained with a dataset from Japan, and tested on China’s holdout
testing area using the sample patch size of 64 × 64 pixels.

Permalink: https://www.hzdr.de/publications/Publ-33606
Publ.-Id: 33606


atoMEC: Average-atom code for Matter under Extreme Conditions

Callow, T. J.; Kotik, D.; Tsvetoslavova Stankulova, E.; Kraisler, E.; Cangi, A.

atoMEC is a python-based average-atom code for simulations of high energy density phenomena such as in warm dense matter. It is designed as an open-source and modular python package. atoMEC uses Kohn-Sham density functional theory, in combination with an average-atom approximation, to solve the electronic structure problem for single-element materials at finite temperature.

  • Software in external data repository
    Publication year 2021
    Programming language: Python
    System requirements: n/a
    License: BSD 3-Clause
    Hosted on GitHub: Link to location
    DOI: 10.5281/zenodo.5772266

Permalink: https://www.hzdr.de/publications/Publ-33605
Publ.-Id: 33605


2021 Data Fusion Contest: Geospatial Artificial Intelligence for Social Good [Technical Committees]

Yokoya, N.; Ghamisi, P.; Hansch, R.; Prieur, C.; Malha, H.; Chanussot, J.; Robinson, C.; Malkin, K.; Jojic, N.

The 2021 Data Fusion Contest, organized by the Image Analysis and Data Fusion Technical Committee (IADF TC) of the IEEE Geoscience and Remote Sensing Society (GRSS), promotes research on geospatial artificial intelligence (AI) for social good. The global objective is to build models for understanding the state of and changes in artificial and natural environments from remote sensing data toward sustainable development.

Permalink: https://www.hzdr.de/publications/Publ-33604
Publ.-Id: 33604


Density functionals with spin-density accuracy for open shells

Callow, T. J.; Pearce, B.; Gidopoulos, N.

Electrons in zero external magnetic field can be studied with density functional theory (DFT) or with spin-DFT (SDFT). The latter is normally used for open shell systems because its approximations appear to model better the exchange and correlation (xc) functional, but also because so far the application of DFT implied a closed-shell-like approximation. Correcting this error for open shells allows the approximate DFT xc functionals to become as accurate as those in SDFT. In the limit of zero magnetic field, the Kohn-Sham equations of SDFT emerge as the generalised KS equations of DFT.

Related publications

Downloads

Permalink: https://www.hzdr.de/publications/Publ-33603
Publ.-Id: 33603


Global Land-Cover Mapping With Weak Supervision: Outcome of the 2020 IEEE GRSS Data Fusion Contest

Robinson, C.; Malkin, K.; Jojic, N.; Chen, H.; Qin, R.; Xiao, C.; Schmitt, M.; Ghamisi, P.; Hänsch, R.; Yokoya, N.

This article presents the scientific outcomes of the 2020 Data Fusion Contest (DFC2020) organized by the Image Analysis and Data Fusion Technical Committee of the IEEE Geoscience and Remote Sensing Society. The 2020 Contest addressed the problem of automatic global land-cover mapping with weak supervision, i.e., estimating high-resolution semantic maps while only low-resolution reference data are available during training. Two separate competitions were organized to assess two different scenarios: 1) high-resolution labels are not available at all; and 2) a small amount of high-resolution labels are available additionally to low-resolution reference data. In this article, we describe the DFC2020 dataset that remains available for further evaluation of corresponding approaches and report the results of the best-performing methods during the contest.

Permalink: https://www.hzdr.de/publications/Publ-33602
Publ.-Id: 33602


First-principles derivation and properties of density-functional average-atom models

Callow, T. J.; Hansen, S. B.; Kraisler, E.; Cangi, A.

Finite-temperature Kohn--Sham density-functional theory (KS-DFT) is a widely-used method in warm dense matter (WDM) simulations and diagnostics. Unfortunately, full KS-DFT-molecular dynamics models scale unfavourably with temperature and there remains uncertainty regarding the performance of existing approximate exchange-correlation (XC) functionals under WDM conditions. Of particular concern is the expected explicit dependence of the XC functional on temperature, which is absent from most approximations. Average-atom (AA) models, which significantly reduce the computational cost of KS-DFT calculations, have therefore become an integral part of WDM modelling. In this paper, we present a derivation of a first-principles AA model from the fully-interacting many-body Hamiltonian, carefully analysing the assumptions made and terms neglected in this reduction. We explore the impact of different choices within this model -- such as boundary conditions and XC functionals -- on common properties in WDM, for example equation-of-state data, ionization degree and the behaviour of the frontier energy levels. Furthermore, drawing upon insights from ground-state KS-DFT, we discuss the likely sources of error in KS-AA models and possible strategies for mitigating such errors.

Related publications

Downloads

Permalink: https://www.hzdr.de/publications/Publ-33601
Publ.-Id: 33601


Recent progress on advanced photocathodes for SC RF guns

Xiang, R.

Recent progress on advanced photocathodes for superconducting RF guns. We will together view the achievements as well as open questions for the reliable gun operation.

Keywords: SRF gun; photocathode

Related publications

  • Open Access Logo Invited lecture (Conferences) (Online presentation)
    Photocathode Physics for Photoinjectors 2021, 10.-12.11.2021, virtual format, USA
  • Open Access Logo Invited lecture (Conferences) (Online presentation)
    Snowmass Electron Source workshop, 16.-18.02.2022, virtual format, USA

Downloads

Permalink: https://www.hzdr.de/publications/Publ-33600
Publ.-Id: 33600


NAM: Normalization-based Attention Module

Liu, Y.; Shao, Z.; Teng, Y.; Hoffmann, N.

Recognizing less salient features is the key for model compression. However, it has not been investigated in the revolutionary attention mechanisms. In this work, we propose a novel normalization-based attention module (NAM), which suppresses less salient weights. It applies a weight sparsity penalty to the attention modules, thus, making them more computational efficient while retaining similar performance. A comparison with three other attention mechanisms on both Resnet and Mobilenet indicates that our method results in higher accuracy. Code for this paper can be publicly accessed at https://github.com/Christian-lyc/NAM.

Keywords: Attention; Normalization; ResNet; MobileNet; Deep Learning; ImageNet; CIFAR-100

  • Open Access Logo Contribution to proceedings
    35th Conference on Neural Information Processing Systems (NeurIPS 2021), Sydney, Australia., 14.12.2021, Sydney, Australia

Downloads

Permalink: https://www.hzdr.de/publications/Publ-33599
Publ.-Id: 33599


Time Lapse 3D Imaging of Mineral Dissolution

Winardhi, C. W.; Da Assuncao Godinho, J. R.; Gutzmer, J.; Frisch, G.

Kinetics and efficiency of mineral dissolution of multi-phase rocks depend on the properties of the mineral assemblage, the fluid composition and the environment (e.g. temperature, fluid velocity at the surface). Links between the different effects can be studied by reactive transport simulations, although the input of experimentally obtained parameters is not always intuitive and its accuracy depends on the type of experiment. Using gold ore leaching with deep eutectic solvents as an example, we present an in-situ experimental setup to image in 3D the changes of the solid phases during mineral dissolution using laboratory X-Ray computed tomography (CT). Our new approach allows measuring the volume and surface area at different dissolution times, which are used to calculate the dissolution rate spectra for different mineral phases and to study the kinetics of the dissolution process. Additionally, the 3D model of the dissolving solid imaged by CT allows direct surface extraction for fluid flow simulations, which are used to investigate the effect of fluid velocity on the dissolution rate spectra. Altogether, our method can be used to study complex geochemical mineral – fluid interactions and to directly capture the link between different factors that affect dissolution, e.g.rate spectra and flow, which traditionally can only be studied by an indirect combination of experimental methods and modelling.

Keywords: Computed Tomography (CT); Dissolution rate; Deep Eutectic Solvents; Time Lapse

  • Open Access Logo Lecture (Conference) (Online presentation)
    Goldschmidt 2021, 04.-09.07.2021, Lyon, France
    DOI: 10.7185/gold2021.3202

Permalink: https://www.hzdr.de/publications/Publ-33598
Publ.-Id: 33598


Modular Multi-Modal Attention Network for Alzheimer’s Disease Detection Using Patient Audio and Language Data

Wang, N.; Cao, Y.; Hao, S.; Shao, Z.; Subbalakshmi, K. P.

In this work, we propose a modular multi-modal architecture to automatically detect Alzheimer’s disease using the dataset provided in the ADReSSo challenge. Both acoustic and text-based features are used in this architecture. Since the dataset provides only audio samples of controls and patients, we use Google cloud-based speech-to-text API to automatically transcribe the audio files to extract text-based features. Several kinds of audio features are extracted using standard packages. The proposed approach consists of 4 networks: C-attention-acoustic network (for acoustic features only), C-Attention-FT network (for linguistic features only), C-Attention-Embedding network (for language embeddings and acoustic embeddings), and a unified network (uses all of those features). The architecture combines attention networks and a convolutional neural network (CAttention network) in order to process these features. Experimental results show that the C-Attention-Unified network with Linguistic features and X-Vector embeddings achieves the best accuracy of 80.28% and F1 score of 0.825 on the test dataset.

Keywords: Alzheimer’s disease; Multi-Modal Approach; CNN-Attention network; Acoustic feature; Linguistic feature

  • Open Access Logo Contribution to proceedings
    INTERSPEECH 2021, 30.08.2021, Brno, Czech Republic
    Alzheimer's Dementia Recognition through Spontaneous Speech The ADReSSo Challenge

Downloads

Permalink: https://www.hzdr.de/publications/Publ-33597
Publ.-Id: 33597


3-dimensional distribution of ore minerals from the Au-U Witwatersrand Supergroup using spectral X-ray computed micro tomography

Sittner, J.; Da Assuncao Godinho, J. R.; Renno, A.; Cnudde, V.; Merkulova, M.; Guy, B. M.; Boone, M.; de Schryver, T.; van Loo, D.; Roine, A.; Liipo, J.

The Witwatersrand Supergroup in South Africa is not only the best-preserved sequence of Archean sedimentary rocks but also hosts the largest gold deposit on earth, yet discovered. The gold is situated in quartz-pebble conglomerates and is generally associated with a wide variety of minerals, including pyrite (FeS2), uraninite (UO2), pyrobitumen, base metal sulfides and phyllosilicates. Despite extensive research over the past 100 years, the origin of the gold is still debated with two models receiving most of the attention: the modified paleoplacer model and the hydrothermal models. The modified paleoplacer model assumes that detrital gold was transported into the host rock by fluvial processes, followed by a short-range mobilization (micrometer- to meter scale) by hydrothermal fluids that infiltrated the host rock. In the hydrothermal model, gold was introduced into the host rock by postdepositional hydrothermal fluids from an external source.
To find new evidence for the origin of gold, we present new high-resolution 3-dimensional (3D) data based on the combination of X-ray computed micro tomography (micro-CT) and spectral X-ray computed micro tomography (Sp-CT). We combine both imaging techniques as micro-CT is an excellent tool for high resolution structural characterization and Sp-CT has the power to chemically identify a selection of minerals relevant in this study. Sp-CT is based on the analysis of X-ray absorption spectra, in particular specific K-edges, which assists in identification of chemical elements in a sample. Since most of the previous research of the Witwatersrand gold focus on 2-dimensional methods, the outcomes of this study will help to understand the 3D spatial and size distribution of the gold and provide morphological information about individual particles.
This research has received funding from the European Institute of Innovation and Technology (EIT). This body of the European Union receives support from the European Union's Horizon 2020 research and innovation program.

  • Lecture (Conference) (Online presentation)
    Goldschmidt 2021, 04.-09.07.2021, Online, Online

Permalink: https://www.hzdr.de/publications/Publ-33596
Publ.-Id: 33596


Spectral X-ray computed micro tomography: a tool for 3-dimensional chemical imaging

Sittner, J.; Merkulova, M.; Da Assuncao Godinho, J. R.; Renno, A.; Cnudde, V.; Boone, M.; de Schryver, T.; van Loo, D.; Roine, A.; Liipo, J.; Dewaele, S.; Guy, B. M.

Image-based analytical tools in geosciences are indispensable for the characterization of minerals, but most of them are limited to the surface of a polished plane in a sample and lack 3D information. X-ray micro computed tomography (micro CT) provides the missing 3D information of the microstructures inside samples. However, a major drawback of micro CT in the characterization of minerals is the lack of chemical information that makes mineral classification challenging.
Spectral X-ray micro computed tomography (Sp-CT) is a new and evolving tool in different applications such as medicine, security, material science, and geology. This non-destructive method uses a multi-pixel photon-counting detector (PCD) such as cadmium telluride (CdTe) in combination with a conventional CT scanner (TESCAN CoreTOM) to image a sample and detect its transmitted polychromatic X-ray spectrum. Based on the spectrum, elements in a sample can be identified by an increase in attenuation at specific K-edge energies. Therefore, chemically different particles can be distinguished inside a sample from a single CT scan. The method is able to distinguish elements with K-edges in the range from 25 to 160 keV, which applies to elements with Z > 48.
We present results from various sample materials. Different pure elements and element oxides were measured to compare the position of theoretical and measured K-edge energies. All measured K-edge energies are slightly above the theoretical value, but based on the results a correction algorithm could be developed. Furthermore, different monazite grains were investigated, which can be divided into two groups with respect to the content of different RE elements on the basis of the spectrum: La-Ce-rich and La-Ce-poor. In addition, samples from the Au-U Witwatersrand Supergroup demonstrate the potential applications of Sp-CT for geological samples. We measured different drill core samples from the Kalkoenkrans Reef at the Welkom Gold field. Sp-CT can distinguish gold, uraninite and galena grains based on their K-edge energies in the drill core without preparation.

  • Lecture (Conference) (Online presentation)
    European Geoscience Union (EGU) 2021, 19.-30.04.2021, Online, Online

Permalink: https://www.hzdr.de/publications/Publ-33595
Publ.-Id: 33595


Spectral X-ray computed micro-tomography: towards 3-dimensional ore characterization

Sittner, J.; Guy, B. M.; Da Assuncao Godinho, J. R.; Renno, A.; Cnudde, V.; Merkulova, M.; Boone, M.; de Schryver, T.; van Loo, D.; Roine, A.; Liipo, J.

Most ore characterization studies are based on analytical tools that are limited to a 2-dimensional (2D) surface of a 3-dimensional (3D) sample. This not only limits the number of particles available for analysis but also results in a lack of 3D morphological information. Especially for the characterization of trace phases, 2D analysis is time consuming. X-ray computed micro-tomography (micro-CT) represents an established 3D technique that is used in numerous applications such as medicine, material science, biology, and geoscience. However, a major drawback of micro-CT in the characterization of ores is the absence of chemical information, which makes mineral classification challenging.
Therefore, we present Spectral X-ray computed micro-tomography (Sp-CT). It is an evolving technique in different research fields and is based on a semiconductor detector that provides chemical information of a sample (e.g., CdTe). This detector can be used with a conventional CT scanner (TESCAN CoreTOM in this study) to image a sample and detect its transmitted polychromatic X-ray spectrum. Based on the spectrum, elements in a sample can be identified by an increase in attenuation at specific absorption edge energies. Therefore, chemically different minerals can be distinguished inside a sample from a single CT scan in the micrometer range. The method is able to distinguish elements with absorption edges in the range from 25 to 160 keV, which applies to elements with Z > 48.
We present the workflow of an ore characterization study using a combination of Sp-CT and high-resolution micro-CT with an example of Au-U ore from the Witwatersrand Supergroup. Different drill core samples from the Kalkoenkrans Reef at the Welkom Gold field were investigated. With the chemical information from the Sp-CT, minerals such as gold, U-phases, and galena can be identified based on their K-edge energies in the spectrum. Several Sp-CT scans were used to train a machine learning segmentation model in the software Dragonfly (version 2021.1) to segment the high-resolution CT data into multiple segments, e.g., gold, U-minerals, sulfide minerals and matrix minerals. The segmented data was then used to extract 3D mineral properties of the segments such as 3D volume or 3D surface area. This new non-destructive approach provides 3D information on distribution of chemically different minerals without any sample preparation. This information can be used for mineral processing simulations but also for genetic mineralogical studies.

  • Open Access Logo Lecture (Conference) (Online presentation)
    3rd European Mineralogical Conference, 29.08.-02.09.2021, Cracow, Poland

Permalink: https://www.hzdr.de/publications/Publ-33594
Publ.-Id: 33594


A particle-based approach to predict the success and selectivity of leaching processes

Winardhi, C. W.; Da Assuncao Godinho, J. R.; Rachmawati, C.; Duhamel Achin, I.; Unzurrunzaga Iturbe, A.; Frisch, G.; Gutzmer, J.

Encouraged by the need for ecologically and economically sustainable technologies for the recovery of metals from complex raw materials, ionometallurgical leaching using deep eutectic solvents is emerging as a promising alternative to conventional hydro- and pyrometallurgy for metal recovery. Current approaches of studying leaching processes do not provide a mineral-based understanding of the leaching process – thus limiting the opportunities for process optimization. This study addresses this shortcoming by combining laboratory-based X-ray computed tomography (CT) and scanning electron microscopy-based image analysis. The latter method provides robust information on the mineralogy and texture of the leach feed material, whereas CT is used to observe the progress of the leaching process through time. Leaching of a Au-Ag bearing sulfide flotation concentrate by deep eutectic solvent ethaline with iodine as oxidizing agent is used as a relevant case study. Results show that time lapsed CT provides an accurate estimation of the dissolution rate of pyrite, chalcopyrite, galena, telluride minerals and gold. Dissolution rates were used then to simulate metal recoveries from the mineral concentrate as a function of leaching time. Simulation results are within 5% variation of recoveries obtained by batch leaching experiments. The developed workflow can be easily transferred to other mineral concentrates or ore types; results may be used to optimize industrial leaching process.

Keywords: Computed Tomography (CT); Dissolution rates; Deep Eutectic Solvents; Leaching; Particle-based leaching simulation

Related publications

Permalink: https://www.hzdr.de/publications/Publ-33593
Publ.-Id: 33593


Modeling the effect of the national borders in the spread of COVID-19: A case study of the Saxony-Czechia border region

Mertel, A.; Calabrese, J.

COVID-19 serves as an opportunity to apply scientific methodologies from various fields to better understand the nature of the spread. In this paper, we are specifically looking into the effect of the presence/absence of national borders on the spread of the disease. We work with the dataset aggregated from the seven-day incidence in the municipalities in Saxony, and Czechia. We further apply the regression model, where a metric to estimate the potential causality of incidence growth in each of two municipalities is dependent on the distance between them, their population ratio, and the existence of the national border. Our preliminary results showed that the effect of the borders is very strong in most of the study areas.

Keywords: COVID-19; epidemiological modeling; spatial regression model; border effect

  • Lecture (Conference)
    International Symposium on Geospatial Approaches to Combating Covid-19, 13.12.2021, Florence, Italien

Permalink: https://www.hzdr.de/publications/Publ-33592
Publ.-Id: 33592


Spectral X-Ray Computed Micro Tomography: 3-Dimensional Chemical Imaging by Using a Pixelated Semiconductor Detector

Sittner, J.; Merkulova, M.; Da Assuncao Godinho, J. R.; Renno, A.; Cnudde, V.; Boone, M.; de Schryver, T.; van Loo, D.; Roine, A.; Liipo, J.; Guy, B. M.

We present a new approach to 3-dimensional (3D) chemical imaging based on X-ray computed micro tomography (micro-CT), which enables the analysis of the internal elemental chemistry. The method uses a conventional laboratory-based micro-CT scanner (Tescan CoreTOM) equipped with a cadmium telluride (CdTe) semiconductor line detector (Tescan PolyDet). Based on the X-ray absorption spectra, elements in a sample can be distinguished by their specific K-edge energy. The capabilities and performance of this approach are illustrated with different experiments. We present results from various sample materials (e.g., pure element reference samples, mineral mixtures and rocks). Different pure elements and element oxides were measured to compare positions of the theoretical K-edge energy with the measured one. Furthermore, we show the results of a particle mixture with quartz as a low-absorbing matrix. Finally, samples of the Au-U Witwatersrand Supergroup demonstrate the possibilities this approach for geological samples. All results show that the method can distinguish elements with K-edges in the range of 25–160 keV. This corresponds to elements with Z > 48 (Cd). Moreover, the spectral information allows a distinction between materials, which show little to no X-ray attenuation variation in the reconstructed CT image.

  • Book chapter
    Jan S. Iwanczyk; Krzysztof Iniewski: Radiation Detection Systems - Medical Imaging, Industrial Testing and Security Applications, Boca Raton: CRC Press, 2021, 9781003218364, 1-28
    DOI: 10.1201/9781003218364

Permalink: https://www.hzdr.de/publications/Publ-33591
Publ.-Id: 33591


Prognostic Value of Pretherapeutic Primary Tumour MTV from [18F]FDG PET in Radically Treated Cervical Cancer Patients

Cegla, P.; Hofheinz, F.; CholewińSki, W.; Czepczynski, R.; Kubiak, A.; van den Hoff, J.; Bos-Liedke, A.; Roszak, A.; Ewa Burchardt, E.

The aim of this study was to assess the usefulness of pretherapeutic primary tumor
metabolic tumor volume (MTV) in the prognosis of radically treated cervical cancer patients. Ret-
rospective, single-centre analysis was performed on a group of 508 cervical cancer patients. All
patients underwent a pretreatment [18 F]FDG PET/CT study for the assessment of the disease stage.
Several PET-derived parameters—namely, maximum standardized uptake value (SUVmax ), mean
standardized uptake value (SUVmean ), total lesion glycolysis (TLG) and MTV, as well as the clinical
parameters, were analysed in terms of the overall survival (OS), event-free survival (EFS), locore-
gional control (LRC) and freedom from distant metastases (FFDM). Hyperthermia and brachytherapy
were prognostic for EFS, OS, and LRC.FIGO stage > II showed a significant effect on EFS, OS, and
FFDM. Moreover, hysterectomy was prognostic for OS and histology was prognostic for FFDM. From
the PET-derived parameters only MTV of the primary tumour had a significant influence on OS
(cutoff point: >12.7 mL, HR: 2.8, 1.75–4.48 95% CI, p < 0.001), LRC (cutoff point: >13.7 mL, HR 2.82,
1.42–5.61 95% CI, p = 0.003), EFS (cutoff point: >10.4 mL, HR: 2.57, 1.67–3.97 95% CI, p < 0.001) and
FFDM (cutoff point: >10.4 mL, HR: 5.04, 1.82–13.99 95% CI, p = 0.002). The pretreatment of MTV
in primary tumour is the only independent prognostic parameter in OS, LRC, EFS, and FFDM in
radically treated cervical cancer patients and should be used in clinical practice in assessing prognosis

Keywords: positron emission tomography/computed tomography; cervical cancer; [18 F]FDG; metabolic parameters

Permalink: https://www.hzdr.de/publications/Publ-33590
Publ.-Id: 33590


16O(n,α) and nat-Fe transmission experiments at GELINA & nELBE

Beyer, R.; Fan, X.; Junghans, A. R.; Kögler, T.; Stach, D.; Urlass, S.; Göök, A.; Heyse, J.; Kopecky, S.; Paradela, M.; Plompen, A. J. M.; Schillebeeckx, P.; Tassan-Got, L.; Leal, L.; Capote, R.; Deboer, R.; Wiescher, M.; Nyman, M.

Vortrag bei der JEFF Nuclear Data Week November 2021, JEF-DOC 2071

Related publications

  • Invited lecture (Conferences) (Online presentation)
    JEFF Nuclear Data Week, 22.-26.11.2021, Paris, France

Permalink: https://www.hzdr.de/publications/Publ-33588
Publ.-Id: 33588


GeoStat-Examples/gstools-herten-example: v1.0

Schüler, L.; Müller, S.

We are going to analyse the Herten aquifer, which is situated in Southern Germany. Multiple outcrop faces where surveyed and interpolated to a 3D dataset.

Related publications

  • Software in external data repository
    Publication year 2021
    Programming language: Python
    System requirements: Same as GSTools
    License: MIT
    Hosted on GitHub: Link to location
    DOI: 10.5281/zenodo.5159657

Permalink: https://www.hzdr.de/publications/Publ-33587
Publ.-Id: 33587


GeoStat-Framework/GSTools: v1.3.2 'Pure Pink'

Müller, S.; Schüler, L.

GeoStatTools provides geostatistical tools for various purposes:

  • random field generation
  • simple, ordinary, universal and external drift kriging
  • conditioned field generation
  • incompressible random vector field generation
  • (automated) variogram estimation and fitting
  • directional variogram estimation and modelling
  • data normalization and transformation
  • many readily provided and even user-defined covariance models
  • metric spatio-temporal modelling
  • plotting and exporting routines

Keywords: python; statistics; geospatial; geostatistics; kriging; variogram; spatio-temporal; srf; covariance

Related publications

  • Software in external data repository
    Publication year 2021
    Programming language: Python
    System requirements: Requirements: NumPy >= 1.14.5 SciPy >= 1.1.0 hankel >= 1.0.2 emcee >= 3.0.0 pyevtk >= 1.1.1 meshio>=4.0.3, <5.0 Optional GSTools-Core >= 0.2.0 matplotlib pyvista
    License: LGPLv3 (Link to license text)
    Hosted on GitHub: Link to location
    DOI: 10.5281/zenodo.1313628

Permalink: https://www.hzdr.de/publications/Publ-33586
Publ.-Id: 33586


Data publication: DNA-Mediated Stack Formation of Nanodiscs

Subramanian, M.; Kielar, C.; Tsushima, S.; Fahmy, K.; Oertel, J.

The recent publication showed the DNA-mediated stack formation of nanodiscs. Background: Membrane-scaffolding proteins (MSPs) become a versatile tool in generating nano-sized discoidal membrane mimetics (nanodiscs) for membrane protein research. We describe here the formation of multimers of membrane-scaffolding protein MSP1D1-bounded nanodiscs using the thiol reactivity of engineered cysteines. The mutated positions N42 and K163 in MSP1D1 were chosen to support chemical modification as evidenced by fluorescent labeling with pyrene. The direct disulphide bond formation of nanodiscs formed by the MSP1D1_N42C variant led to dimers and trimers with low yield. In contrast, transmission electron microscopy revealed that the attachment of oligonucleotides to the engineered cysteines of MSP1D1 allowed the growth of submicron-sized tracts of stacked nanodiscs through the hybridization of nanodisc populations carrying complementary strands and a flexible spacer.

Keywords: membrane-scaffolding protein; nanodisc; membrane protein; lipid bilayer; lipid protein interaction; multimerization; self-assembly; bionanotechnology

Related publications

Downloads

Permalink: https://www.hzdr.de/publications/Publ-33585
Publ.-Id: 33585


Self-Supervised Learning With Adaptive Distillation for Hyperspectral Image Classification

Yue, J.; Fang, L.; Rahmani, H.; Ghamisi, P.

Hyperspectral image (HSI) classification is an important topic in the community of remote sensing, which has a wide range of applications in geoscience. Recently, deep learning-based methods have been widely used in HSI classification. However, due to the scarcity of labeled samples in HSI, the potential of deep learning-based methods has not been fully exploited. To solve this problem, a self-supervised learning (SSL) method with adaptive distillation is proposed to train the deep neural network with extensive unlabeled samples. The proposed method consists of two modules: adaptive knowledge distillation with spatial–spectral similarity and 3-D transformation on HSI cubes. The SSL with adaptive knowledge distillation uses the self-supervised information to train the network by knowledge distillation, where self-supervised knowledge is the adaptive soft label generated by spatial–spectral similarity measurement. The SSL with adaptive knowledge distillation mainly includes the following three steps. First, the similarity between unlabeled samples and object classes in HSI is generated based on the spatial–spectral joint distance (SSJD) between unlabeled samples and labeled samples. Second, the adaptive soft label of each unlabeled sample is generated to measure the probability that the unlabeled sample belongs to each object class. Third, a progressive convolutional network (PCN) is trained by minimizing the cross-entropy between the adaptive soft labels and the probabilities generated by the forward propagation of the PCN. The SSL with 3-D transformation rotates the HSI cube in both the spectral domain and the spatial domain to fully exploit the labeled samples. Experiments on three public HSI data sets have demonstrated that the proposed method can achieve better performance than existing state-of-the-art methods.

Downloads

Permalink: https://www.hzdr.de/publications/Publ-33584
Publ.-Id: 33584


SNG based energy storage systems with subsurface CO₂ storage

Fogel, S.; Yeates, C.; Unger, S.; Rodriguez Garcia, G.; Baetcke, L.; Dornheim, M.; Schmidt-Hattenberger, C.; Bruhn, D.; Hampel, U.

Large-scale energy storage plants based on power-to-gas-to-power technologies incorporating high temperature electrolysis, catalytic methanation of H₂ and CO₂ and novel, highly efficient methane-fired Allam reconversion cycles allow for a confined and circular use of CO₂ and thus an emission-free storage of intermittent renewable energy. The Allam power cycle is considered as a beneficial power plant concept, which employs supercritical CO₂ as working fluid as well as an oxy-combustion process to reach high efficiencies of up to 66%. The combination of said process chain could reach a maximum roundtrip efficiency of 54.2 % assuming the presence of sufficient storage capacities for all relevant technical gases. In a technically feasible scenario, paired with a separate air separation unit instead of stationary O₂ storages, roundtrip efficiencies of 49.0 % were determined..
The implementation of said energy storage systems into existing national energy systems will pose a major challenge, since they will require far-reaching infrastructural changes to the respective systems itself, such as extensive installations of renewable generation and electrolysis capacities as well as sufficient subsurface storage capacities for both CO₂ and CH₂. Furthermore, an exemplary energy system forecast for Germany for the year of 2050 is presented to show the viability of the energy storage concept. In case of a fully circular use of CO₂, when electricity is solely generated by renewable energy sources (RES), 736 GW of RES, 234 GW of electrolysis and 62 GW of gas-to-power capacities are required. The total storage volume on the national scale of Germany for both CO₂ and CH₄ was determined to be 7.8 billion Nm³, respectively, leading to a CH₄ storage capacity of 54.5 TWh. The present investigation illustrates the feasibility of large-scale energy storage systems for renewable electricity based on high temperature electrolysis, catalytic methanation and Allam power cycles paired with large subsurface storages for CO₂ and CH₄.

Keywords: CCUS; CCU; Methanation; SOEC; Subsurface CO₂ storage; sCO₂ power cycles; Carbon loop; Hydrogen storage

Permalink: https://www.hzdr.de/publications/Publ-33583
Publ.-Id: 33583


Unravelling the secrets of laser plasma particle (ion) acceleration with x-rays from the European XFEL

Schramm, U.

Invited plenary presentation on:

Unravelling the secrets of laser plasma particle (ion) acceleration with x-rays from the European XFEL

Keywords: XFEL; laser plasma

Related publications

  • Invited lecture (Conferences)
    HIBEF Inauguration Festakt, 31.08.2021, Hamburg Schenefeld, Deutschland

Permalink: https://www.hzdr.de/publications/Publ-33582
Publ.-Id: 33582


Unsupervised Deep Learning for Landslide Detection from Multispectral Sentinel-2 Imagery

Shahabi, H.; Maryam, R.; Sepideh, T. P.; Omid, G.; Saied, H.; Thomas, B.; Samsung, L.; Ghamisi, P.

This paper proposes a new approach based on an unsupervised deep learning (DL) model for landslide detection. Recently, supervised DL models using convolutional neural networks (CNN) have been widely studied for landslide detection. Even though these models provide robust performance and reliable results, they depend highly on a large labeled dataset for their training step. As an alternative, in this paper, we developed an unsupervised learning model by employing a convolutional auto-encoder (CAE) to deal with the problem of limited labeled data for training. The CAE was used to learn and extract the abstract and high-level features without using training data. To assess the performance of the proposed approach, we used Sentinel-2 imagery and a digital elevation model (DEM) to map landslides in three different case studies in India, China, and Taiwan. Using minimum noise fraction (MNF) transformation, we reduced the multispectral dimension to three features containing more than 80% of scene information. Next, these features were stacked with slope data and NDVI as inputs to the CAE model. The Huber reconstruction loss was used to evaluate the inputs. We achieved reconstruction losses ranging from 0.10 to 0.147 for the MNF features, slope, and NDVI stack for all three study areas. The mini-batch K-means clustering method was used to cluster the features into two to five classes. To evaluate the impact of deep features on landslide detection, we first clustered a stack of MNF features, slope, and NDVI, then the same ones plus with the deep features. For all cases, clustering based on deep features provided the highest precision, recall, F1-score, and mean intersection over the union in landslide detection.

Permalink: https://www.hzdr.de/publications/Publ-33581
Publ.-Id: 33581


High dose-rate in-vivo proton irradiation at DRACO-PW, pilot study results and prerequisites

Schramm, U.

invited talk on "High dose-rate in-vivo proton irradiation at DRACO-PW, pilot study results and prerequisites"

Keywords: laser proton acceleration

Related publications

  • Invited lecture (Conferences) (Online presentation)
    SPIE 2021 ALPA Workshop, 19.-22.04.2021, Prag, Tschechien
  • Invited lecture (Conferences) (Online presentation)
    47th Conference on Plasma Physics - Satellite Meeting Laser-driven particle and radiation sources for application (LASA), 28.-29.06.2021, Barcelona, Spanien
  • Invited lecture (Conferences) (Online presentation)
    ELI Beamlines user conference 2021, 20.-21.10.2021, Prag, Tschechien
  • Invited lecture (Conferences)
    INANOTHERAD International Meeting, 15.-17.11.2021, Orsay, Frankreich
  • Invited lecture (Conferences) (Online presentation)
    42nd Int. Workshop on High-Energy-Density Physics with Intense Ion and Laser Beams, 31.01.-03.02.2022, Hirschegg, Österreich
  • Invited lecture (Conferences)
    Disruptive technologies for proton/ion oncology workshop, 28.04.2022, Oxford, UK

Permalink: https://www.hzdr.de/publications/Publ-33580
Publ.-Id: 33580


Remote Sensing Image Scene Classification via Label Augmentation and Intra-Class Constraint

Xie, H.; Chen, Y.; Ghamisi, P.

In recent years, many convolutional neural network (CNN)-based methods have been proposed to address the scene classification tasks of remote sensing images. Since the number of training samples in RS datasets is generally small, data augmentation is often used to expand the training set. It is, however, not appropriate when original data augmentation methods keep the label and change the content of the image at the same time. In this study, label augmentation (LA) is presented to fully utilize the training set by assigning a joint label to each generated image, which considers the label and data augmentation at the same time. Moreover, the output of images obtained by different data augmentation is aggregated in the test process. However, the augmented samples increase the intra-class diversity of the training set, which is a challenge to complete the following classification process. To address the above issue and further improve classification accuracy, Kullback–Leibler divergence (KL) is used to constrain the output distribution of two training samples with the same scene category to generate a consistent output distribution. Extensive experiments were conducted on widely-used UCM, AID and NWPU datasets. The proposed method can surpass the other state-of-the-art methods in terms of classification accuracy. For example, on the challenging NWPU dataset, competitive overall accuracy (i.e., 91.05%) is obtained with a 10% training ratio.

Permalink: https://www.hzdr.de/publications/Publ-33579
Publ.-Id: 33579


The impact of high hydrostatic pressure maintenance after high-pressure torsion on phenomena during high hydrostatic pressure annealing

Krawczynska, A. T.; Kerber, M.; Suchecki, P.; Romelczyk-Baishya, B.; Liedke, M. O.; Butterling, M.; Hirschmann, E.; Wagner, A.; Lewandowska, M.; Setman, D.

The impact of high hydrostatic pressure release after high-pressure torsion on subsequent high hydrostatic pressure annealing was analyzed by performing experiments on nanostructured Ni. Ni was deformed by high-pressure torsion at a pressure of 6GPa in 5 turns. Directly after deformation, the pressure was reduced to 2GPa, and under 2GPa annealing at 400 °C was conducted for 5 min. For comparison, samples were also annealed under 2GPa after deformation without loading between processes. Microhardness measurements, detailed microscopy observations and positron annihilation spectroscopy investigations were performed to elucidate the changes in the microstructures obtained after different processing routes. It is demonstrated that the pressure applied between deformation and high hydrostatic pressure annealing caused an increase in microhardness by 20% in comparison with pressure realize. Moreover, the pressure applied had an impact on the vacancy concentration, and consequently on the microstructure, leading to a smaller average grain size and a more heterogenous microstructure in terms of grain size, leaving space for optimizing the strength-ductility balance.

Keywords: high hydrostatic pressure; Ni; nickel; deformation; positron annihilation spectroscopy

Related publications

Downloads

Permalink: https://www.hzdr.de/publications/Publ-33578
Publ.-Id: 33578


Experimentelle und numerische Untersuchung der Aufschlusszerkleinerung von Multi-Material-Strukturen zur Abschätzung der Recyclingfähigkeit

Heibeck, M.; Richter, J.; Rudolph, M.; Hornig, A.; Modler, N.; Reuter, M.; Filippatos, A.

Im Rahmen einer ressourceneffizienten Kreislaufwirtschaft (engl. Circular Economy) hat das Recycling von Produkten am Ende ihrer Lebenszyklen das Potenzial, den Ressourcenverbrauch und klimaschädliche Umweltauswirkungen von Produktsystemen zu verringern. Für eine nachhaltige Etablierung von Recycling-Lösungen sind neben der Recyclingindustrie auch Produkthersteller bereits in der Konstruktionsphase mit einzubeziehen. Hierfür fehlt es derzeit jedoch meist an Methoden, um die Auswirkungen von Designentscheidungen auf die Recyclingfähigkeit abzuschätzen und zu optimieren (engl. Design-for-Recycling). Deshalb arbeiten wir an einem digitalen Modell, das die Bewertung der Recyclingfähigkeit schon im Produktentstehungsprozess ermöglichen soll. Ein besonderer Fokus liegt dabei auf dem Prozessschritt der Aufschlusszerkleinerung, da eine zunehmende Anzahl von Produkten, von Fahrzeugen bis Haushaltsgeräten, aus Multi-Material Strukturen bestehen. Hier müssen Verbindungen zwischen unterschiedlichen Materialien im Recycling meist wieder gelöst werden, um hohe Recyclingraten für alle verbauten Materialien zu erzielen. Dies erfolgt typischerweise mechanisch durch Zerkleinerungsprozesse.
Vor diesem Hintergrund wollen wir herausfinden, welche Parameter bereits während der Bauteilentwicklung beeinflussbar sind, um den Materialaufschluss bei der mechanischen Aufbereitung zu optimieren, ohne dabei Funktion und Lebensdauer der Struktur in der Nutzungsphase zu beeinträchtigen. Dazu haben wir zum einen Zerkleinerungsexperimente von Prüfkörpern aus der Automobilbranche in einem Rotorreißer durchgeführt. Im Mittelpunkt der Untersuchungen stand dabei insbesondere der Einfluss verschiedener Verbindungscharakteristika auf das Aufschlussverhalten. Da die experimentelle Datenerhebung aufgrund hoher Parametervariabilität im Produktdesign und des Zerkleinerungsprozesses aufwändig ist, entwickeln wir zum anderen ein physikalisch basiertes, numerisches Modell der Aufschlusszerkleinerung mithilfe der Finiten Elemente Methode. Hierzu nutzen wir die Software LS-DYNA, verwenden darin Materialmodelle, welche die Plastizität und das Versagen der beteiligten Werkstoffe sowie deren Interfaces berücksichtigen. Zudem wird die Simulation für verschiedene Lastfälle parametrisiert, wie beispielsweise unterschiedliche Orientierungen des Prüfkörpers im Rotorreißer. Neben dem experimentellen zeigen wir erste numerische Ergebnisse der Berechnungen am Beispiel einer Metall-Kunststoff-Hybridstruktur. Damit leistet unsere Arbeit einen Beitrag dazu, den Einfluss von Konstruktionsentscheidungen auf das Aufschlussverhalten abzuschätzen, sowie Erfahrungen bei der Erstellung einer durchgängigen digitalen Kette vom Design über Fertigung bis hin zum Recycling zu sammeln.

  • Lecture (Conference)
    Tagung Aufbereitung und Recycling, 11.-12.11.2021, Freiberg, Deutschland

Permalink: https://www.hzdr.de/publications/Publ-33577
Publ.-Id: 33577


Environment-induced decay dynamics of anti-ferromagnetic order in the Mott-Hubbard system

Schaller, G.; Queisser, F.; Szpak, N.; König, J.; Schützhold, R.

We study the dissipative Fermi-Hubbard model in the limit of weak tunneling and strong repulsive interactions, where each lattice site is tunnel-coupled to a Markovian fermionic bath. For cold baths at intermediate chemical potentials, the Mott insulator property remains stable and we find a fast relaxation of the particle number towards half filling. On longer time scales, we find that the anti-ferromagnetic order of the Mott-Néel ground state on bi-partite lattices decays, even at zero temperature. For zero and non-zero temperatures, we quantify the different relaxation time scales by means of waiting time distributions which can be derived from an effective (non-Hermitian) Hamiltonian and obtain fully analytic expressions for the Fermi-Hubbard model on a tetramer ring.

Keywords: Fermi-Hubbard model; local master equation; magnetic order; waiting-time distributions

Downloads

Permalink: https://www.hzdr.de/publications/Publ-33576
Publ.-Id: 33576


Contribution to recyclability estimation of multi-material structures with focus on modelling material liberation through shredding

Heibeck, M.; Rudolph, M.; Modler, N.; Reuter, M.; Filippatos, A.

Multi-material structures are usually designed into products with the aim of optimizing the operation phase, e.g. lightweight structures leading to higher energy efficiency of vehicles. However, in the recycling phase, most materials connected in multi-material structures should be liberated and separated again to enable high material recoveries. We want to contribute to estimating recyclability of multi-material structures already at the design stage by investigating material liberation through shredding. Therefore, we conducted an experimental shredding study, where we observed liberation behaviour and characterized in- and output particles. Furthermore, we are currently working on the numerical simulation of shredding processes using the Finite Element Method. In the future, we want to analyse the influence of design parameters on liberation behavior and, thereby, contribute to making more sustainable design decisions.

  • Invited lecture (Conferences) (Online presentation)
    24. Internationales Dresdner Leichtbausymposium, 17.-18.06.2021, Dresden, Deutschland

Permalink: https://www.hzdr.de/publications/Publ-33575
Publ.-Id: 33575


Investigating material liberation of multi-material structures through shredding

Heibeck, M.; Rudolph, M.; Reuter, M.; Filippatos, A.

Most products in consumables, aerospace and automotive industry are multi-material structures, which consist of materials connected through different joining techniques. Multi-material design aims for optimizing performance during production and service phase but usually does not consider the recycling. During recycling, materials combined in multi-material structures need to be liberated, i.e. disconnected, again to enable high material recoveries in subsequent recycling processes.
The goal of this study is to investigate material liberation of multi-material structures through mechanical processing, namely shredding. An experimental study is conducted where automotive A-frame-based specimens are shredded in a rotary shear. Particle analysis and characterization is supported by computer tomography. Furthermore, a first approach to model material liberation using Finite Element Method is introduced. This study is a contribution to estimating product recyclability in terms of material liberation already at the design stage, thereby supporting the design-engineer in sustainable design and product optimization.

Related publications

  • Lecture (Conference) (Online presentation)
    Sustainable Minerals ´21, 21.-24.06.2021, Falmouth, United Kingdom

Permalink: https://www.hzdr.de/publications/Publ-33574
Publ.-Id: 33574


Towards multiscale simulations for matter under extreme conditions: Building surrogate models with machine learning

Fiedler, L.; Cangi, A.

The accurate numerical treatment of matter under extreme conditions is crucial for the understanding of important physical phenomena such as radiation damage in fusion reactor walls, or planetary interiors. Yet, such simulations are unfeasible with state-of-art methods, e.g., density functional theory (DFT) if performed at large length and time scales, due to unfavorable scaling behavior. One possible route to mitigate these scaling issues are machine-learning based surrogate models; DFT data is used to calculate models that allow access to the same quantities of interest a DFT simulation would, at drastically reduced computational cost. CASUS (in cooperation with SNL and ORNL) develops a framework called "Materials Learning Algorithms" (MALA), drawing on which DFT surrogate models can easily be created and applied. Here we present an overview of MALA and recent results, such as size transferability and automated model construction.

Keywords: Density Functional Theory; Machine Learning; Surrogate Model

  • Poster (Online presentation)
    MML-Workshop 2021, 22.-24.11.2021, Darmstadt, Deutschland

Permalink: https://www.hzdr.de/publications/Publ-33573
Publ.-Id: 33573


Materials Learning Algorithms (MALA): Learning the electronic structure of materials with neural networks

Fiedler, L.; Cangi, A.; Kotik, D.

The accurate modeling of materials is a fundamental task in material science. Advanced methods such as Density Functional Theory (DFT) provide quantum chemical accuracy through explicit calculation of the electronic structure of materials, but they come at high computational costs. These computational demands are especially prohibitive in the context of dynamic investigations. Increasingly efficient implementations of DFT can only alleviate this problem to a certain degree.
Here, we present a different approach to tackle this problem. Feed-forward neural networks are trained on electronic structure data in order to replace DFT calculations at a fraction of the computational cost. Such surrogate models can be used to model matter under extreme conditions as they occur in planetary interiors or fusion reactors across multiple length and time scales.
To facilitate the training, testing, and application of DFT surrogate models, the Center for Advanced Systems Understanding develops the Materials Learning Algorithm (MALA) package as an open-source software project in collaboration with the Sandia National Laboratories and Oak Ridge National Laboratory.

Keywords: Density Functional Theory; Machine Learning; Surrogate Model

  • Lecture (Conference) (Online presentation)
    ML@HZDR Symposium 2021, 06.12.2021, Dresden, Deutschland

Permalink: https://www.hzdr.de/publications/Publ-33572
Publ.-Id: 33572


A Deep Dive into Machine Learning Density Functional Theory for Materials Science and Chemistry

Fiedler, L.; Shah, K.; Bussmann, M.; Cangi, A.

With the growth of computational resources, the scope of electronic structure simulations has increased greatly. Artificial intelligence and robust data analysis hold the promise to accelerate large-scale simulations and their analysis to hitherto unattainable scales. Machine learning is a rapidly growing field for the processing of such complex datasets. It has recently gained traction in the domain of electronic structure simulations, where density functional theory takes the prominent role of the most widely used electronic structure method. Thus, DFT calculations represent one of the largest loads on academic high-performance computing systems across the world. Accelerating these with machine learning can reduce the resources required and enables simulations of larger systems. Hence, the combination of density functional theory and machine learning has the potential to rapidly advance electronic structure applications such as in-silico materials discovery and the search for new chemical reaction pathways. We provide the theoretical background of both density functional theory and machine learning on a generally accessible level. This serves as the basis of our comprehensive review including research articles up to December 2020 in chemistry and materials science that employ machine-learning techniques. In our analysis, we categorize the body of research into main threads and extract impactful results. We conclude our review with an outlook on exciting research directions in terms of a citation analysis.

Keywords: Density Functional Theory; Machine Learning; Review Article

Related publications

Downloads

Permalink: https://www.hzdr.de/publications/Publ-33571
Publ.-Id: 33571


Structural and high-field magnetic properties of Laves phase RFe2-H hydrides

Tereshina, I. S.; Karpenkov, A. Y.; Gorbunov, D.; Doerr, M.; Tereshina-Chitrova, E. A.; Drulis, H.

The crystal structure and magnetic properties of the multicomponent compounds (Tb1−xYx)0.8Sm0.2Fe2Hz (x = 0, 0.2, 0.4, 0.6, 0.8, 1; z = 0 and 3.7) are investigated. The compounds crystallize in the MgCu2 type of structure. While the parent compounds Tb0.8Sm0.2Fe2 and Y0.8Sm0.2Fe2 are single phase, we detect 5%–8% of a second phase with a crystal structure of the PuNi3 type (space group R3m) in the alloys with 0.2 ≤ x < 0.8. Hydrogen absorption does not change the space group of the (Tb,Y,Sm)Fe2 compounds but boosts significantly the lattice parameter a. A large volume change of ΔV/V ∼ 28% upon hydrogen absorption is observed. By applying high magnetic fields up to 58 T, we observed rotations of the magnetic sublattices and hence we were able to determine the critical transition fields, H, from the ferrimagnetic to the ferromagnetic state and the inter-sublattice exchange parameter λ. The magnetic compensation occurs at x ≈ 0.6 and 0.2 in (Tb1−xYx-)0.8Sm0.2Fe2Hz at z = 0 and 3.7, respectively. While maintaining the collinear magnetic structure, the phenomenon of compensation in hydrides should be observed at x ≈ 0.4.

Downloads

Permalink: https://www.hzdr.de/publications/Publ-33570
Publ.-Id: 33570


A generalized population balance model for the simulation of polydisperse multiphase flows within the Euler-Euler framework

Lehnigk, R.

Polydisperse multiphase flows appear in a multitude of industrial processes. Depending on the application, the fluid or solid particles differ not only in size, but also with respect to other variables such as their velocity, shape, temperature, crystal structure or chemical composition. These secondary properties can significantly influence the corresponding process or the performance of the end product. An example are bubbly flows in vertical channels. The velocity vectors of the individual bubbles depend on their size, which ultimately determines the gas phase distribution in the pipe cross-section. Another example is the gas phase synthesis of ceramic powder in high temperature processes. The resulting particle aggregates are usually non-spherical due to the competition of aggregation and sintering of primary particles. The aggregate morphology affects the likelihood of collisions and the primary particle size determines the characteristics of the product powder. The evolution of property distributions within the dispersed phase can be described with the population balance equation. Its coupled solution with the governing equations of fluid flow allows to consider spatial dependencies. In the present thesis, a flexible population balance model has been developed and combined with a multifluid solver within the open source Computational Fluid Dynamics library OpenFOAM. The population balance equation is solved with the method of classes. The applied technique preserves the total mass and number of particles and allows for an arbitrary discretization of the distribution function. A new formulation that allows a direct implementation of binary breakup models with an implicitly given daughter size distribution is proposed which eliminates the need for an additional numerical integration. Further, a general approach for predicting the evolution of secondary size-conditioned properties is presented. The flexibility of the developed population balance model is demonstrated by applying it to two fundamentally different problems. First, the cocurrent flow of air and water in a vertical pipe is simulated. Predicting the development of the lateral void fraction profile is still a largely unsolved problem and requires proper modeling of several physical mechanisms. In dealing with the complexity a stepwise validation strategy is adopted, whereby the limits of each model layer are determined for a large matrix of measured superficial velocities. By employing an established model for the momentum exchange between the phases it is shown that, in the case of a nearly developed flow, especially the transition region between bubbly and slug flow can be simulated reliably. Next, using volume-averaged flow parameters, the performance of several coalescence and breakup model combinations is assessed. Promising results are obtained for some cases, albeit the models still require further development and calibration. Finally, the developing flow is simulated and it is shown that a complete model for predicting transitions between flow regimes must account for the size dependency of the bubble motion, as possible with the developed population balance model. The second application is the synthesis of titania in an aerosol reactor. The specific surface area of the aggregates is considered as a secondary property here. In combination with a constant fractal dimension their collision diameter can be modeled. The mean primary particle diameter can be inferred from it as well. The created model helps in explaining the trends observed in the experiment, which is not possible on the basis of considering merely the aggregate size distribution or using a simplified description of the reactor geometry.

Related publications

  • Doctoral thesis
    TU Dresden, 2020
    Mentor: Prof. Dr.-Ing. habil. Dr. h. c. Uwe Hampel
    127 Seiten

Permalink: https://www.hzdr.de/publications/Publ-33569
Publ.-Id: 33569


Colossal angular magnetoresistance in ferrimagnetic nodal-line semiconductors

Seo, J.; De, C.; Ha, H.; Lee, J. E.; Park, S.; Park, J.; Scurschii, I.; Choi, E. S.; Kim, B.; Cho, G. Y.; Yeom, H. W.; Cheong, S.-W.; Kim, J. H.; Yang, B.-J.; Kim, K.; Kim, J. S.

Efcient magnetic control of electronic conduction is at the heart of spintronic functionality for memory and logic applications. Magnets with topological band crossings serve as a good material platform for such control, because their topological band degeneracy can be readily tuned by spin confgurations, dramatically modulating electronic conduction. Here we propose that the topological nodal-line degeneracy of spin-polarized bands in magnetic semiconductors induces an extremely large angular response of magnetotransport. Taking a layered ferrimagnet, Mn3Si2Te6, and its derived compounds as a model system, we show that the topological band degeneracy, driven by chiral molecular orbital states, is lifted depending on spin orientation, which leads to a metal–insulator transition in the same ferrimagnetic phase. The resulting variation of angular magnetoresistance with rotating magnetization exceeds a trillion per cent per radian, which we call colossal angular magnetoresistance. Our fndings demonstrate that magnetic nodal-line semiconductors are a promising platform for realizing extremely sensitive spin- and orbital-dependent functionalities.

Permalink: https://www.hzdr.de/publications/Publ-33568
Publ.-Id: 33568


Maximum performance of an active magnetic regenerator

Benke, D.; Fries, M.; Gottschall, T.; Ohmer, D.; Taubel, A.; Skokov, K.; Gutfleisch, O.

Magnetocaloric materials change their temperature when a magnetic field is applied or removed, which allows building a magnetic cooling device. We derive an analytical expression for the maximum heat that such a material can transfer in one cooling cycle by investigating the operation of a simplified active magnetic regenerator (AMR). The model largely only depends on the adiabatic temperature change, the specific entropy change, and the temperature span between the hot and cold reservoirs. While this expression overestimates the performance of a real AMR due to its simplification, it can predict an upper limit of any AMRs’ performance independent of the implementation details. Based on this, we calculate the upper limit of the cooling power of magnetic cooling devices at any temperature span, frequency, mass, and material. This upper limit is used to predict how the thermal span is scaling with the applied magnetic field, and it can be utilized for the optimization of the magnetic field source. Additionally, we confirm that the product of isothermal entropy and adiabatic temperature change, already used in the literature, is a suitable figure of merit for magnetocaloric materials.

Permalink: https://www.hzdr.de/publications/Publ-33567
Publ.-Id: 33567


Nano- and microscaled biosensing and (de-)coding in micro- and millifluidics

Schütt, J.

Aim: Further development and improvement of disease diagnostic devices and protocols
So far: Very precise, but bulky, time-consuming and costly, trained personnel and laboratory conditions required

Keywords: Point-of-care

  • Lecture (Conference) (Online presentation)
    European Biosensor Symposium -Emerging trends in bioelectronics-, 19.10.-21.12.2021, Dresden, Deutschland

Permalink: https://www.hzdr.de/publications/Publ-33566
Publ.-Id: 33566


Electronic and Transport Properties of Novel Two Dimensional Materials

Ramzan, M. S.

The family of 2D layered materials has gained enormous attention of materials scientists and researchers from other fields of science. This stems from the fact that 2D monolayers (1Ls) can exhibit remarkably different electronic properties than their bulk counterparts. Moreover, stacking different 1Ls, results in yet different electronic properties than these of the 1Ls. Recently, among others, van der Waals heterostructures (vdW HS) of transition-metal dichalcogenides (TMDC) have been extensively studied due to their type-II band alignment.
This thesis summarizes four different theoretical studies on layered 2D materials. The first study investigates the potential existence of a new family of bulk layered materials with chemical formula XY3 (where X = group 14; Y = group 15). The low cleavage energies indicate the potential exfoliation as mono- and bi- layers (2Ls), where most of the exfoliated layers are thermally and dynamically stable. Interestingly, many 1Ls and 2Ls show strong quantum confinement and turn into indirect semiconductors, unlike bulks which are all metals. Such metal to semiconductor transition was previously known for noble-metal dichalcogenides. Next study shows one of the potential applications of XY3, that is, single-material logical junction for gas sensing applications. A device that consists of metallic multilayers (3L) as electrodes and semiconducting 1L as scattering region. To do so, one of the exemplary materials (SnP3) was picked to construct a single-material device. The results combining density functional theory (DFT) and non-equilibrium Green’s function (NEGF) calculations revealed that SnP3 is an ideal material for gas sensing applications, especially for poisonous NO gas molecules. For NO molecules, this device showed a negative differential resistance (NDR) at small bias voltages.
Moreover, electronic properties of vdW TMDC HS were investigated for the HS having up to six layers. In this part, it was essentially studied how the electron and hole states in heterobilayer (HBL), namely MoS2/WSe2, will change as a function of additional electron/hole layers. We found that additional electron layers will result in equal delocalization of electron states among all layers forming conduction bands. However, additional hole layers do not alter the holes states distribution much, i.e., hole states stay localized at HBL+1L (WSe2).
The last study, in this thesis, focused on understanding the interplay between the so- called atomic collapse states and moiré potential in twisted bilayer graphene (tBLG) systems. It was found that individual graphene layers did host collapse states. However, moiré potential in tBLG may destroy the collapse states, although tBLG systems have similar band dispersion as in graphene.
The knowledge acquired from the findings presented in this thesis can provide new potential candidates as well as some helpful insights into electronic properties of existing layered materials, for their applications in the future nano(opto)electronic devices.

  • Doctoral thesis
    Jacobs University Bremen, 2022
    Mentor: PD Dr. A. B. Kuc

Permalink: https://www.hzdr.de/publications/Publ-33565
Publ.-Id: 33565


[¹⁸F]FLUDA - A novel radiotracer for PET imaging of the adenosine A₂A receptor (A₂AR)

Lai, T. H.; Toussaint, M.; Teodoro, R.; Dukić-Stefanović, S.; Gündel, D.; Ludwig, F.-A.; Wenzel, B.; Schröder, S.; Sattler, B.; Moldovan, R.-P.; Sabri, O.; Deuther-Conrad, W.; Brust, P.

Introduction: Selective A₂AR antagonists have emerged as potential therapeutics for multiple diseases. With regard to Parkinson’s disease, adjunctive treatment of A₂AR antagonists potentially reduces adverse effects of long-term L-DOPA treatment. Therefore, imaging of receptor availability during the A2AR-tailored therapy is of utmost importance. We recently developed [¹⁸F]FLUDA as an novel A₂AR-specific PET radiotracer [1].
Methods: [¹⁸F]FLUDA was synthesized by an automated procedure Biological evaluation was performed in healthy mice and piglets. In vitro autoradiography was performed with brain cryosections. In vivo metabolism was analysed by radio-HPLC of plasma and brain homogenate. Pharamcokinetics and biodistribution was assessed by dynamic PET imaging under control and blocking conditions (2.5 mg/kg tozadenant and/or 1.0 mg/kg istradefylline). SUV ratio (SUVr) of striatum-over-cerebellum was used as a metric for specific uptake. A single dose acute toxicity study was performed in Wistar rats according to the ICH guideline M3(R2). Radiation dosimetry was investigated in piglets.
Results: In vitro autoradiography revealed an A₂AR affinity (KD;) of 4.3 and 0.7 nM and an A₂AR density (Bmax) of 556 and 218 fmol/mg in the striatum of mice and piglets. No radiometabolites were detected in the mouse brain at 15 min p.i., whereas radiometabolites were found in piglet plasma but are assumed to not cross the blood-brain barrier. PET demonstrated high specific binding of [¹⁸F]FLUDA in both species (Fig.1). Toxicity studies revealed no adverse effects up to a dose of 30 µg/kg (~4000-fold of expected human dose). The ED to humans is 16.4 µSv/MBq, which is in the range of other ¹⁸F-labeled radiotracers [2].
Conclusion: We have demonstrated that [¹⁸F]FLUDA is suitable for determination of the A₂AR availability in the striatum. No safety concerns are expected upon administration of [¹⁸F]FLUDA according to toxicity and dosimetry data. These results encourage the clinical translation of [¹⁸F]FLUDA.
Acknowledgement: This work (Project No. 100226753) has been funded by the European Regional Development Fund (ERDF) and Sächsische Aufbaubank (SAB).
References: [1] Lai, T.H., Toussaint, M., Teodoro, R., Dukić-Stefanović, S., Gündel, D., Ludwig, F.-A., Wenzel, B., Schröder, S., Sattler, B., Moldovan, R.-P., Falkenburger, B.H., Sabri, O., Winnie Deuther-Conrad, W., Peter Brust, P. Improved in vivo PET imaging of the adenosine A₂A receptor in the brain using [¹⁸F]FLUDA, a deuterated radiotracer with high metabolic stability. Eur J Nucl Med Mol Imaging 2021, 48, 2727–2736. [2] Sattler, B., Kranz, M., Lai, T.H., Gündel, D., Toussaint, M., Schröder, S., Moldovan, R.-P., Winnie Deuther-Conrad, W., Teodoro, R., Sabri, O., Peter Brust, P. Preclincal incorporation dosimetry of [¹⁸F]FLUDA - a novel ¹⁸F-labeled tracer for PET imaging of the expression of the adenosine A₂A receptor (A₂AR). J Nucl Med 2020, 61:1014.

Keywords: adenosine receptors; A₂A receptor; neurodegeneration; positron emission tomography; fluorine-18

  • Poster (Online presentation)
    NRM2021 - XIII international symposium of functional neuroreceptor mapping of the living brain, 14.-16.12.2021, online, online
  • Poster (Online presentation)
    NRM 2021 Mapping NeuroReceptors at Work, 14.-16.12.2021, virtual presentation, virtual presentation

Permalink: https://www.hzdr.de/publications/Publ-33564
Publ.-Id: 33564


²¹⁰Pb measurements at the André E. Lalonde AMS Laboratory: Potential for the radioassay of materials used in rare event search detectors

Vivo Vilches, C.; Weiser, B.; Zhao, X.; Francisco, B. B. A.; Gornea, R.; Kieser, W. E.

²¹⁰Pb (𝑇1∕2=22.2 y) is an important source of background in rare event searches, such as neutrinoless double-𝛽 decay and dark matter direct detection experiments. In this paper, the capabilities of the A.E. Lalonde AMS Laboratory at the University of Ottawa for ²¹⁰Pb measurements are discussed.
For fluoride targets, the blank ²¹⁰Pb/²⁰⁶Pb ratio was in the 1e-14 to 1e-13 range, but (PbF₃)- current output was lower and less stable. For oxide targets, (PbO₂)- current output showed better stability, despite a significant difference in current output for commercial PbO and processed samples, and background studies suggested a background not much higher than that of the fluoride targets. Both target materials showed, therefore, good performance for ²¹⁰Pb Accelerator Mass Spectrometry assay.
Measurements of Kapton ultra-thin films were performed. 90% C.L. upper limits for the ²¹⁰Pb specific activity in the range of 0.74–2.8 Bq/kg were established for several Kapton HN films.

Keywords: ²¹⁰Pb contamination; Accelerator mass spectrometry; Rare event searches; Astroparticle physics; Radiopurity

Downloads

Permalink: https://www.hzdr.de/publications/Publ-33562
Publ.-Id: 33562


EANM Guideline on Quality Risk Management for radiopharmaceuticals

Gillings, N.; Hjelstuen, O.; Behe, M.; Decristoforo, C.; Elsinga, P.; Ferrari, V.; Kiß, O.; Kolenc, P.; Koziorowski, J.; Laverman, P.; Mindt, T.; Ocak, M.; Patt, M.; Todde, S.; Walte, A.

This document is intended as a supplement to the EANM “Guidelines on current Good Radiopharmacy Practice (cGRPP)” issued by the Radiopharmacy Committee of the EANM [1]. The aim of the EANM Radiopharmacy Committee is to provide a document that describes how to manage risks associated with small-scale “in-house” preparation of radiopharmaceuticals, not intended for commercial purposes or distribution.

Keywords: Risk assessment; radiopharmaceuticals; quality assurance

Permalink: https://www.hzdr.de/publications/Publ-33561
Publ.-Id: 33561


Cyclotrons operated for Nuclear Medicine and Radiopharmacy in the German speaking D-A-CH countries: An update on current status and trends

Zippel, C.; Ermert, J.; Patt, M.; Gildehaus, F. J.; Ross, T. L.; Reischl, G.; Neumaier, B.; Kiß, O.; Mitterhauser, M.; Wadsak, W.; Schibli, R.; Kopka, K.

Background: Cyclotrons form a central infrastructure and are a resource of medical radionu- clides for the development of new radiotracers as well as the production and supply of clini- cally established radiopharmaceuticals for patient care in nuclear medicine.
Aim: To provide an updated overview of the number and characteristics of cyclotrons that are currently in use within radiopharmaceutical sciences and for the development of radiopharma- ceuticals to be used for patient care in Nuclear Medicine in Germany (D), Austria (A) and Switzerland (CH).
Methods: Publicly available information on the cyclotron infrastructure was (i) consolidated and updated, (ii) supplemented by selective desktop research and, last but not least, (iii) vali- dated by members of the committee of the academic “Working Group Radiochemistry and Radiopharmacy” (AGRR), consisting of radiochemists and radiopharmacists of the D-A-CH countries and belonging to the German Society of Nuclear Medicine (DGN), as well as the Radiopharmaceuticals Committee of the DGN.
Results: In total, 39 cyclotrons were identified that are currently being operated for medical radionuclide production for imaging and therapy in Nuclear Medicine clinics, 29 of them in Germany, 4 in Austria and 6 in Switzerland. The majority of the cyclotrons reported (69%) are operated by universities, university hospitals or research institutions close to a university (clinic), less by/in cooperation with industrial partners (26%) or a (non-university) clinic/PET-center (5%). Most of the cyclotrons (82%) are running with up to 18 MeV proton beams, which is sufficient for the production of the currently most common cyclotron-based radionuclides for PET imaging.
Discussion: The data presented provide an academically-updated overview of the medical cy- clotrons operated for the production of radiopharmaceuticals and their use in Nuclear Medi- cine in the D-A-CH countries. In this context, we discuss current developments and trends with a view to the cyclotron infrastructure in these countries, with a specific focus on organi- sational aspects.

Keywords: (Medical) Cyclotron; radionuclide production; nuclear medicine; infrastructure for radiopharmaceutical production

Permalink: https://www.hzdr.de/publications/Publ-33560
Publ.-Id: 33560


Automated radiosynthesis of the adenosine A2A receptor-targeting radiotracer [18F]FLUDA

Lai, T. H.; Wenzel, B.; Moldovan, R.-P.; Brust, P.; Kopka, K.; Teodoro, R.

[18F]FLUDA is a selective radiotracer for in vivo imaging of the adenosine A2A receptor (A2AR) by positron emission tomography (PET). Promising preclinical results obtained by neuroimaging of mice and piglets suggest the translation of [18F]FLUDA to human PET studies. Thus, we report herein a remotely controlled automated radiosynthesis of [18F]FLUDA using a GE TRACERlab FX2 N radiosynthesizer. The radiotracer was obtained by a one-pot two-step radiofluorination procedure with a radiochemical yield of 9 ± 1%, a radiochemical purity of ≥ 99% and molar activities in the range of 69 333 GBq/µmol at the end of synthesis within a total synthesis time of approx. 95 min (n = 16). Altogether, we successfully established a reliable and reproducible procedure for the automated production of [18F]FLUDA.

Related publications

  • Open Access Logo Journal of Labelled Compounds and Radiopharmaceuticals 65(2022), 162-166
    Online First (2022) DOI: 10.1002/jlcr.3970

Permalink: https://www.hzdr.de/publications/Publ-33558
Publ.-Id: 33558


Data Publication: Nondiffusive Transport and Anisotropic Thermal Conductivity in High-Density Pt/Co Superlattices

Shahzadeh, M.; Andriyevska, O.; Salikhov, R.; Fallarino, L.; Hellwig, O.; Pisana, S.

This dataset is a sample preparation description and magnetic property characteristics for Co/Pt multilayers, where the ballistic-like anisotropic thermal conductivity is detected. 

Keywords: heat transport; metallic multilayers; anisotropic thermal conductivity; nondiffusive transport; frequency domain thermoreflectance

Related publications

Downloads

Permalink: https://www.hzdr.de/publications/Publ-33556
Publ.-Id: 33556


Warm dense matter and many body theory

Vorberger, J.

The talk will cover some recent attempts to recreate and describe the states of matter as in brown dwarfs, ice giant planets, or the earth. In particular, state of the art methods will be described to model the x-ray scattering signal of such warm dense matter states. Density functional theory seems to be a very promising tool, although upon close inspection, several problems arise that strongly limit the predictive power of this method. This leads to investigations of the underlying model system, the electron gas, using quantum Monte Carlo methods. Finally, we show a promising new method to study higher order correlations in the system by nonlinear excitations.

  • Lecture (others) (Online presentation)
    CFEL Theory Seminar, 26.01.2021, online, Germany

Permalink: https://www.hzdr.de/publications/Publ-33555
Publ.-Id: 33555


Intrinsic energy flow in laser-excited 3d ferromagnets

Zahn, D.; Jakobs, F.; Seiler, H.; Butcher, T. A.; Engel, D.; Vorberger, J.; Atxitia, U.; William Windsor, Y.; Ernstorfer, R.

Ultrafast magnetization dynamics are governed by energy flow between electronic, magnetic, and lattice degrees of freedom. A quantitative understanding of these dynamics must be based on a model that agrees with experimental results for all three subsystems. However, ultrafast dynamics
of the lattice remain largely unexplored experimentally. Here, we combine femtosecond electron diffraction experiments of the lattice dynamics with energy-conserving atomistic spin dynamics (ASD) simulations and ab-initio calculations to study the intrinsic energy flow in the 3d ferromagnets cobalt (Co) and iron (Fe). The simulations yield a good description of experimental data, in particular an excellent description of our experimental results for the lattice dynamics. We find that the lattice dynamics are influenced significantly by the magnetization dynamics due to the energy cost of demagnetization. Our results highlight the role of the spin system as the dominant heat sink in the first hundreds of femtoseconds. Together with previous findings for nickel, our work demonstrates that energy-conserving ASD simulations provide a general and consistent description of the laser-induced dynamics in all three elemental 3d ferromagnets.

Keywords: ferromagnet; iron; cobalt; lattice; spin; relaxation

Related publications

Permalink: https://www.hzdr.de/publications/Publ-33554
Publ.-Id: 33554


Proton stopping measurements at low velocity in warm dense carbon

Malko, S.; Cayzac, W.; Ospina-Bohorquez, V.; Bhutwala, K.; Bailly-Grandvaux, M.; Fedosejevs, R.; McGuffey, C.; Vaisseau, X.; Tauschwitz, A.; Apinaniz, J. I.; Gatti, G.; de Luis, D.; Perez Hernandez, J. A.; Huault, M.; Hu, S. X.; White, A. J.; Collins, L. A.; Neumayer, P.; Faussurier, G.; Vorberger, J.; Prestopino, G.; Verona, C.; Santos, J. J.; Batani, D.; Beg, F.; Volpe, L.

Ion stopping in warm dense matter is a process of fundamental importance for the understanding of the properties of dense plasmas, the realization and the interpretation of experiments involving ion beam-induced warm dense matter samples, and for inertial confinement fusion research. The theoretical description of the ion stopping power in warm dense matter is difficult notably due to electron coupling and degeneracy, and measurements are still largely missing. In particular, the low-velocity stopping range around the Bragg peak, that features the largest modelling uncertainties, remains virtually unexplored. Here, we report proton energy-loss measurements in warm dense plasma at lower projectile velocities than previous experiments, coming significantly closer to the Bragg peak region. Our energy-loss data, combined with a precise target characterization based on plasma temperature measurements us-
ing two different diagnostics, demonstrate a significant deviation of the stopping power from classical models in this regime. In particular, we show
that our results are consistent with recent first-principles simulations based on time-dependent density functional theory.

Keywords: stopping power; fusion

Permalink: https://www.hzdr.de/publications/Publ-33553
Publ.-Id: 33553


Quasiparticle electronic structure and optical response (G0W0+BSE) of anatase TiO2 starting from modified HSE06 functionals

Sruthil Lal, S. B.; Sharan, A.; Devaraj, M.; Posselt, M.; Sasikala Devi, A. A.

The quasiparticle electronic structure and optical excitation of anatase TiO2 is determined within the framework of many-body perturbation theory (MBPT) by combining the G0W0 method and the Bethe-Salpeter Equation (BSE). A modified version of the HSE06 screened hybrid functional, that includes 20% exact Fock exchange (HSE06(20)) as opposed to 25% in the standard HSE06 functional, is used to set up the starting Hamiltonian for G0W0+BSE calculations. The HSE06(20) functional accurately predicts the ground state electronic band structure. BSE calculations based on data from G0W0+HSE06(20) yield direct optical excitation energies and oscillator strengths in excellent agreement with existing experiments and theoretical calculations characterizing direct excitation. In particular, an exciton binding energy of 229 +- 10 meV is obtained, in close agreement with experiments. The projections of excitonic states onto the quasiparticle band structure in a fatband representation shows that the lowest optical transition of anatase TiO2 consists of excitons originating from the mixing of direct transitions within band pairs running parallel to the Gamma-Z direction in the tetragonal Brillouin zone. This implies a strong spatial localization of excitons in the xy plane of the lattice. This investigation highlights the importance of a suitable non-interacting Hamiltonian for the MBPT based quasiparticle G0W0 and subsequent BSE calculations and suggests HSE06(20) as an optimal choice in the case of anatase TiO2.

Keywords: Quasiparticle electronic structure; Anatase Ti dioxide; Optical response; Density functional theory; HSE06 hybrid functional; Many body pertubation theory; G0W0 approach; Bethe-Salpeter equation; Excitons

Permalink: https://www.hzdr.de/publications/Publ-33551
Publ.-Id: 33551


Selenium nanowire formation by reaction of selenate with magnetite

Poulain, A.; Fernandez-Martinez, A.; Greneche, J.-M.; Prieur, D.; Scheinost, A.; Menguy, N.; Bureau, S.; Magnin, V.; Findling, N.; Drnec, J.; Martens, I.; Mirolo, M.; Charlet, L.

The mobility of 79Se, a long half-life radioisotope and fission product of 235U, and contaminant of drainage waters from black shale mountains and from coal mines, is an important parameter in the safety assessment of radioactive nuclear waste disposal systems. Highly mobile and soluble in its high oxidation states (Se(VI)O42-, Se(IV)O32-), selenium oxyanions can interact with magnetite, a mineral present in anoxic natural environments and in steel corrosion products, and be precipitated by reduction, and thus immobilized. Here, the sorption and reduction capacity of synthetic nanomagnetite towards Se(VI) was investigated at neutral and acidic pH, under reducing, oxygen free conditions. The additional presence of Fe(II)aq, released during magnetite dissolution at pH 5, is shown to have an effect on the reduction kinetics. XANES analyses revealed that, at pH 5, trigonal gray Se(0) formed, and that outer-sphere Se(IV) complexes existed at the nanoparticle surface at longer reaction times. The Se(0) nanowires grew during the reaction, which points to a complex transport mechanism of reduced species or to active reduction sites at the tip of the Se(0) nanowires. The concomitant uptake of aqueous Fe(II) and Se(VI) ions is interpreted as a consequence of small pH oscillations that result from the Se(VI) reduction, leading to a re- adsorption of aqueous Fe(II) onto the magnetite, renewing its reducing capacity. This effect is not observed at pH 7, indicating that the presence of aqueous Fe(II) may be an important factor to be considered when examining the environmental reactivity of magnetite.

Keywords: Nuclear wastes; Magnetite to maghemite interconversion; Selenium reduction; Sorption on magnetite; Selenium needles

Related publications

Downloads

Permalink: https://www.hzdr.de/publications/Publ-33550
Publ.-Id: 33550


Using neutrons and x rays to measure plasma conditions in a solid sphere of deuterated polyethylene compressed to densities of 35 g/cc at temperatures of 2 keV and pressures of 40 Gbar

Nilsen, J.; Bachmann, B.; Zimmerman, G. B.; Hatarik, R.; Döppner, T.; Swift, D. C.; Hawreliak, J.; Collins, G. W.; Falcone, R. W.; Glenzer, S. H.; Kraus, D.; Landen, O. L.; Castor, J. I.; Whitley, H. D.; Kritcher, A. L.

This paper describes an experiment that shock compresses the center of a solid deuterated polyethylene sphere, CD2, to densities of 35 g/cc and temperatures of 2 keV with corresponding pressure of 40 Gbar. The design employs a strong spherically converging shock launched through a solid ball of material using a Hohlraum radiation drive. As the shock coalesces at the center it produces a hot spot that we
characterize by measuring the x-ray self-emission and 2.45MeV neutrons emitted. Two-dimensional images and time-resolved measurements of the x rays emitted determine the size and time duration of the hot spot, leading to an estimated 2 keV electron temperature. The neutron time of flight spectrometer measures an average ion temperature of 1.06 +/- 0.15 keV and neutron yield of 7.0 (+/-0.5) x 10^9 DD neutrons. Our new distribution function tool enables us to create a forward model of the experimental data based on 1D radiation-hydrodynamic simulations, leading to a better understanding of the plasma conditions that produce the measured neutrons and x rays. Our simulations indicate that the x rays are produced in a short-lived hot-dense core over tens of picoseconds, whereas the neutron emission continues for about 200 ps, as the hot core starts to expand, thereby leading to a lower mean temperature of the plasma during neutron production. This finding is in agreement with the experimental data, and we therefore conclude that the forward-modeling is a useful tool forinferring the conditions of the hot spot in a laser-driven implosion during burn.

Downloads

Permalink: https://www.hzdr.de/publications/Publ-33549
Publ.-Id: 33549


Teaching ML workshop at ECML/PKDD - 2 years in, 3 thoughts out

Steinbach, P.; Kinnaird, K. M.; Guhr, O.

As a co-organizer of the Teaching Machine Learning Workshop at ECMLPKDD, I'd like to share our experience in striving to host a mixture of communities to share and discuss advances in teaching of ML to any level of prior knowledge.

What was thought of a small event on the European level, has now become an event at international scale. I'll distill essential outcomes that have relevance to Helmholtz.

This presentation was delivered at the TEACH conference:

https://events.hifis.net/event/164/timetable/#20211207.detailed

Keywords: machine learning; teaching; training; data science; artificial intelligence; conference; didactics

  • Open Access Logo Lecture (Conference) (Online presentation)
    TEACH - Talk about Education Across Communities in Helmholtz, 07.-10.12.2021, virtuell, Deutschland
    DOI: 10.6084/m9.figshare.17134580.v1

Permalink: https://www.hzdr.de/publications/Publ-33548
Publ.-Id: 33548


Do We Need Complex Image Features to Personalize Treatment of Patients with Locally Advanced Rectal Cancer?

Shahzadi, I.; Lattermann, A.; Linge, A.; Zwanenburg, A.; Baldus, C.; Peeken, J. C.; Combs, S. E.; Baumann, M.; Krause, M.; Troost, E. G. C.; Löck, S.

Radiomics has shown great potential for outcome prognosis and presents a promising approach for improving personalized
cancer treatment. In radiomic analyses, features of different complexity are extracted from clinical imaging datasets, which
are correlated to the endpoints of interest using machine-learning approaches. However, it is generally unclear if more
complex features have a higher prognostic value and show a robust performance in external validation. Therefore, in this
study, we developed and validated radiomic signatures for outcome prognosis after neoadjuvant radiochemotherapy in
locally advanced rectal cancer (LARC) using computed tomography (CT) and T2-weighted magnetic resonance imaging
(MRI) of two independent institutions (training/validation: 94/28 patients). For the prognosis of tumor response and freedom
from distant metastases (FFDM), we used different imaging features extracted from the gross tumor volume: less complex
morphological and first-order (MFO) features, more complex second-order texture (SOT) features, and both feature classes
combined. Analyses were performed for both imaging modalities separately and combined. Performance was assessed by
the area under the curve (AUC) and the concordance index (CI) for tumor response and FFDM, respectively. Overall,
radiomic features showed prognostic value for both endpoints. Combining MFO and SOT features led to equal or higher
performance in external validation compared to MFO and SOT features alone. The best results were observed after
combining MRI and CT features (AUC = 0.76, CI = 0.65). In conclusion, promising biomarker signatures combining MRI and
CT were developed for outcome prognosis in LARC. Further external validation is pending before potential clinical
application.

Keywords: Biomarkers; Distant metastases; Rectal cancer; Tumor response

  • Book chapter
    in: Medical Image Computing and Computer Assisted Intervention – MICCAI 2021, Cham: Springer Nature Switzerland AG, 2021, 775-785
    DOI: 10.1007/978-3-030-87234-2_73

Permalink: https://www.hzdr.de/publications/Publ-33547
Publ.-Id: 33547


Lamellipodin-rictor signaling mediates glioblastoma cell invasion and radiosensitivity downstream of egfr

Moritz, S.; Krause, M.; Schlatter, J.; Cordes, N.; Vehlow, A.

Glioblastoma is a tumor type of unmet need despite the development of multimodal treatment strategies. The main factors
contributing to the poor prognosis of glioblastoma patients are diverse genetic and epigenetic changes driving glioblastoma
persistence and recurrence. Com-plemented are these factors by extracellular cues mediated through cell surface receptors,
which further aid in fostering pro-invasion and pro-survival signaling contributing to glioblastoma therapy resistance. The
underlying mechanisms conferring this therapy resistance are poorly understood. Here, we show that the cytoskeleton
regulator Lamellipodin (Lpd) mediates invasiveness, proliferation and radiosensitivity of glioblastoma cells.
Phosphoproteome analysis identified the epidermal growth factor receptor (EGFR) signaling axis commonly hyperactive in
glioblastoma to depend on Lpd. Mechanistically, EGFR signaling together with an interaction between Lpd and the
Rapamycin-insensitive companion of mammalian target of rapamycin (RICTOR) jointly regulate glioblastoma radiosensitivity.
Collectively, our findings demonstrate an essential function of Lpd in the radiation response and invasiveness of
glioblastoma cells. Thus, we uncover a novel Lpd-driven resistance mechanism, which adds an additional critical facet to the
complex glioblastoma resistance network. © 2021 by the authors. Licensee MDPI, Basel, Switzerland.

Keywords: EGFR; Glioblastoma; Invasion; Lamellipodin; Radiosensitivity; RICTOR

Permalink: https://www.hzdr.de/publications/Publ-33546
Publ.-Id: 33546


Towards online adaptive proton therapy: first report of plan-library-based plan-of-the-day approach

Troost, E. G. C.; Menkel, M.; Tschiche, M.; Thiele, J.; Jaster, M.; Haak, D.; Kunath, D.

letter to editor

Downloads

Permalink: https://www.hzdr.de/publications/Publ-33545
Publ.-Id: 33545


Reduced diffusion in white matter after radiotherapy with photons and protons

Dünger, L.; Seidlitz, A.; Jentsch, C.; Platzek, I.; Kotzerke, J.; Beuthien-Baumann, B.; Baumann, M.; Krause, M.; Troost, E. G. C.; Raschke, F.

Background and purpose

Radio(chemo)therapy is standard in the adjuvant treatment of glioblastoma. Inevitably, brain tissue surrounding the target volume is also irradiated, potentially causing acute and late side-effects. Diffusion imaging has been shown to be a sensitive method to detect early changes in the cerebral white matter (WM) after radiation. The aim of this work was to assess possible changes in the mean diffusivity (MD) of WM after radio(chemo)therapy using Diffusion-weighted imaging (DWI) and to compare these effects between patients treated with proton and photon irradiation.
Materials and methods

70 patients with glioblastoma underwent adjuvant radio(chemo)therapy with protons (n = 20) or photons (n = 50) at the University Hospital Dresden. MRI follow-ups were performed at three-monthly intervals and in this study were evaluated until 33 months after the end of therapy. Relative white matter MD changes between baseline and all follow-up visits were calculated in different dose regions.
Results

We observed a significant decrease of MD (p < 0.05) in WM regions receiving more than 20 Gy. MD reduction was progressive with dose and time after radio(chemo)therapy (maximum: −7.9 ± 1.2% after 24 months, ≥50 Gy). In patients treated with photons, significant reductions of MD in the entire WM (p < 0.05) were seen at all time points. Conversely, in proton patients, whole brain MD did not change significantly.
Conclusions

Irradiation leads to measurable MD reduction in white matter, progressing with both increasing dose and time. Treatment with protons reduces this effect most likely due to a lower total dose in the surrounding white matter. Further investigations are needed to assess whether those MD changes correlate with known radiation induced side-effects.

Keywords: Diffusion imaging; White matter; Radiotherapy; Proton therapy; Photon therapy

Permalink: https://www.hzdr.de/publications/Publ-33544
Publ.-Id: 33544


The impact of anatomical changes during photon or proton based radiation treatment on tumor dose in glioblastoma dose escalation trials

Hessen, E. D.; Makocki, S.; van der Heide, U. A.; Jasperse, B.; Lutkenhaus, L. J.; Lamers, E.; Damen, E.; Troost, E. G. C.; Borst, G. R.

Purpose/Objective

Most dose-escalation trials in glioblastoma patients integrate the escalated dose throughout the standard course by targeting a specific subvolume. We hypothesize that anatomical changes during irradiation may affect the dose coverage of this subvolume for both proton- and photon-based radiotherapy.
Material and Methods

For 24 glioblastoma patients a photon- and proton-based dose escalation treatment plan (of 75 Gy/30 fr) was simulated on the dedicated radiotherapy planning MRI obtained before treatment. The escalated dose was planned to cover the resection cavity and/or contrast enhancing lesion on the T1w post-gadolinium MRI sequence. To analyze the effect of anatomical changes during treatment, we evaluated on an additional MRI that was obtained during treatment the changes of the dose distribution on this specific high dose region.
Results

The median time between the planning MRI and additional MRI was 26 days (range 16–37 days). The median time between the planning MRI and start of radiotherapy was relatively short (7 days, range 3–11 days). In 3 patients (12.5%) changes were observed which resulted in a substantial deterioration of both the photon and proton treatment plans. All these patients underwent a subtotal resection, and a decrease in dose coverage of more than 5% and 10% was observed for the photon- and proton-based treatment plans, respectively.
Conclusion

Our study showed that only for a limited number of patients anatomical changes during photon or proton based radiotherapy resulted in a potentially clinically relevant underdosage in the subvolume. Therefore, volume changes during treatment are unlikely to be responsible for the negative outcome of dose-escalation studies.

Keywords: Glioblastoma; Anatomical changes; Radiotherapy; Repeated MRI; Target volume changes; Dose escalation trials

Permalink: https://www.hzdr.de/publications/Publ-33543
Publ.-Id: 33543


Role of postoperative radiotherapy in the management for resected NSCLC – Decision criteria in clinical routine pre- and post-LungART

Süveg, K.; Le Pechoux, C.; Faivre-Finn, C.; Putora, P. M.; de Ruysscher, D.; Widder, J.; van Houtte, P.; Troost, E. G. C.; Slotman, B.; Ramella, S.; Pöttgen, C.; Peeters, S. T. H.; Nestle, U.; McDonald, F.; Dziadziuszko, R.; Belderbos, J.; Ricardi, U.; Manapov, F.; Lievens, Y.; Geets, X.; Dieckmann, K.; Guckenberger, M.; Andratschke, N.; Glatzer, M.

Background

The role of postoperative radiation therapy (PORT) in stage III N2 NSCLC is controversial. We analyzed decision-making for PORT among European radiation oncology experts in lung cancer.
Methods

Twenty-two experts were asked before and after presentation of the results of the LungART trial to describe their decision criteria for PORT in the management of pN+ NSCLC patients. Treatment strategies were subsequently converted into decision trees and analyzed.
Results

Following decision criteria were identified: extracapsular nodal extension, incomplete lymph node resection, multistation lymph nodes, high nodal tumor load, poor response to induction chemotherapy, ineligibility to receive adjuvant chemotherapy, performance status, resection margin, lung function and cardiopulmonary comorbidities. The LungART results had impact on decision-making and reduced the number of recommendations for PORT. The only clear indication for PORT was a R1/2 resection. Six experts out of ten who initially recommended PORT for all R0 resected pN2 patients no longer used PORT routinely for these patients, while four still recommended PORT for all patients with pN2. Fourteen experts used PORT only for patients with risk factors, compared to eleven before the presentation of the LungART trial. Four experts stated that PORT was never recommended in R0 resected pN2 patients regardless of risk factors.
Conclusion

After presentation of the LungART trial results at ESMO 2020, 82% of our experts still used PORT for stage III pN2 NSCLC patients with risk factors. The recommendation for PORT decreased, especially for patients without risk factors. Cardiopulmonary comorbidities became more relevant in the decision-making for PORT.

Keywords: Adjuvant; Decision-making; Decision tree; NSCLC; Radiotherapy

Permalink: https://www.hzdr.de/publications/Publ-33542
Publ.-Id: 33542


Untersuchung der Wechselwirkung von magnetotaktischen Bakterien mit Uran in wässrigen Systemen

Ramtke, J.

Im Rahmen der Forschungsarbeiten zur Wechselwirkung von magnetotaktischen Bakterien mit Uran am Beispiel des Mikroogranismus Magnetospirillum magneticum AMB-1 konnte gezeigt werden, dass dieser ein interessantes Potential aufweist, Uranyl in wässrigen Systemen zu sorbieren. Es stellte sich heraus, dass unter den gegebenen Bedingungen, zwischen 80 und 95 % der Ausgangskonzentrationen, im Bereich von 0,1 mM, innerhalb von 25 Stunden sorbiert werden konnte. Den Daten ist zu entnehmen, dass die prozentuale Sorptionskapazität durch die Biomassekonzentration beeinflusst werden kann, mit dem Ergebnis, dass mehr Biomasse zu einer höheren Sorption führt und der Sorptionsprozess somit schneller vonstatten geht. Die Variation der Urankonzentration zeigt, dass auch Konzentrationen <0,1 mM Uran zu einem beträchtlichen Teil sorbiert werden können, allerdings im Bereich von 0,01 mM eine eher geringere Sorption stattfindet. Mit Variation des pH-Wertes konnte gezeigt werden, in welchen Bereichen die Bakterien während des Sorptionsprozesses relativ vital bleiben (pH 4,5-6,5) und welche Bereiche zu einem vermehrten Absterben führen (pH 3,5 und 7,5). Hierbei ist zu erwähnen, dass das vermehrte Absterben der Bakterien scheinbar keinen negativen Einfluss auf die Uransorption hat. Die Lokalisierung des Urans mithilfe von Transmissionselektronenmikroskopie und energiedispersiver Röntgenspektroskopie zeigt, dass die Zellwand der gramnegativen Bakterien einen großen Teil des Urans sorbieren kann. Mithilfe der zeitaufgelösten Laser-induzierten Fluoreszenzspektroskopie in Kombination mit paralleler Faktoranalyse konnten insgesamt fünf U(VI)-Spezies an der Biomasse ausfindig gemacht werden, welche mit verschiedenen Liganden wechselwirken. Es war ebenfalls möglich, anhand der Daten zu zeigen, dass diese in Abhängigkeit von dem gewählten pH-Wert in den Stufen 3,5-7,5 variieren. Dies stellt ein interessantes Ergebnis dar, weil es verdeutlicht, dass der pH-Wert einen Einfluss auf die Verteilung des Urans in den Zellen haben kann und womöglich unterschiedliche Mechanismen für die Wechselwirkung mit dem Radionuklid verantwortlich sein können. Durch die Messung von ausgewählten Referenzproben, welche die U(VI)-Spezies genauer identifizieren sollten, war es möglich zu zeigen, dass drei der fünf Spezies eine Übereinstimmung mit Proben des Peptidoglycans aufweisen (Spezies 1, 2, 3). Somit konnte anhand der Ergebnisse gezeigt werden, dass es zu einer Bindung des U(VI) am Peptidoglycan des Bakteriums Magnetospirillum magneticum AMB-1 gekommen ist, was eine neuartige Erkenntnis darstellt. Des Weiteren deuten die Daten von weiteren gemessenen Referenzproben darauf hin, dass es zu keiner Bindung am Lipopolysaccharid oder Kohlenhydraten der o-spezifischen Seitenkette gekommen ist, da die erhaltenen U(VI)-Spektren dieser Referenzen keine Übereinstimmung mit den Biomasse assoziierten U(VI)-Spektren aufweisen.

Keywords: Magnetotactic bacteria; Uranium; Sorption; Spectroscopy; Microscopy

  • Bachelor thesis
    Hochschule Zittau/Görlitz, 2021
    Mentor: Dr. Evelyn Krawczyk-Bärsch, Prof. Dr. Thomas Wiegert
    82 Seiten

Permalink: https://www.hzdr.de/publications/Publ-33541
Publ.-Id: 33541


Classifying oscillatory brain activity associated with Indian Rasas using network metrics

Pandey, P.; Tripathi, R.; Prasad Miyapuram, K.

Neural oscillations are the rich source to understand cognition, perception, and emotions. Decades of research on brain oscillations have primarily discussed neural signatures for the western classification of emotions. Despite this, the Indian ancient treatise on emotions popularly known as Rasas has remained unexplored. In this study, we collected Electroencephalography (EEG) encodings while participants watched nine emotional movie clips corresponding to nine Rasas. The key objective of this study is to identify the brain waves that could
distinguish between Rasas. Therefore, we decompose the EEG signals into five primary frequency bands comprising delta (1-4 Hz), theta (4-7 Hz), alpha (8-13 Hz), beta (13-30 Hz), and gamma (30-45 Hz). We construct the functional networks from EEG time-series data and subsequently utilize the fourteen graph-theoretical measures to compute the features. Random Forest models are trained on the extracted features, and we present our findings based on classifier predictions. We observe slow (delta) and fast brain waves (beta and gamma)
exhibited the maximum discriminating features between Rasas, whereas alpha and theta bands showed fewer distinguishable pairs. Out of nine Rasas, Sringaram, Bibhatsam, and Bhayanakam displayed the most distinguishing characteristics from other Rasas. Interestingly, our results are consistent with the previous studies, which highlight the significant role of higher frequency oscillations for the classification of emotions. Our finding on the alpha band is consistent with the previous study, which reports the maximum similarity in brain networks across emotions in the alpha band. This research contributes to the pioneering work on Indian Rasas utilizing brain responses.

Keywords: EEG; Emotion; Classification; Natyashastra; Rasa Clips; Random Forest; wPLI; Graph Theory

Permalink: https://www.hzdr.de/publications/Publ-33539
Publ.-Id: 33539


Treatment verification with prompt-gamma imaging: Detection sensitivity of anatomical changes in HNC

Berthold, J.; Hübinger, L.; Piplack, N.; Pietsch, J.; Khamfongkhruea, C.; Thiele, J.; Appold, S.; Traneus, E.; Janssens, G.; Smeets, J.; Stützer, K.; Richter, C.

Purpose/Objective
In this systematic study, we investigate the sensitivity of prompt-gamma imaging (PGI) towards the field-wise detection of inter-fractional anatomical changes in proton therapy (PT) of head and neck cancer (HNC) patients.

Materials/Methods
Spot-wise range shifts ∆RPGI were monitored with a PGI-slit-camera during 22 field deliveries of HNC pencil beam scanning (PBS) treatments of 4 patients (field-wise dose per fraction: 0.7-1.0GyE). In-room CTs were acquired for all monitored fractions and range shifts ∆RIDD at the 80% falloff of spot-wise integrated depth-dose (IDD) profiles served as input for an automatic field-wise ground truth classification (Fig.1). To receive results consistent with an additional manual dose-based classification per field, a PBS spot with relative weight to the field >0.1% was rated as relevant if |∆RIDD| was ≥5mm for that and at least 1 neighboring spot. Subsequently, a field was classified as relevantly changed if at least 1.5% of all spots were rated relevant.
For the independent PGI evaluation, spots were clustered based on Bragg-peak position and proton number to mitigate statistical measurement uncertainty. Clusters with |∆RPGI|≥5mm were classified as relevant. For training of the field-wise PGI classification model, the number of relevant clusters, that is necessary to classify the whole field as relevantly changed, was optimized with respect to the IDD ground truth classification using a training set of 11 fields. Finally, the classification model was validated on an independent test set (11 fields).

Results
On the level of PGI spot clusters, there is a significant correlation (rPearson=0.3, p<0.01) between IDD and PGI range shifts over all 22 monitored fields (Fig.2B). The only moderate correlation is mainly due to statistical uncertainty of the clusters, represented by the mean absolute error between IDD and PGI range shifts of 3.4mm. The correlation might also be affected by difficult range shift determination due to spots traversing highly heterogeneous tissue.
Despite the moderate correlation on cluster level, a field-wise classification, the main endpoint in our study, is possible with high detection sensitivity. Resulting from the training, a field was classified as relevantly changed if >12% of PGI clusters are relevant. The final model achieved a sensitivity of 80% (4/5) and a specificity of 67% (4/6) on the test cohort (Fig.2C).

Conclusion
A first systematic investigation on the sensitivity of a PGI system to field-wise detect anatomical changes in clinical HNC PT treatments was performed using quantitative dose-based ground truth information from up-to-date control CTs. The capability of PGI to detect relevant anatomical changes with high sensitivity was demonstrated, which is essential for its clinical application, e.g. as treatment intervention system for online-adaptive PT. The now available evaluation workflow as well as the permanently growing PGI dataset from the ongoing clinical PGI study are a unique basis for follow-up studies.

  • Lecture (Conference)
    ESTRO 2022, 06.-10.05.2022, Kopenhagen, Dänemark
  • Abstract in refereed journal
    Radiotherapy and Oncology 170(2022)Supplement, S837-S838
    DOI: 10.1016/S0167-8140(22)02725-6

Permalink: https://www.hzdr.de/publications/Publ-33538
Publ.-Id: 33538


Synthesis of novel selective histone deacetylase inhibitors for the development of a suitable ¹⁸F-labelled radiotracer for the molecular imaging of HDAC1 in brain tumours

Clauß, O.; Toussaint, M.; Schäker-Hübner, L.; Wenzel, B.; Deuther-Conrad, W.; Dukic-Stefanovic, S.; Ludwig, F.-A.; Gündel, D.; Teodoro, R.; Kopka, K.; Brust, P.; Hansen, F. K.; Scheunemann, M.

Objectives: Epigenetic mechanisms like methylation and acetylation of histones regulate the gene expression on the chromatin level. Thus, the degree of acetylation of lysine residues on histones influences the accessibility of DNA and furthermore the gene expression. Histone deacetylases (HDACs) are overexpressed in various tumour diseases, resulting in the interest in HDAC inhibitors (HDACi) for cancer therapy. The aim of this work is the development of a novel ¹⁸F-labelled HDAC1-selective inhibitor with an ortho-aminoanilide zinc-binding group (ZBG) to visualize this enzyme in brain tumours by positron emission tomography (PET).
Methods: Based on the selective HDAC1-3 inhibitors tacedinaline and entinostat, a series of fluorine-containing derivatives was synthesized and the IC₅₀ values were determined by an in-house biochemical enzyme assay. Out of several ligands with high inhibitory potency and selectivity for HDAC1, N-(2-amino-5-(thiophen-3-yl)phenyl)-4-((2-fluoropropanamido)methyl)benzamide (BA3, Figure 1A) was selected for radiofluorination. The two-step one-pot radiosynthesis of [¹⁸F]BA3 was performed by a nucleophilic aliphatic substitution reaction of the protected 2-bromopropionyl precursor 2 and subsequent deprotection. The process was successfully transferred to a TRACERlab FX2 N radiosynthesizer (Figure 1B). For the characterization of BA3, the in vitro stability in mouse and human liver microsomes and the cell toxicity in glioblastoma cell lines (U251-MG, F98) were assessed. In parallel, the in vivo metabolism of [¹⁸F]BA3 was investigated (mouse plasma and brain samples, 30 min p.i.) as well as PET studies in mice were carried out.
Results: BA3, containing a PAMBA linker (para-aminomethylbenzoic acid), shows a high inhibitory activity against HDAC1 and high selectivity towards HDAC3 and HDAC6 (see Table 1). The cell viability of U251-MG and F98 cells after incubation with 50 µM BA3 for 72h was only 64% and 36%, respectively. The automated radiosynthesis of [¹⁸F]BA3 resulted in a radiochemical yield of 1%, a radiochemical purity of > 96% and a molar activity between 21 and 51 GBq/µmol (n = 5, EOS). The PET studies in mice showed a low [¹⁸F]BA3 accumulation in the brain, suggesting a low blood-brain barrier penetration (SUV₅ₘᵢₙ: 0.24). Furthermore, the amount of intact radiotracer in the brain and plasma at 30 min p.i. was only 25% and 7%, respectively.
Conclusion: Due to the low blood-brain barrier penetration and the high amount of brain-penetrable radiometabolites, [¹⁸F]BA3 is classified as unsuitable for further PET-related investigations. The obtained results will be used in the design of metabolically more stable HDAC inhibitors.
Reference: [1] Krieger et al., J. Med. Chem. 2019, 62(24), 11260-11279.

Keywords: histone deacetylase 1; positron emission tomography; radiochemistry

  • Open Access Logo Poster
    ISRS 2022, 29.05.-02.06.2022, Nantes, Frankreich

Downloads

Permalink: https://www.hzdr.de/publications/Publ-33536
Publ.-Id: 33536


Light-driven permanent transition from insulator to conductor

Rana, D.; Agarwal, S.; Islam, M.; Banerjee, A.; Uberuaga, B. P.; Saadatkia, P.; Dulal, P.; Adhikari, N.; Butterling, M.; Liedke, M. O.; Wagner, A.; Selim, F. A.

The transition from insulator to conductor can be realized in some materials but requires modification of both the arrangement of atoms and their electronic configurations. This is often achieved by doping. Here we reveal a different mechanism the lattice may adopt to induce such a transition. Experiments showed the surprising finding that limited exposure to sub-bandgap light caused a permanent transition from an insulator state to a conductor state in the insulating oxide Ga2O3, with 9-orders of magnitude increase in electronic conduction. Furthermore, annealing up to 400 C did not suppress or decrease the induced conductivity. Photoexcitation by light-induced modification in the charge state of defects and subsequent lattice distortion around them was suggested to be the underlying mechanism behind this transition. Density functional theory calculations confirmed that modifying the charge state of defects leads to redistribution of the localized electrons and massive structural distortion in the surrounding lattice, causing large shifts in the density of states and introducing new states with shallower energy levels. Both experimental and theoretical results revealed the introduction of new stable shallow energy levels, explaining the mechanism behind the transition from an insulator to a conductor state by light. We suggest that this mechanism may occur in other wide bandgap metal oxides leading to drastic modification in their electronic properties.

Keywords: Ga2O3; insulator; conductor; doping; light illumination; band-gap

Related publications

Permalink: https://www.hzdr.de/publications/Publ-33535
Publ.-Id: 33535


On the electrodeposition of conically nano-structured Nickel layers assisted by a capping agent

Skibińska, K.; Huang, M.; Mutschke, G.; Eckert, K.; Włoch, G.; Wojnicki, M.; Żabiński, P.

Capping agents are frequently used in electrodeposition to support spatially inhomogeneous mass transfer at small scales. As such, chloride ions are known to support the deposition of conically nanostructured nickel layers. This work presents a systematic experimental study of the impact of a capping agent on the electrochemical growth of conically-shaped nickel deposits. Furthermore, a modeling approach on the scale of cones for numerical simulations of electrodeposition with capping agents is provided for the first time to give deeper insight on how the capping agent influences the local growth of the deposit. The growth rates of the nano-cones obtained numerically are compared with experimental data, and a good agreement is found. The impact of the capping agent concentration, the deposition time, the electrolyte temperature and the current density are investigated systematically, and optimum conditions for conical growth are derived.

Keywords: Electrodeposition; Nanostructured surface; Ni deposition; Capping agent; Ammonium chloride; Numerical modeling

Permalink: https://www.hzdr.de/publications/Publ-33534
Publ.-Id: 33534


A critical review of the solution chemistry, solubility, and thermodynamics of europium: recent advances on the Eu3+ aqua ion and the Eu(III) aqueous complexes and solid phases with the sulphate, chloride, and phosphate inorganic ligands

Jordan, N.; Thoenen, T.; Starke, S.; Spahiu, K.; Brendler, V.

This review provides a critical assessment of the published thermodynamic data of the Eu(III) aqua ion as well as complexation constants and solubility products of Eu(III) with the SO42−, Cl−, and PO43− inorganic ligands in aqueous solution. The main source for the selection of thermodynamic data are original experimental data published in peer-reviewed papers from around 1900 until the end of 2020. This review strictly follows, with a few minor deviations, the methodology recommended by the Thermochemistry Database group of the Nuclear Energy Agency, which relies on the Specific ion Interaction Theory (SIT) for describing activity coefficients in aqueous electrolyte solutions. For each inorganic ligand, a discussion is provided on the selected as well as the rejected literature data, and the procedures leading to the derivation of recommended thermodynamic data at infinite dilution, such as solubility products and complexation constants, enthalpies and entropies of reaction, molar entropies, heat capacities, as well as ion interaction coefficients ε, are described in detail. These recommended data will contribute to the establishment of a comprehensive, internally consistent, and quality-assured thermodynamic reference database for the chemical, geochemical and chemotechnical modeling of europium and increase the robustness of applications of chemical analogies for trivalent actinides or linear free energy relationships within the lanthanide group.

Keywords: Europium(III); sulphate; chloride; phosphate; complexation; solubility; SIT; thermodynamic database

Permalink: https://www.hzdr.de/publications/Publ-33533
Publ.-Id: 33533


Cation exchange on colloidal copper selenide nanosheets: a route to two-dimensional metal selenide nanomaterials

Shamraienko, V.; Spittel, D.; Hübner, R.; Khoshkhoo, M. S.; Weiß, N.; Georgi, M.; Borchert, K. B. L.; Schwarz, D.; Lesnyak, V.; Eychmüller, A.

We report a synthesis route to two-dimensional PbSe, HgSe, ZnSe, SnSe, and Cu-Zn-Sn-Se (CZTSe) nanomaterials based on cation exchange (CE) reactions. This approach includes two steps: it starts with the synthesis of hexagonal, up to several micrometers large yet approx. 5 nm-thick CuSe nanosheets (NSs), followed by CE of the host copper ions with the desired guest cation (Pb2+, Hg2+, Zn2+, or Sn4+). In the case of CZTSe, both guest cations can be added simultaneously since the variation of the guest cation ratio and reaction time can lead to various compositions. Mild reaction conditions allow for a preservation of the size and the 2D shape of the parent NSs accompanied by corresponding changes in their crystal structure. We furthermore demonstrate that the crystal structure of CuSe NSs can be rearranged even without addition of guest cations in the presence of tri-n-octylphosphine. Thus, the obtained NSs were further subjected to ligand exchange reactions in order to replace insulating bulky organic molecules on their surface with compact iodide and sulfide ions, a step crucial for the application of nanomaterials in (opto)electronic devices. The resulting NS dispersions were processed into thin films by spray-coating onto commercially available interdigitated platinum electrodes. Light response measurements of PbSe and CZTSe NS-films demonstrated their potential for applications as light-sensitive materials in photodetection or photovoltaics.

Related publications

Permalink: https://www.hzdr.de/publications/Publ-33532
Publ.-Id: 33532


Mineralogical Mapping with Accurately Corrected Shortwave Infrared Hyperspectral Data Acquired Obliquely from UAVs

Thiele, S. T.; Bnoulkacem, Z.; Lorenz, S.; Bordenave, A.; Menegoni, N.; Madriz Diaz, Y. C.; Dujoncquoy, E.; Gloaguen, R.; Kenter, J.

While uncrewed aerial vehicles are routinely used as platforms for hyperspectral sensors, ap-plications are mostly confined to nadir imaging orientations. Oblique hyperspectral imaging has been impeded by the absence of robust registration and correction protocols, which are essential to extract accurate information. These corrections are especially important for detecting the gen-erally small spectral features produced by minerals, and for infrared data acquired using pushbroom sensors. The complex movements of unstable platforms (such as UAVs) require rigor-ous geometric and radiometric corrections, especially in the rugged terrain often encountered for geological applications. In this contribution we propose a novel correction methodology, and as-sociated toolbox, dedicated to the accurate production of hyperspectral data acquired by UAVs, without any restriction concerning view angles or target geometry. We make these codes freely available to the community, and thus hope to trigger an increasing usage of hyperspectral data in Earth sciences, and demonstrate them with the production of, to our knowledge, the first fully corrected oblique SWIR drone-survey. This covers a vertical cliff in the Dolomites (Italy), and al-lowed us to distinguish distinct calcitic and dolomitic carbonate units, map the qualitative abun-dance of clay/mica minerals, and thus characterise seismic scale facies architecture.

Keywords: infrared; hyperspectral; uncrewed aerial vehicle; calcite; dolomite

Permalink: https://www.hzdr.de/publications/Publ-33531
Publ.-Id: 33531


Pages: [1.] [2.] [3.] [4.] [5.] [6.] [7.] [8.] [9.] [10.] [11.] [12.] [13.] [14.] [15.] [16.] [17.] [18.] [19.] [20.] [21.] [22.] [23.] [24.] [25.] [26.] [27.] [28.] [29.] [30.] [31.] [32.] [33.] [34.] [35.] [36.] [37.] [38.] [39.] [40.] [41.] [42.] [43.] [44.] [45.] [46.] [47.] [48.] [49.] [50.] [51.] [52.] [53.] [54.] [55.] [56.] [57.] [58.] [59.] [60.] [61.] [62.] [63.] [64.] [65.] [66.] [67.] [68.] [69.] [70.] [71.] [72.] [73.] [74.] [75.] [76.] [77.] [78.] [79.] [80.] [81.] [82.] [83.] [84.] [85.] [86.] [87.] [88.] [89.] [90.] [91.] [92.] [93.] [94.] [95.] [96.] [97.] [98.] [99.] [100.] [101.] [102.] [103.] [104.] [105.] [106.] [107.] [108.] [109.] [110.] [111.] [112.] [113.] [114.] [115.] [116.] [117.] [118.] [119.] [120.] [121.] [122.] [123.] [124.] [125.] [126.] [127.] [128.] [129.] [130.] [131.] [132.] [133.] [134.] [135.] [136.] [137.] [138.] [139.] [140.] [141.] [142.] [143.] [144.] [145.] [146.] [147.] [148.] [149.] [150.] [151.] [152.] [153.] [154.] [155.] [156.] [157.] [158.] [159.] [160.] [161.] [162.] [163.] [164.] [165.] [166.] [167.] [168.] [169.] [170.] [171.] [172.] [173.] [174.] [175.] [176.] [177.] [178.] [179.] [180.] [181.] [182.] [183.] [184.] [185.] [186.] [187.] [188.] [189.] [190.] [191.] [192.] [193.] [194.] [195.] [196.] [197.] [198.] [199.] [200.] [201.] [202.] [203.] [204.] [205.] [206.] [207.] [208.] [209.] [210.] [211.] [212.] [213.] [214.] [215.] [216.] [217.] [218.] [219.] [220.] [221.] [222.] [223.] [224.] [225.] [226.] [227.] [228.] [229.] [230.] [231.] [232.] [233.] [234.] [235.] [236.] [237.] [238.] [239.] [240.] [241.] [242.] [243.] [244.] [245.] [246.] [247.] [248.] [249.] [250.] [251.] [252.] [253.] [254.] [255.] [256.] [257.] [258.] [259.] [260.] [261.] [262.] [263.] [264.] [265.] [266.] [267.] [268.] [269.] [270.] [271.] [272.] [273.] [274.] [275.] [276.] [277.] [278.] [279.] [280.] [281.] [282.] [283.] [284.] [285.] [286.] [287.] [288.] [289.] [290.] [291.] [292.] [293.] [294.] [295.] [296.] [297.] [298.] [299.] [300.] [301.] [302.] [303.] [304.] [305.] [306.] [307.] [308.] [309.] [310.] [311.] [312.] [313.] [314.] [315.] [316.] [317.] [318.] [319.] [320.] [321.] [322.] [323.] [324.] [325.] [326.] [327.] [328.] [329.] [330.] [331.] [332.] [333.] [334.] [335.] [336.] [337.] [338.] [339.] [340.] [341.] [342.] [343.] [344.] [345.] [346.] [347.] [348.] [349.]