Publications Repository - Helmholtz-Zentrum Dresden-Rossendorf

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41421 Publications

Wire-mesh sensor data for vertical upward gas-liquid flow

Kipping, R.; Schleicher, E.

This data set contains the processed data of the wire-mesh sensor, obtained in a flow loop with inner diameter of 50 mm with a vertical section of 3 m length. The dimension of the sensor is 16x16 wires and a lateral wire distance of 3.125 mm. Each file contains data of 60 s measurement time with 10 kHz samling frequency.

The set up was operated with pressurized air and deionized water. The experimental matrix contains meausrements at different superficial velocities of the gas and the liquid. Thus different flow pattern are observed. For injection of the gas two different types have been used. In the first set of experiments (files 1- 61, *injection1*) the gas was injected with a small tube with inner diameter of 9 mm. In the second set of experiments (files 101 - 151, *injection2*) the gas was injected with a small pipe of 25 mm inner diameter.

An overview of the experimental conditions for the two sets of experiments are summarized in the excel file. The corresponding *.zip files contain the processed data. These are void files, which contain the gas holdup in each crossing point and for all time steps of the measurement stack. Additionally the time averaged cross sectional gas holdup distribution (*.epsxy), the time averaged radial gas holdup (*.epsrad_20) and the cross sectional average gas holdup at each time step (*.epst) is provided,

Keywords: two-phase flow; wire-mesh sensor

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Permalink: https://www.hzdr.de/publications/Publ-37954
Publ.-Id: 37954


Introducing Relative Encounter Rates: a scale-invariant home range measure of animal interaction

Saraiva De Menezes, J. F.; Fleming, C. H.; Martinez Garcia, R.; Belant, J. L.; Medici, E. P.; Morato, R. G.; Calabrese, J.

Animal encounters are key components of population dynamics, community dynamics, and
evolutionary processes. Consequently, measuring encounter rates (i.e. encounters per time) can be
insightful. Encounter rates can be measured from animal tracking data, using metrics that can be split
into two groups. The first group consists of trajectory-based metrics, i.e. measures based on serial
records of animal locations. This first group includes PROX, the number of observed per number of
samples. The second group, in contrast, consists of metrics based on home range overlap, including
the Bhattacharyya coefficient (BC). In this study, we argue both types of metrics are limited.
Trajectory-based metrics are direct measures of encounter rates but have statistical estimation
issues due to their dependency on the frequency of location sampling. Meanwhile, home-rangebased metrics are statistically sound but are not proportional to encounter rates. To overcome both
challenges, we proposed a new metric, Relative Encounter Rate (RER). RER increases linearly with the
number of encounters and does not depend on the frequency of sampling (i.e. it is scale-invariant). In
an individual-based simulation, we measured how RER, BC, and PROX relative error under different
sample sizes and sampling frequencies. Further, we compared these metrics in three empirical case
studies. We tested Jaguars for polygyny, deforestation effects on tapir connectivity, and an extension
of the dearest enemy hypothesis with brown bears. We also compared partner hierarchy according
to BC and RER in Jaguar mating clusters. In the simulation study, we found PROX overestimates the
encounter rate when data has a low sampling frequency. The simulation also indicates BC
overestimated encounters. Furthermore, PROX led to false positives in the Tapir and Bear case
studies. In addition, PROX was incapable of detecting many individual relationships in the jaguar
polygyny study. RER does not depend on sampling frequency (contrary to PROX) or sample size
(contrary to BC). We discuss further hypotheses to test with RER and argue RER can enable ecologists
to analyze encounters with a level of detail adequate to their importance, leading to a better
understanding of how individual behaviors influence population and community dynamics.

  • Open Access Logo Poster
    GRC Movement Ecology Conference, 28.05.-02.06.2023, Renaissance Tuscany Il Ciocco, Italy

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Permalink: https://www.hzdr.de/publications/Publ-37953
Publ.-Id: 37953


Knowledge and technology transfer in and beyond mineral exploration

Kesselring, M.; Kirsch, M.; Wagner, F.; Gloaguen, R.

In natural sciences, mineral exploration has a high network centrality. For industries with high technological- and knowledge proximity, transfer effects are an important function for innovation. Despite the high level of proximity between mineral exploration and other natural sciences, scholars hardly examine transfers from and to mineral exploration. This paper analyzes obstacles and mechanisms of transfer effects in and from mineral exploration and finds answers on how to institutionalize knowledge and technology transfer (KTT). The study employs a qualitative research design. The underlying database consists of 16 expert interviews, from the fields of natural science. The results show that KTT between areas as diverse as mineral exploration, healthcare, and arts are possible. A lack of interdisciplinary exchange and rigid scientific structures is the main inhibitor of KTT. Before this study, evidence for KTT from and to smaller industries is mostly anecdotal. The study is among the few, which investigates KTT concerning functional transfer opportunities.

Keywords: Knowledge transfer; Technology transfer; Mineral exploration; Natural sciences

Permalink: https://www.hzdr.de/publications/Publ-37952
Publ.-Id: 37952


Effect of carbon content on electronic structure of uranium carbides

Butorin, S. M.; Bauters, S.; Amidani, L.; Beck, A.; Rossberg, A.; Weiss, S.; Vitova, T.; Kvashnina, K.; Tougait, O.

The electronic structure of UC (x = 0.9, 1.0, 1.1, 2.0) was studied by means of x-ray absorption spectroscopy (XAS) at the C K edge and measurements in the high energy resolution fluorescence detection (HERFD) mode at the U and edges. The full-relativistic density functional theory calculations taking into account the Coulomb interaction U and spin-orbit coupling (DFT+U+SOC) were also performed for UC and UC. While the U HERFD-XAS spectra of the studied samples reveal little difference, the U HERFD-XAS spectra show certain sensitivity to the varying carbon content in uranium carbides. The observed gradual changes in the U HERFD spectra suggest an increase in the C 2p-U 5f charge transfer, which is supported by the orbital population analysis in the DFT+U+SOC calculations, indicating an increase in the U 5f occupancy in UC as compared to that in UC. On the other hand, the density of states at the Fermi level were found to be significantly lower in UC, thus affecting the thermodynamic properties. Both the x-ray spectroscopic data (in particular, the C K XAS measurements) and results of the DFT+U+SOC calculations indicate the importance of taking into account U and SOC for the description of the electronic structure of actinide carbides.

Related publications

Permalink: https://www.hzdr.de/publications/Publ-37950
Publ.-Id: 37950


Influence of the cement additive PBTC on aquatic uranium(VI) speciation and retention on cementitious material

Wollenberg, A.; Acker, M.; Kretzschmar, J.; Schmeide, K.; Tsushima, S.; Chiorescu, I.; Krüger, S.

The ingress of water into an underground nuclear repository, described as a worst-case scenario, can lead to the degradation of cement-based engineered barriers and thus to the release of organic cement additives that can affect radionuclide immobilisation. The additive 2-phosphonobutane-1,2,4-tricarboxylic acid (PBTC) is one of the most commonly used long-term retarders in cement, and also used as a corrosion inhibitor in reinforced concrete and steel. PBTC
is an organophosphonate ligand with one phosphonate and three carboxyl groups [1]. These functional groups make PBTC an effective dispersant and strong complexing agent for various metal ions (e.g. Ca2+, Al3+, Fe3+). However, neither the complexation of radionuclides by PBTC nor the influence of PBTC on radionuclide retention in cement phases has been investigated.
Therefore, both the complexation of U(VI) with PBTC in solution (binary system) and the influence of PBTC on the U(VI) retention by cementitious materials (ternary system) were investigated for the first time. The U(VI) complexation studies were performed by different series varying the pH from 2 to 11 and/or the U(VI) to PBTC ratio. The structure-sensitive methods NMR, IR and Raman spectroscopy were used to characterize the complex structure. Complementary DFT calculations were carried out. The U(VI) speciation in presence of PBTC was determined by UV-Vis and TRLFS spectroscopy. In the case of PBTC excess, soluble complex species are formed up to pH >10, which is relevant for cementitious systems due to degradation processes. For the U(VI) retention studies both calcium (aluminate) silicate hydrate (C-(A-)S-H) phases of different compositions, representing different cement degradation stages, as well as hardened cement paste were applied. TRLFS was applied to characterize the U(VI) binding. The PBTC retention was quantified by 1H and 31P solution NMR.

Keywords: uranium; 2-phosphonobutane-1,2,4-tricarboxylic acid; complexation; stability constants; cement; retention; spectroscopy

  • Lecture (Conference)
    Joint 6th International Workshop on Mechanisms and Modelling of Waste / Cement Interactions, 20.-22.11.2023, Prague, Czech Republic

Permalink: https://www.hzdr.de/publications/Publ-37949
Publ.-Id: 37949


Structural identification of aquatic U(VI)-PBTC complexes by spectroscopic investigations

Wollenberg, A.; Kretzschmar, J.; Tsushima, S.; Krüger, S.; Acker, M.; Taut, S.; Stumpf, T.

In a nuclear waste repository, cement-based materials are to be used for waste conditioning and as an engineered barrier. The ingress of water into the nuclear waste repository, described as a worst-case scenario, leads to increased aging and degradation of the concrete. These processes are associated with a leaching of diverse organic substances usually added to the cement to realize the desired physicochemical and mechanical properties of the cement-based materials. The impact of the additives is based on their excellent ability to complex metal ions. Consequently, the complexation behavior of such additives towards radionuclides (RN) and thus their impact on RN mobilization and migration into the environment is essential for a comprehensive risk assessment. One of the additives commonly used for long-term retardation of cement hardening is 2-phosphonobutane-1,2,4-tricarboxylic acid (PBTC).
PBTC is a polyfunctional ligand possessing three carboxyl groups and one phosphonate group, which have been shown to make PBTC a strong complexing agent for various metal ions (e.g. Ca2+, Zn2+, Al3+, Fe3+) [1,2]. However, to date, there are no studies on PBTC interaction with radionuclides. Therefore,
the complexation of PBTC with U(VI) was investigated for the first time, using different spectroscopic methods over a wide pH range (2 through 11) to identify and characterize possible complex species.
U(VI)-PBTC species with solubility as high as 100 mM were observed throughout the entire pH range studied, especially when PBTC is in excess. This allowed the convenient application of structuresensitive methods such as NMR, IR, and Raman spectroscopies. Furthermore, time-resolved laserinduced
fluorescence spectroscopy (TRLFS) and UV-Vis titration studies provided insight into U(VI)–PBTC system’s speciation.

Keywords: uranium(VI); 2-phosphonobutane-1,2,4-tricarboxylic acid; complexation; stability constants; spectroscopy

  • Lecture (Conference)
    18th International Conference on the Chemistry and Migration Behaviour of Actinides and Fission Products in the Geosphere - Migration 2023, 24.-29.09.2023, Nantes, France

Permalink: https://www.hzdr.de/publications/Publ-37948
Publ.-Id: 37948


Characterisation of highly soluble U(VI)-PBTC complexes

Wollenberg, A.; Kretzschmar, J.; Schmeide, K.; Acker, M.; Taut, S.; Stumpf, T.

Organophosphonates are used multipurpose in the chemical industry. One of the most commonly used organophosphonates is 2-phosphonobutane-1,2,4-tricarboxylic acid (PBTC).[1] The functional groups of PBTC consist of one phosphonate and three carboxylate groups, which make PBTC not only an effective dispersant, but also a very good complexing agent for various metal ions (e.g. Ca2+, Al3+, Fe3+).[2,3] Due to these properties, PBTC is used, for example, as an efficient long-term retarder in cement, as a corrosion inhibitor in reinforced concrete and steel, or as a scale inhibitor in water treatment plants or cooling water circulation systems.[4,5] However, this ubiquitous use can also lead to anthropogenic discharge into the environment, where PBTC can complex heavy metals or even radionuclides. Complexation can increase the solubility of metal ions and thus their bioavailability. As a result, there is an increased risk of toxic metal ions being distributed in the environment and thus also being absorbed into the human food chain.
However, to date there have been no studies on the complexation of PBTC with radionuclides. For this reason, the complexation of PBTC with U(VI) in the pH range from 1 to 11 was investigated for the first time using various spectroscopic methods. The studies were performed by different series varying the pH or the U(VI) to PBTC ratio. For the methods used, U(VI) concentrations in the mM range were employed, which was possible due to the very good water solubility of the U(VI)-PBTC complexes. The structure-sensitive methods NMR, IR and Raman spectroscopy were used to characterise the complex structure. Supporting DFT calculations were carried out. The stability constants of the complex species were determined by UV-Vis spectroscopy. By applying the different spectroscopic methods, it was possible to determine chelation of U(VI) by the phosphonate group and one of the carboxyl groups. Furthermore, by means of factor analysis, the distribution of complex species as well as the complexation constants could be determined for the first time. Therefore, the results of this study make it possible to evaluate the risk of PBTC entering the environment in relation to the radionuclide uranium.

Keywords: uranium(VI); 2-phosphonobutane-1,2,4-tricarboxylic acid; complexation; stability constants; spectroscopy

  • Lecture (Conference)
    5th International Caparica Conference on Pollutant Toxic Ions and Molecules (PTIM) 2023, 06.-09.11.2023, Caparica, Portugal

Permalink: https://www.hzdr.de/publications/Publ-37947
Publ.-Id: 37947


Magnetic structure and phase diagram of the Heisenberg-Ising spin chain antiferromagnetic PbCo2V2O8

Puzniak, K.; Aguilar-Maldonado, C.; Feyerherm, R.; Prokes, K.; Islam, A. T. M. N.; Skourski, Y.; Keller, L.; Lake, B.

The effective spin-1/2 antiferromagnetic Heisenberg-Ising chain materials, ACo2V2O8, A = Sr, Ba, are a rich source of exotic fundamental phenomena and have been investigated for their model magnetic properties both in zero and nonzero magnetic fields. Here we investigate a new member of the family, namely, PbCo2V2O8. We synthesize powder and single-crystal samples of PbCo2V2O8 and determine its magnetic structure using neutron diffraction. Furthermore, the magnetic field/temperature phase diagrams for a magnetic field applied along the c, a, and [110] crystallographic directions in the tetragonal unit cell are determined via magnetization and heat capacity measurements. A complex series of phases and quantum phase transitions are discovered that strongly depend on both the magnitude and direction of the field. Our results show that PbCo2V2O is an effective spin-1/2 antiferromagnetic Heisenberg-Ising chain with properties that are, in general, comparable to those of SrCo2V2O8 and BaCo2V2O8. One interesting departure from the results of these related compounds is, however, the discovery of a new field-induced phase for the field direction H ӏӏ [110].

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Permalink: https://www.hzdr.de/publications/Publ-37943
Publ.-Id: 37943


300 mm CMOS-compatible superconducting HfN and ZrN thin films for quantum applications

Potjan, R.; Wislicenus, M.; Ostien, O.; Hoffmann, R.; Lederer, M.; Reck, A.; Emara, J.; Roy, L.; Lilienthal-Uhlig, B.; Wosnitza, J.

The rising interest in increased manufacturing maturity of quantum processing units is pushing the development of alternative superconducting materials for semiconductor fab process technology. However, these are often facing CMOS process incompatibility. In contrast to common CMOS materials, such as Al, TiN, and TaN, reports on the superconductivity of other suitable transition-metal nitrides are scarce, despite potential superiority. Here, we demonstrate fully CMOS-compatible fabrication of HfN and ZrN thin films on state-of-the-art 300mm semiconductor process equipment, utilizing reactive DC magnetron sputtering on silicon wafers. Measurement of mechanical stress and surface roughness of the thin films demonstrates process compatibility. We investigated the materials phase and stoichiometry by structural analysis. The HfN and ZrN samples exhibit superconducting phase transitions with critical temperatures up to 5.84 and 7.32 K, critical fields of 1.73 and 6.40 T, and coherence lengths of 14 and 7 nm, respectively. A decrease in the critical temperature with decreasing film thickness indicates mesoscopic behavior due to geometric and grain-size limitations. The results promise a scalable application of HfN and ZrN in quantum computing and related fields.

  • Open Access Logo Applied Physics Letters 123(2023), 172602
    Online First (2023) DOI: 10.1063/5.0176060

Permalink: https://www.hzdr.de/publications/Publ-37942
Publ.-Id: 37942


Local-symmetry-sensitive elastic softening in the Kramers doublet system Y1−xNdxCo2Zn20

Ishii, I.; Umeno, T.; Yamamoto, R.; Onimaru, T.; Suzuki, T.; Araki, K.; Miyata, A.; Zherlitsyn, S.; Wosnitza, J.

We investigated the elastic properties of Y1−xNdxCo2Zn20 with localized Nd f electrons and ground-state Kramers doublet. All longitudinal and transverse moduli of NdCo2Zn20 (x = 1) show an elastic softening below 50 K accompanied by a minimum around 2.5 K. The softening, which is robust to magnetic fields up to 8 T, is not observed for samples with Nd concentrations of x = 0.19, 0.05, and 0. In localized f electron systems, elastic softening from high temperatures is often understood by crystal electric field effects; however, this cannot explain the behavior in NdCo2Zn20. Our experimental and calculated results reveal that the softening neither is caused by a phonon contribution, a Nd3+ single-site effect, nor a magnetic interaction. We conclude that the softening is due to a local-symmetry-sensitive electronic state in NdCo2Zn20.

Permalink: https://www.hzdr.de/publications/Publ-37941
Publ.-Id: 37941


Giant irreversibility of the inverse magnetocaloric effect in the Ni47Mn40Sn12.5Cu0.5 Heusler alloy

Kamantsev, A. P.; Koshkidko, Y. S.; Bykov, E.; Gottschall, T.; Gamzatov, A. G.; Aliev, A. M.; Varzaneh, A. G.; Kameli, P.

Direct studies of the adiabatic temperature change (ΔTad) in the Ni47Mn40Sn12.5Cu0.5 Heusler alloy in steady magnetic fields up to 8 T by the extraction method and in pulsed magnetic fields up to 50 T were carried out in this paper. The alloy Ni47Mn40Sn12.5Cu0.5 demonstrates a magnetostructural phase transition (MSPT) of the first order in the 254–283 K temperature range as well as a second order phase transition near the Curie temperature TC = 313 K. An inverse magnetocaloric effect (MCE) was found in the region of the MSPT, and it reaches the maximum value ΔTad = -12 K in 20 T at the initial temperature T0 = 275 K. The irreversible part of the MCE reached ΔTir = -10 K when the field is completely removed. We consider the dynamics of the MCE in the vicinity of the MSPT and discuss the mechanisms that cause the giant irreversibility of the MCE as well as the possibilities of its application in hybrid cooling systems.

Permalink: https://www.hzdr.de/publications/Publ-37940
Publ.-Id: 37940


Characterization of domain wall patterns in granular antiferromagnetic Cr2O3 films

Pylypovskyi, O.; Hedrich, N.; Tomilo, A.; Kosub, T.; Wagner, K.; Hübner, R.; Shields, B.; Sheka, D.; Faßbender, J.; Maletinsky, P.; Makarov, D.

Cr2O3 is an exceptional antiferromagnet with an easy axis of anisotropy that exhibits a magnetoelectric effect at room temperature [1]. Although there are technological challenges to use it for applications because of the relatively low bulk Neel temperature of TN = 308 K, there are demonstrations that TN can be substantially enhanced by strain in thin films. The morphology and growth procedure of such samples allow the appearance of flexomagnetic effects and pinning of domain walls at grain boundaries [2,3].

Here, we propose a material model of granular antiferromagnetic films and apply it to maze-like domain patterns in thin Cr2O3 samples [4]. The domain pattern is obtained by means of the nitrogen vacancy magnetometry and compared with spin-lattice simulations. We analyze the statistics of the size and self-similarity of the domain wall patterns to correlate the experimental measurements with the parameters of the theoretical model and compare the domain wall patterns with predictions made by a machine learning approach. The estimated inter-grain coupling is characterized by a substantial reduction of the effective exchange coupling to about 10% of the bulk value, with a wide standard deviation. Based on the material model, we provide design rules for the granular AFM recording media.

Keywords: Cr2O3; granular antiferromagnet

  • Lecture (others)
    WEH Seminar, 02.-05.01.2024, Bad Honnef, Germany

Permalink: https://www.hzdr.de/publications/Publ-37939
Publ.-Id: 37939


Foundational Competencies and Responsibilities of a Research Software Engineer

Goth, F.; Alves, R.; Braun, M.; Jael Castro, L.; Chourdakis, G.; Christ, S.; Cohen, J.; Erxleben, F.; Grad, J.-N.; Hagdorn, M.; Hodges, T.; Juckeland, G.; Kempf, D.; Lamprecht, A.-L.; Linxweiler, J.; Schwarzmeier, M.; Seibold, H.; Philipp Thiele, J.; von Waldow, H.; Wittke, S.

The term Research Software Engineer, or RSE, emerged a little over 10 years ago as a way to represent
individuals working in the research community but focusing on software development. The term has been widely
adopted and there are a number of high-level definitions of what an RSE is. However, the roles of RSEs vary
depending on the institutional context they work in. At one end of the spectrum, RSE roles may look similar to
a traditional research role. At the other extreme, they resemble that of a software engineer in industry. Most
RSE roles inhabit the space between these two extremes. Therefore, providing a straightforward, comprehensive
definition of what an RSE does and what experience, skills and competencies are required to become one is
challenging. In this community paper we define the broad notion of what an RSE is, explore the different types
of work they undertake, and define a list of fundamental competencies as well as values that define the general
profile of an RSE. On this basis, we elaborate on the progression of these skills along different dimensions, looking
at specific types of RSE roles, proposing recommendations for organisations, and giving examples of future
specialisations. An appendix details how existing curricula fit into this framework.

Keywords: research software engineering; curriculum design; training; learning; competencies; certification

Permalink: https://www.hzdr.de/publications/Publ-37938
Publ.-Id: 37938


Helmholtz Metadata Collaboration - Facilitating FAIR metadata in Helmholtz

Schaller, T.; Günter, G.; Kubin, M.; Özkan, Ö.; Rau, F.; Steinmeier, L.

Data are an essential part of every scientific endeavour. An efficient and future oriented research data management is therefore essential in order to ensure long-term availability of the generated data. This in turn ensures the reproducibility of scientific results. In order to facilitate FAIR data management within the Helmholtz community the incubator platform “Helmholtz Metadata Collaboration (HMC)” was established.

HMC develops and provides services, tools and trainings to support and improve FAIR (meta)data management in the Helmholtz Association and aligns these approaches with national and international approaches and initiatives (e.g. RDA, EOSC, NFDI) to ensure compatibility with international research communities.

To achieve this goal, HMC builds its work along three strategic areas: (1) Assessing and monitoring the state of FAIR data across Helmholtz, (2) Facilitating the connectivity of Helmholtz research data, and (3) Transforming (meta)data recommendations into implementations. At the centres, HMC supports research communities and data professionals with six research-field specific hubs: At HZDR HMC is represented locally by a unit dedicated to research field Energy and remotely by a unit for research field Matter. In our poster we will illustrate how research and data professional communities at HZDR can benefit from HMC's services, tools and trainings.

Keywords: Helmholtz-Zentrum Dresden-Rossendorf; HZDR data management day; metadata management; Helmholtz Metadata Collaboration

  • Poster
    HZDR Data Management Day, 21.11.2023, Dresden, Dresden

Permalink: https://www.hzdr.de/publications/Publ-37937
Publ.-Id: 37937


Influence of selected organics on the retention of uranium(VI) by calcium-(aluminate-)silicate-hydrate phases

Schmeide, K.; Kretzschmar, J.; Huittinen, N. M.

Most underground nuclear waste disposal concepts envisage the extensive use of cementitious materials in the geo-engineered barrier as a buffer and borehole sealing material and to ensure the mechanical stability of disposal systems. In order to assess the radionuclide (RN) retention potential of these barrier materials, it is necessary to study the impact of various repository relevant conditions that will evolve over time, such as changed pH values, increased ionic strength, elevated temperatures, or the release of organic components. The U(VI) retention by calcium (aluminate) silicate hydrate (C-(A-)S-H) phases, forming owing to Al-rich additives in cement formulations, was studied for samples with C/S molar ratios of 0.8, 1.2, and 1.6, representing different alteration stages of concrete, and with increasing A/S molar ratios of 0, 0.06, and 0.18 in each series, with special focus on the presence of organics. The latter thereby comprise gluconate (GLU), 2-phosphonobutane-1,2,4,-tricarboxylate (PBTC), and a mixture of cellulose degradation products (CDP) obtained from dry radiolysis (dose rate 0.6 kGy/h, absorbed dose ~ 1.37 MGy) followed by hydrolysis in artificial cement water (pH > 13, anoxic conditions) provided by project partners within the CORI framework. Complementary analytical techniques were applied to address the different specific aspects of the cement / organics / RN ternary systems. 27Al and 29Si magic angle spinning (MAS) nuclear magnetic resonance (NMR) spectroscopy and powder X-ray diffraction (XRD) were applied to determine the bulk structure and composition of the synthesized C-(A-)S-H phases. 13C-, and in case of PBTC also 31P-, MAS NMR measurements aimed at localization and speciation of the organic components involved [1]. 1H and 31P solution NMR of the aqueous phase allowed for quantification of the organics’ fraction removed from solution and hence associated with the solid phase. Retained U(VI) species were identified by time-resolved laser-induced luminescence spectroscopy (TRLFS). Zeta-potential measurements were conducted to study the organics’ influence on the surface charge and, upon changing the order of mixing the individual components of the ternary systems (e.g., C-(A-)S-H phases synthesized in absence or presence of U(VI) and/or organics), along with results from spectroscopies, to derive mechanistic understanding of retention processes as well as surface complex models.

Keywords: uranium; C-S-H; C-A-S-H; hydrothermal synthesis; luminescence; spectroscopy

  • Lecture (Conference)
    Joint 6th International Workshop on Mechanisms and Modelling of Waste / Cement Interactions, 20.-22.11.2023, Prague, Czech Republic

Permalink: https://www.hzdr.de/publications/Publ-37936
Publ.-Id: 37936


Von Hochleistungslasern und Plasmen zum kompakten Protonen-Beschleuniger für radiobiologische Studien

Metzkes-Ng, J.

Die Methode zur Verstärkung sogenannter gechirpter Laserpulse wurde im Jahr 2018 mit dem Physik-Nobelpreis ausgezeichnet. Basierend auf dieser Methode lassen sich nun Laseranlagen mit Leistungen im Bereich von mehreren Petawatt realisieren. Werden die ultrakurzen Laserpulse eines solchen Hochleistungslasers auf dünne Metall- oder Plastikfolien fokussiert, können auf einer Strecke von wenigen Mikrometern intensive Ionenpulse beschleunigt werden. Bei der Wechselwirkung von Laserpuls und Folie entsteht dabei ein Plasma, in dem die Laserenergie zuerst auf schnelle Elektronen übertragen wird. Deren kollektive Felder bewirken dann die Beschleunigung von Ionen – das Prinzip eines Laser-Plasma-Beschleunigers. Besonders effektiv ist dieser Prozess für Protonen, die sich aktuell auf Energien jenseits der 100 MeV beschleunigen lassen.
Neben der Möglichkeit, kompakte Beschleuniger bauen zu können, punkten Laser-Plasma-Beschleuniger durch eine weitere besondere Eigenschaft: ihre Strahlen sind sehr intensiv und in Pikosekundenlänge gepulst, sodass ultrahohe Dosisleistungen erreicht werden. Davon kann die translationalen Krebsforschung profitieren – also jenes Forschungsgebiet, in dem Resultate der Grundlagenforschung auf neue Ansätze zur Prävention, Diagnostik und Behandlung von Krebserkrankungen übertragen werden. Die radiobiologische Wirkung stark gepulster Strahlung stellt hier nämlich eine aktuell intensiv diskutierte Fragestellung dar.
An der Realisierung einer Plattform für Radiobiologie mit ultrahohen Dosisraten basieren auf einem Laser-Plasma-Beschleuniger wird am Helmholtz-Zentrum Dresden—Rossendorf seit mehr als 15 Jahren gearbeitet. 2020 ist es hier nun erstmals gelungen, Tumoren in einem Kleintiermodell kontrolliert mit laserbeschleunigten Protonen zu bestrahlen. Bisherige Untersuchungen beschränkten sich auf Zellkulturen. Über viele Jahre wurden dazu der Laser, der Beschleunigungsmechanismus und das radiobiologische Modell studiert und optimiert, um bisherige Limitierungen bezüglich Protonenenergie und Beschleunigerstabilität zu überwinden und schließlich den Schritt von der Petrischale hin zum lebenden Modell wagen zu können. Die Ergebnisse markieren einen Meilenstein für die Entwicklung zuverlässiger Laser-Plasma-Beschleuniger und ermöglichen neuartige radiobiologische Studien.

Keywords: Laser-Protonenbeschleunigung

  • Invited lecture (Conferences)
    Festkolloquium 25 Jahre Medizinische Physik an der Martin-Luther-Universität Halle-Wittenberg, 23.11.2023, Halle (Saale), Deutschland

Permalink: https://www.hzdr.de/publications/Publ-37935
Publ.-Id: 37935


EOSC EVERSE: Paving the way towards a European Virtual Institute for Research Software Excellence

Psomopoulos, F.; Juckeland, G.; Stewart, G. A.; Roiser, S.; Capella-Gutierrez, S.; Portell-Silva, L.; Bos, P.; Maassen, J.; Vuillaume, T.; Chue Hong, N.; Garijo, D.; Tedds, J.; Doglioni, C.; Goble, C.

Extended abstract of the EOSC EVERSE project (https://everse.software/), submitted for presentation in the International Research Software Engineering Research (IRSER) Community Meetup in January 2024 (https://www.software.ac.uk/news/international-research-software-engineering-research-irser-community-meetup)

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Permalink: https://www.hzdr.de/publications/Publ-37934
Publ.-Id: 37934


ALDH1A1 drives prostate cancer metastases and radioresistance by interplay with AR- and RAR-dependent transcription

Gorodetska, I.; Offerman, A.; Püschel, J.; Lukiyanchuk, V.; Gaete, D.; Kurzyukova, A.; Freytag, V.; Fjeldbo, C.; Di Gaetano, S.; Schwarz, F.; Patil, S.; Borkowetz, A.; Erb, H.; Baniahmad, A.; Mircetic, J.; Lyng, H.; Löck, S.; Linge, A.; Lange, T.; Knopf, F.; Wielockx, B.; Krause, M.; Perner, S.; Dubrovska, A.; Haider, M.-T.

Rationale: Current therapies for metastatic osseous disease frequently fail to provide a durable treatment response. To date, there are only limited therapeutic options for metastatic prostate cancer, the mechanisms that drive the survival of metastasis-initiating cells are poorly characterized, and reliable prognostic markers are missing. A high aldehyde dehydrogenase (ALDH) activity has been long considered a marker of cancer stem cells (CSC). Our study characterized a differential role of ALDH1A1 and ALDH1A3 genes as regulators of prostate cancer progression and metastatic growth.
Methods: By genetic silencing of ALDH1A1 and ALDH1A3 in vitro, in xenografted zebrafish and murine models, and by comparative immunohistochemical analyses of benign, primary tumor, and metastatic specimens from patients with prostate cancer, we demonstrated that ALDH1A1 and ALDH1A3 maintain the CSC phenotype and radioresistance and regulate bone metastasis-initiating cells. We have validated ALDH1A1 and ALDH1A3 as potential biomarkers of clinical outcomes in the independent cohorts of patients with PCa. Furthermore, by RNAseq, chromatin immunoprecipitation (ChIP), and biostatistics analyses, we suggested the molecular mechanisms explaining the role of ALDH1A1 in PCa progression.
Results: We found that aldehyde dehydrogenase protein ALDH1A1 positively regulates tumor cell survival in circulation, extravasation, and metastatic dissemination, whereas ALDH1A3 plays the opposite role. ALDH1A1 and ALDH1A3 are differentially expressed in metastatic tumors of patients with prostate cancer, and their expression levels oppositely correlate with clinical outcomes. Prostate cancer progression is associated with the increasing interplay of ALDH1A1 with androgen receptor (AR) and retinoid receptor (RAR) transcriptional programs. Polo-like kinase 3 (PLK3) was identified as a transcriptional target oppositely regulated by ALDH1A1 and ALDH1A3 genes in RAR and AR-dependent manner. PLK3 contributes to the control of prostate cancer cell proliferation, migration, DNA repair, and radioresistance. ALDH1A1 gain in prostate cancer bone metastases is associated with high PLK3 expression.
Conclusion: This report provides the first evidence that ALDH1A1 and PLK3 could serve as biomarkers to predict prostate cancer metastatic dissemination and radiotherapy resistance in patients with prostate cancer and be potential therapeutic targets to eliminate metastasis-initiating and radioresistant tumor cell populations.

Keywords: prostate cancer; bone metastases; cancer stem cells; aldehyde dehydrogenase; RARA; androgen receptor; retinoic acid; radiotherapy

Permalink: https://www.hzdr.de/publications/Publ-37932
Publ.-Id: 37932


NiGe formation on thin Ge films by flash lamp annealing: electrical properties

Begeza, V.; Rebohle, L.; Stöcker, H.; Mehner, E.; Hübner, R.; Zhou, S.

Flash lamp annealing (FLA) is an ultra-short annealing method which excellently meets the requirements of thin film processing and has already been used in microelectronics. Due to the relatively high hole mobility, thin Ge layers are highly interesting as a transistor channel material or generally as a functional layer both in CMOS technology and in the field of low-cost electronics. One possibility to realize ohmic contacts with low contact resistance is the use of metal germanides, especially the stoichiometric NiGe phase.
In this work, NiGe contacts on thin Ge films were fabricated by magnetron sputtering followed by FLA. The evolution of microstructure with increasing thermal budget was traced by transmission electron microscopy, energy-dispersive X-ray spectroscopy, and X-ray diffraction. The electrical measurements focus on the determination of contact resistance by the circular transfer length method (cTLM). The contacts were fabricated by two different approaches, and the influence of different process steps on layer morphology and the uncertainty of the measurement was studied.

Keywords: germanium; nickel germanide; thin films; sputtering; flash lamp annealing; circular transfer length

Related publications

  • Lecture (Conference)
    E-MRS SPRING MEETING 2023, 29.05.-02.06.2023, Strasbourg, Frankreich

Permalink: https://www.hzdr.de/publications/Publ-37931
Publ.-Id: 37931


NiGe formation on thin Ge films by flash lamp annealing

Begeza, V.; Rebohle, L.; Stöcker, H.; Mehner, E.; Hübner, R.; Zhou, S.

In this work, NiGe contacts on thin Ge films were fabricated by magnetron sputtering followed by flash lamp annealing (FLA). The evolution of microstructure with increasing thermal budget was traced by transmission electron microscopy, energy-dispersive X-ray spectroscopy and X-ray diffraction. The film sheet resistance, the free charge carrier mobility and concentration, and the contact resistance were measured by the four-point-probe method, by Hall effect measurements, and by the circular transfer length method, respectively. Based on this data, the formation process of NiGe contacts during FLA is described, which passes through a stage of Ni-rich phases with high electrical resistivity, before the final stoichiometric NiGe phase is formed.

Keywords: germanium; nickel germanide; thin films; sputtering; flash lamp annealing; circular transfer length

Related publications

  • Lecture (Conference)
    Nutzertreffen Heissprozesse und Ionenimplantation, 10.-11.05.2023, Erlangen, Deutschland

Permalink: https://www.hzdr.de/publications/Publ-37930
Publ.-Id: 37930


Data publication: Cadmium sorption on alumina nanoparticles, and mixtures of alumina and smectite: An experimental and modelling study

Mayordomo, N.; Missana, T.; Alonso, U.

Data is shown in origin, the thermodynamic database of Cd is adapted for Chess V2 software

Keywords: Cd; sorption model; retention; immobilization; heavy metals; Al2O3

Related publications

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Permalink: https://www.hzdr.de/publications/Publ-37929
Publ.-Id: 37929


Learning Crop-Type Mapping From Regional Label Proportions in Large-Scale SAR and Optical Imagery

La Rosa, L.; Oliveira, D.; Ghamisi, P.

The application of deep learning (DL) algorithms to Earth observation (EO) in recent years has enabled substantial progress in fields that rely on remotely sensed data. However, given the data scale in EO, creating large datasets with pixel-level annotations by experts is expensive and highly time-consuming. In this context, priors are seen as an attractive way to alleviate the burden of manual labeling when training DL methods for EO. For some applications, those priors are readily available. Motivated by the great success of contrastive-learning methods for self-supervised feature representation learning in many computer-vision tasks, this study proposes an online deep clustering method using crop label proportions as priors to learn a sample-level classifier based on government crop-proportion data for a whole agricultural region. We evaluate the method using two large datasets from two different agricultural regions in Brazil. Extensive experiments demonstrate that the method is robust to different data types [synthetic-aperture radar (SAR) and optical images], reporting higher accuracy values considering the major crop types in the target regions. Thus, it can alleviate the burden of large-scale image annotation in EO applications.

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Permalink: https://www.hzdr.de/publications/Publ-37928
Publ.-Id: 37928


Leveraging involution and convolution in an explainable building damage detection framework

Teymoor Seydi, S.; Hasanlou, M.; Chanussot, J.; Ghamisi, P.

Timely and accurate building damage mapping is essential for supporting disaster response activities. While RS satellite imagery can provide the basis for building damage map generation, detection of building damages by traditional methods is generally challenging. The traditional building damage mapping approaches focus on damage mapping based on bi-temporal pre/post-earthquake dataset extraction information from bi-temporal images, which is difficult. Furthermore, these methods require manual feature engineering for supervised learning models. To tackle the abovementioned limitation of the traditional damage detection frameworks, this research proposes a novel building damage map generation approach based only on post-event RS satellite imagery and advanced deep feature extractor layers. The proposed DL based framework is applied in an end-to-end manner without additional processing. This method can be conducted in five main steps: (1) pre-processing, (2) model training and optimization of model parameters, (3) damage mapping generation, (4) accuracy assessment, and (5) visual explanations of the proposed method’s predictions. The performance of the proposed method is evaluated by two real-world RS datasets that include Haiti-earthquake and Bata-explosion. Results of damage mapping show that the proposed method is highly efficient, yielding an OA of more than 84%, which is superior to other advanced DL-based damage detection methods.

Permalink: https://www.hzdr.de/publications/Publ-37927
Publ.-Id: 37927


Explainable Artificial Intelligence (XAI) Model for Earthquake Spatial Probability Assessment in Arabian Peninsula

Ratiranjan, J.; Abdallah, S.; Rami, A.-R.; Biswajeet, P.; Mohamed, B. A. G.; Mohamad, A. K.; Omid, G.; Ganapathy, P. G.; Ghamisi, P.

Among all the natural hazards, earthquake prediction is an arduous task. Although many studies have been published on earthquake hazard assessment (EHA), very few have been published on the use of artificial intelligence (AI) in spatial probability assessment (SPA). There is a great deal of complexity observed in the SPA modeling process due to the involvement of seismological to geophysical factors. Recent studies have shown that the insertion of certain integrated factors such as ground shaking, seismic gap, and tectonic contacts in the AI model improves accuracy to a great extent. Because of the black-box nature of AI models, this paper explores the use of an explainable artificial intelligence (XAI) model in SPA. This study aims to develop a hybrid Inception v3-ensemble extreme gradient boosting (XGBoost) model and shapely additive explanations (SHAP). The model would efficiently interpret and recognize factors’ behavior and their weighted contribution. The work explains the specific factors responsible for and their importance in SPA. The earthquake inventory data were collected from the US Geological Survey (USGS) for the past 22 years ranging the magnitudes from 5 Mw and above. Landsat-8 satellite imagery and digital elevation model (DEM) data were also incorporated in the analysis. Results revealed that the SHAP outputs align with the hybrid Inception v3-XGBoost model (87.9% accuracy) explanations, thus indicating the necessity to add new factors such as seismic gaps and tectonic contacts, where the absence of these factors makes the prediction model performs poorly. According to SHAP interpretations, peak ground accelerations (PGA), magnitude variation, seismic gap, and epicenter density are the most critical factors for SPA. The recent Turkey earthquakes (Mw 7.8, 7.5, and 6.7) due to the active east Anatolian fault validate the obtained AI-based earthquake SPA results. The conclusions drawn from the explainable algorithm depicted the importance of relevant, irrelevant, and new futuristic factors in AI-based SPA modeling.

Permalink: https://www.hzdr.de/publications/Publ-37925
Publ.-Id: 37925


Spatially explicit models of population dynamics: a dialogue between statistical physics and ecology.

Martinez Garcia, R.

Theoretical models in ecology often assume well-mixed populations and thus that individuals interact with one another with the same probability regardless of their spatial location. This strong assumption results in mathematically very tractable models, often based on ordinary differential equations for the population size, that have taught us a lot about how populations change over time. However, these models do not account for the fact that populations are spatially structured, which favors interactions between nearby individuals.
In this presentation, I will present some of our recent work investigating the effect of space in shaping population dynamics. First, I will discuss how stochastic spatial models, from lattice models to systems of interacting particles, can provide more accurate descriptions of ecological populations and how to analyze them computationally and analytically. Then, I will use a specific example based on an asymmetric voter model to show how modeling spatial processes can reverse the outcome of species competition predicted by a well-mixed model.

  • Invited lecture (Conferences)
    Autumn Meeting of the Brazilian Physics Society, 21.-25.05.2023, Ouro Preto, MG, Brazil

Permalink: https://www.hzdr.de/publications/Publ-37924
Publ.-Id: 37924


Ecological dynamics with long-range individual interactions: from stochastic individual based models to non-local partial differential equations

Martinez Garcia, R.

A lot of ecological theory relies on ordinary-differential-equation models that assume well-mixed systems and do not incorporate any information about the spatial distribution of organisms. However, ecosystems present spatial heterogeneities at different scales that can impact individual fitness and, ultimately, population dynamics. I will present an alternative approach to describe the spatiotemporal dynamics of a population of interacting agents. To this end, I will consider a system with nonlinear birth-death rates and positive and negative inter-individual interactions acting at different spatial ranges. I will first describe the stochastic, individual-level rules that govern the reproduction and death of each individual. Then, using field-theory techniques, I will derive a non-local partial differential equation for the population density and compare its predictions with those obtained assuming well-mixed populations. Finally, I will discuss the ecological relevance of our results and how this approach can be extended to more complex scenarios.

  • Invited lecture (Conferences)
    Modelling Diffusive Systems 2023: Theory & Biological Applications, 11.-15.09.2023, Edinburgh, United Kingdom

Permalink: https://www.hzdr.de/publications/Publ-37923
Publ.-Id: 37923


To go or not to go? Modeling the decision-making process behind ungulate partial migration

Martinez Garcia, R.

Despite the importance of ungulate migrations, we lack a complete understanding of why some ungulates species migrate and some do not. Moreover, at the population level, some migrate and others remain behind as residents, a phenomenon known as partial migration. Even though progress has been made towards understanding long-term fitness benefits of partial migration, the underlying decision-making process that makes some individuals migrate and others remain within one single range remain unknown. In this presentation I will combine empirical data from three different migrant ungulate species and mathematical modeling to address this question. I will first show that, across these three ungulate species, the number of residents is unrelated to total population size, a pattern predicted by no previous modeling framework. Next, I will introduce a new model of ungulate partial migration wherein individuals probabilistically decide to start migrating based on the intensity of environmental and social cues. Within this modeling framework, residents arise for most parameter combinations and the number of residents is largely invariant with total population size. Therefore, this new model explains the ubiquity of residents in migratory ungulate populations and presents novel patterns to be tested with further data collection.

  • Lecture (Conference)
    European Conference on Ecological Modeling, 03.-07.07.2023, Leipzig, Germany

Permalink: https://www.hzdr.de/publications/Publ-37922
Publ.-Id: 37922


Absorption statistics of movement models with home-ranging behavior: animal-vehicle collisions as a case study.

Martinez Garcia, R.

A lot of ecological theory relies on ordinary-differential-equation models that assume well-mixed systems and do not incorporate any information about the spatial distribution of organisms. However, ecosystems present spatial heterogeneities at different scales that can impact individual fitness and, ultimately, population dynamics. I will present an alternative approach to describe the spatiotemporal dynamics of a population of interacting agents. To this end, I will consider a system with nonlinear birth-death rates and positive and negative inter-individual interactions acting at different spatial ranges. I will first describe the stochastic, individual-level rules that govern the reproduction and death of each individual. Then, using field-theory techniques, I will derive a non-local partial differential equation for the population density and compare its predictions with those obtained assuming well-mixed populations. Finally, I will discuss the ecological relevance of our results and how this approach can be extended to more complex scenarios.

  • Lecture (Conference)
    II Spatial Ecology Workshop: From animal movement processes to spatial distributions, 11.-14.07.2023, Sheffield, United Kingdom

Permalink: https://www.hzdr.de/publications/Publ-37921
Publ.-Id: 37921


Learning Active Matter Behavior of Poxvirus Spreading through Time-lapse Image Generation by Denoising Diffusion Probabilistic Model

Della Maggiora Valdes, G. E.; Yakimovich, A.

Complex dynamic processes occurring in nature may be captured by time-lapse imaging.
However, understanding and reproducing these processes remains a challenge. These
processes range from mass transfer in fluids to the complex behaviour of live active matter
dynamics in cell motility driven by poxvirus infection spread in a monolayer of cells.
Understanding these processes can be attempted through time-lapse sequence synthesis by
means of generative modelling. Here, we present a novel method to predict behaviour from
video sequences, where the underlying mechanics are governed by differential equations with
known and unknown characteristics. Our method is an extension of residual video diffusion in
which we learn an approximation of the underlying differential equation separating the drift
term and the stochastic term. We evaluate it with the reaction-diffusion equation in which we
hide the inhibitor variable from the model and the incompressible Navier-Stokes equation with
a stochastic forcing parameter. Our model accurately predicts the inhibitor variable in the
reaction-diffusion equations and the stochastic forcing parameter in the Navier-Stokes
equation. Additionally, we evaluate the model's capability to learn distinct biological behaviours
of the active matter when trained on time-lapse microscopy of poxvirus spread phenotypes.
The results confirm the model's potential in capturing meaningful equation embeddings, thus
contributing to a deeper understanding of biological dynamics. To assess the accuracy of
poxvirus prediction, we measured the mean absolute error when close to the initial condition.
To evaluate the generation of longer sequences, we employed a qualitative analysis in which
our model achieved excellent results.

  • Poster
    NHR Conference, 18.09.2023, Berlin, Germany

Permalink: https://www.hzdr.de/publications/Publ-37920
Publ.-Id: 37920


Ecological systems are rarely well-mixed: how-animal movement can influence long-term ecological processes

Martinez Garcia, R.

A large body of existing ecological theory relies on very strong and unrealistic assumptions about the way individuals move and get to interact with each other and with the environment. Specifically, several models assume that individuals behave like the molecules of an ideal gas: following completely random trajectories through the entire area occupied by the population and only interacting with each other when their trajectories intersect.

In this presentation, I will first discuss how traditional population dynamics models emerge from ideal gas assumptions. Then, I will present our ongoing research to refine those models using more elaborated tools from random walk theory, spatially-extended nonlinear dynamical systems, and stochastic calculus. I will discuss examples covering both the development of new theory and its application ecological data.

  • Lecture (others)
    University of Bath Computational and Mathematical Biology Colloquium, 10.07.2023, Bath, United Kingdom

Permalink: https://www.hzdr.de/publications/Publ-37919
Publ.-Id: 37919


Backdoor Attacks for Remote Sensing Data With Wavelet Transform

Nikolaus, D.; Yonghao, X.; Ghamisi, P.

Recent years have witnessed the great success of deep learning algorithms in the geoscience and remote sensing (RS) realm. Nevertheless, the security and robustness of deep learning models deserve special attention when addressing safety-critical RS tasks. In this article, we provide a systematic analysis of backdoor attacks for RS data, where both scene classification and semantic segmentation tasks are considered. While most of the existing backdoor attack algorithms rely on visible triggers such as squared patches with well-designed patterns, we propose a novel wavelet transform-based attack (WABA) method, which can achieve invisible attacks by injecting the trigger image into the poisoned image in the low-frequency domain. In this way, the high-frequency information in the trigger image can be filtered out in the attack, resulting in stealthy data poisoning. Despite its simplicity, the proposed method can significantly cheat the current state-of-the-art deep learning models with a high attack success rate. We further analyze how different trigger images and the hyperparameters in the wavelet transform would influence the performance of the proposed method. Extensive experiments on four benchmark RS datasets demonstrate the effectiveness of the proposed method for both scene classification and semantic segmentation tasks and thus highlight the importance of designing advanced backdoor defense algorithms to address this threat in RS scenarios. The code will be available online at https://github.com/ndraeger/waba .

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Permalink: https://www.hzdr.de/publications/Publ-37918
Publ.-Id: 37918


To leave or not to leave: a mechanistic model for the decision-making process behind ungulate partial migration.

Martinez Garcia, R.

Despite the importance of ungulate migrations, we lack a complete understanding of why some ungulates species migrate and some do not. Moreover, at the population level, some migrate and others remain behind as residents, a phenomenon known as partial migration. Even though progress has been made towards understanding long-term fitness benefits of partial migration, the underlying decision-making process that makes some individuals migrate and others remain within one single range remain unknown. In this presentation I will combine empirical data from three different migrant ungulate species and mathematical modeling to address this question. I will first show that, across these three ungulate species, the number of residents is unrelated to total population size, a pattern predicted by no previous modeling framework. Next, I will introduce a new model of ungulate partial migration wherein individuals probabilistically decide to start migrating based on the intensity of environmental and social cues. Within this modeling framework, residents arise for most parameter combinations and the number of residents is largely invariant with total population size. Therefore, this new model explains the ubiquity of residents in migratory ungulate populations and presents novel patterns to be tested with further data collection.

  • Lecture (others)
    Biosciences Colloquium at the University of Swansea, 07.11.2023, Swansea, United Kingdom

Permalink: https://www.hzdr.de/publications/Publ-37917
Publ.-Id: 37917


Population dynamics models with non-local spatial interactions: from spatial patterns to species coexistence

Martinez Garcia, R.

From microbial colonies to entire landscapes, biological systems often self-organize into regular spatial patterns, which might have significant ecological consequences. Several models have been proposed to explain the emergence of these patterns. Most of them rely on a Turing-like activation-inhibition scale-dependent feedback whereby interactions favoring growth dominate at short distances and inhibitory, competitive interactions dominate in the long-range. However, the importance of short-range positive interactions for pattern formation remains disputable. Alternative theories predict their emergence from long-range inhibition alone. In this presentation, I will explain how self-organized patterns might emerge in purely competitive models. I will first present in which conditions long-range competition alone can generate regular patterns of population density in systems with one and two species. Then, I will discuss the ecological implications of those patterns both for population persistence and species coexistence.

  • Lecture (others)
    Mathematics Colloquium at the University of Swansea, 09.11.2023, Swansea, United Kingdom

Permalink: https://www.hzdr.de/publications/Publ-37916
Publ.-Id: 37916


AI Security for Geoscience and Remote Sensing: Challenges and future trends

Xu, Y.; Bai, T.; Yu, W.; Chang, S.; Atkinson, P. M.; Ghamisi, P.

Recent advances in artificial intelligence (AI) have significantly intensified research in the geoscience and remote sensing (RS) field. AI algorithms, especially deep learning-based ones, have been developed and applied widely to RS data analysis. The successful application of AI covers almost all aspects of Earth-observation (EO) missions, from low-level vision tasks like superresolution, denoising, and inpainting, to high-level vision tasks like scene classification, object detection, and semantic segmentation. Although AI techniques enable researchers to observe and understand the earth more accurately, the vulnerability and uncertainty of AI models deserve further attention, considering that many geoscience and RS tasks are highly safety critical. This article reviews the current development of AI security in the geoscience and RS field, covering the following five important aspects: adversarial attack, backdoor attack, federated learning (FL), uncertainty, and explainability. Moreover, the potential opportunities and trends are discussed to provide insights for future research. To the best of the authors’ knowledge, this article is the first attempt to provide a systematic review of AI security-related research in the geoscience and RS community. Available code and datasets are also listed in the article to move this vibrant field of research forward.

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Permalink: https://www.hzdr.de/publications/Publ-37915
Publ.-Id: 37915


Earthquake spatial probability and hazard estimation using various explainable AI (XAI) models at the Arabian peninsula

Ratiranjan, J.; Abdallah, S.; Rami, A.-R.; Biswajeet, P.; Mohamed, B. A. G.; Mohamad, A. K.; Omid, G.; Ghamisi, P.

Earthquakes are the most destructive natural hazards because of their adversely severe impacts on urban areas. Earthquakes affect people's lives and properties, thus captivating the extensive attention of seismologists. Carrying out probability and hazard assessment for the prevention, and reduction of mega-events and recovery will be of great significance in affected areas. Given that limited studies have attempted to estimate earthquake Spatial Probability Assessment (SPA) in the Arabian Peninsula, this study aims to evaluate the SPA and Earthquake Hazard Assessment (EHA). This study implements and evaluates various machine learning and explainable-AI (XAI) techniques for the estimation of SPA and EHA in the Arabian Peninsula, explores the contribution and highlights the importance of different factors in the development of AI-based models. A total of twelve factors ranging from seismological to geophysical factors were evaluated. Two machine learning models namely Light Gradient Boosting Machine (LightGBM) and deep Recurrent Neural Networks (RNN) along with three XAI approaches (i.e, Smart predictor, Smart Explainer and Local Interpretable Model-Agnostic Explanation (LIME) model) were investigated. Results of the comparative earthquake SPA estimation demonstrated that the accuracy of 89% and 87% were achieved by LightGBM and RNN models. Moreover, the results of the XAI models show that the Smart Predictor provides better spatial outputs than the other evaluated XAI models. The stable factors identified by Smart Predictor were magnitude variation and earthquake frequency whereas the important factors were magnitude variation, earthquake frequency, depth variation, and seismic gap. Collectively, results of SPA show that, the Gulf of Aden, Red Sea, Iran, and Turkey are falling under a very-high SPA index (0.991–1). Correspondingly, Gulf areas, coastal areas of Saudi Arabia, and areas in the Zagros fault and Anatolian fault zone fall under a very-high hazard zone. This research could support planners, and decision-makers for emergency planning, infrastructure development, and reconstruction projects.

Permalink: https://www.hzdr.de/publications/Publ-37914
Publ.-Id: 37914


The potential of AI in ecosystem management: drylands as a case study

Martinez Garcia, R.

Introduction to the group research.

  • Lecture (Conference) (Online presentation)
    Big data analytical methods for complex systems, 19.10.2023, Wroclaw, Poland

Permalink: https://www.hzdr.de/publications/Publ-37913
Publ.-Id: 37913


A physics foray into ecology: modeling vegetation dynamics in water-limited ecosystems

Martinez Garcia, R.

Water-limited ecosystems are incredibly complex systems covering 40% of Earth's land surface, mostly in developing countries, and are home to 35% of the world population. A paradigmatic property of these ecosystems is the spatial self-organization of vegetation, which leads to strikingly regular spatial distributions of plants. These self-organized spatial patterns have been suggested as important ecosystem health indicators. Specifically, pattern shapes may indicate the proximity of the ecosystem to undergo a desertification transition. Despite this potential ecological importance, the plant interactions that underlie pattern formation remain unclear. Without strong empirical evidence of how these patterns emerge, mathematical modeling has been crucial in formulating different hypotheses. However, models assuming different mechanistic origins reproduce the same series of patterns but predict contradicting ecological consequences for them. In this context, a new approach to understanding vegetation dynamics in water-limited ecosystems that focus on unveiling how plants interact with each other and how those interactions scale to large population sizes to create emergent patterns is needed.

In this presentation, I will first give an overview of existing models for vegetation pattern formation and their connection to well-known physical systems. Then, I will present our efforts to study vegetation dynamics in water-limited ecosystems, using a combination of models and greenhouse experiments.

  • Lecture (others) (Online presentation)
    Physics colloquium. Federal Univeristy of Paraná., 10.08.2023, Curitiba, Brazil

Permalink: https://www.hzdr.de/publications/Publ-37912
Publ.-Id: 37912


The role of resource dynamics on below-ground plant interactions. A dialogue between simple mathematical models and data.

Martinez Garcia, R.

Plant roots determine carbon uptake, survivorship, and agricultural yield and represent a large proportion of the world’s vegetation carbon pool. The study of below-ground plant growth, unlike aboveground shoot competition, is hampered by our inability to observe roots. We have few observations of intact root systems in soil and lack a comprehensive theory for root system responses to their environment.

In this presentation, I will first review previous theoretical efforts to explain plant below-ground competition and discuss how they lead to seemingly contradictory predictions. Then, I will introduce our recent theoretical and experimental work and show how it resolves existing controversy and provides a unifying framework to study below-ground plant interactions, both competitive and facilitative. I will conclude by discussing future research lines that depart from our results and how they can be addressed with extensions of our framework

  • Lecture (others)
    Senckenberg Colloquium, 20.11.2023, Senckenberg, Germany

Permalink: https://www.hzdr.de/publications/Publ-37911
Publ.-Id: 37911


The search behavior of terrestrial mammals

Noonan, M. J.; Martinez Garcia, R.; Fleming, C. H.; Garcia De Figueiredo, B.; Ali, A. H.; Attias, N.; Belant, J. L.; Beyer Jr., D. E.; Berteaux, D.; Bidner, L. R.; Boone, R.; Boutin, S.; Brito, J.; Brown, M.; Carter, A.; Castellanos, A.; Castellanos, F. X.; Chitwood, C.; Darlington, S.; Antonio De La Torre, J.; Dekker, J.; Deperno, C.; Droghini, A.; Farhadinia, M.; Fennessy, J.; Fichtel, C.; Ford, A.; Gill, R.; Goheen, J. R.; Gustavo R. Oliveira-Santos, L.; Hebblewhite, M.; Hodges, K. E.; Isbell, L. A.; Janssen, R.; Kappeler, P.; Kays, R.; Kaczensky, P.; Kauffman, M.; Lapoint, S.; Alan Lashley, M.; Leimgruber, P.; Little, A.; Macdonald, D. W.; Masiaine, S.; T. McBride Jr., R.; Patricia Medici, E.; Mertes, K.; Moorman, C.; Morato, R. G.; Mourão, G.; Mueller, T.; Neilson, E. W.; Pastorini, J.; Patterson, B. D.; Pereira, J.; Petroelje, T. R.; Piecora, K.; John Power, R.; Rachlow, J.; Ranglack, D. H.; Roshier, D.; Safford, K.; Scott, D. M.; Serrouya, R.; Songer, M.; Songsasen, N.; Stabach, J.; Stacy-Dawes, J.; Swingen, M. B.; Thompson, J.; Tucker, M. A.; Velilla, M.; Yarnell, R. W.; Young, J.; Fagan, W. F.; Calabrese, J.

Animals moving through landscapes need to strike a balance between finding sufficient resources to grow and reproduce while minimizing encounters with predators 1,2. Because encounter rates are determined by the average distance over which directed motion persists 1,3–5, this trade-off should be apparent in individuals’ movement. Using GPS data from 1,396 individuals across 62 species of terrestrial mammals, we show how predators maintained directed motion ~7 times longer than for similarly-sized prey, revealing how prey species must trade off search efficiency against predator encounter rates. Individual search strategies were also modulated by resource abundance, with prey species forced to risk higher predator encounter rates when resources were scarce. These findings highlight the interplay between encounter rates and resource availability in shaping broad patterns mammalian movement strategies.

Permalink: https://www.hzdr.de/publications/Publ-37910
Publ.-Id: 37910


Intraspecific encounters can induce home-range shifts

Fagan, W. F.; Garani Krishnan, A.; Liao, Q.; Fleming, C. H.; Liao, D. F.; Lamb, C.; Patterson, B.; Wheeldon, T.; Martinez Garcia, R.; Saraiva De Menezes, J. F.; Noonan, M. J.; Gurarie, E.; Calabrese, J.

Direct encounters, in which two or more individuals are physically close to one another, are a topic of increasing interest as more and better movement data become available. Recent progress, including the development of statistical tools for estimating robust measures of changes in animals’ space use over time, facilitates opportunities to link direct encounters between individuals with the long-term consequences of those encounters. Working with movement data for coyotes (Canis latrans) and grizzly bears (Ursus arctos horribilis), we investigate whether close intraspecific encounters were associated with spatial shifts in the animals’ range distributions, as might be expected if one or both of the individuals involved in an encounter were seeking to reduce or avoid conflict over space. We analyze the movement data of a pair of coyotes in detail, identifying how a shift in home range location resulting from altered movement behavior was apparently a consequence of a close intraspecific encounter. With grizzly bear 50 movement data, we approach the problem from the perspective of a set of encounter pairs within a population. We find support for the hypotheses that 1) close intraspecific encounters between bears are, on average, associated with subsequent shifts in range distributions and 2) encounters defined at finer spatial scales are followed by greater changes in space use. Our results suggest that animals can undertake long-term, large-scale spatial shifts in response to close intraspecific encounters that have the potential for conflict. These results lend support for existing theory on the evolution of territories and space use (e.g., Maynard-Smith’s bourgeois strategy regarding low-conflict coexistence). Overall, we find that analyses of movement data in a pairwise context can 1) identify distances at which individuals’ proximity to one another may alter behavior and 2) facilitate testing of population-level hypotheses concerning the potential for direct encounters to alter individuals’ space use.

Permalink: https://www.hzdr.de/publications/Publ-37909
Publ.-Id: 37909


How movement bias to attractive regions determines population spread and critical habitat size

Dornelas, V.; de Castro, P.; Calabrese, J.; Fagan, W. F.; Martinez Garcia, R.

Ecologists have long investigated how the demographic and movement parameters of a population determine its spatial spread and the critical habitat size that can sustain it. Yet, most existing models make oversimplifying assumptions about individual movement behavior, neglecting how landscape heterogeneity influences dispersal. We relax this assumption and introduce a reaction-advection-diffusion model that describes the spatial density distribution of a population with space-dependent movement bias toward preferred regions, including avoidance of degraded habitats. In this scenario, the critical habitat size depends on the spatial location of the habitat edges with respect to the preferred regions and on the intensity of the movement bias components. In particular, we identify parameter regions where the critical habitat size decreases when diffusion increases, a phenomenon known as the “drift paradox”. We also find that biased movement toward low-quality or highly populated regions can reduce the population size, therefore creating ecological traps. Our results emphasize the importance of species-specific movement behavior and habitat selection as drivers of population dynamics in fragmented landscapes and, therefore, the need to account for them in the design of protected areas.

Permalink: https://www.hzdr.de/publications/Publ-37908
Publ.-Id: 37908


Demographic effects of aggregation in the presence of a component Allee effect

Jorge, D. C. P.; Martinez Garcia, R.

Intraspecific interactions are key drivers of population dynamics because they establish relations between individual fitness and population density. The component Allee effect is defined as a positive correlation between any fitness component of a focal organism and population density, and it can lead to positive density dependence in the population per capita growth rate. The spatial population structure is key to determining whether and to which extent a component Allee effect will manifest at the demographic level because it determines how individuals interact with one another. However, existing spatial models to study the Allee effect impose a fixed spatial structure, which limits our understanding of how a component Allee effect and the spatial dynamics jointly determine the existence of demographic Allee effects. To fill this gap, we introduce a spatially-explicit theoretical framework where spatial structure and population dynamics are emergent properties of the individual-level demographic and movement rates. Depending on the intensity of the individual-level processes, the population exhibits a variety of spatial patterns, including evenly spaced aggregates of organisms, that determine the demographic-level by-products of an existing individual-level component Allee effect. We find that aggregation increases population abundance and allows populations to survive in harsher environments and at lower global population densities when compared with uniformly distributed organisms. Moreover, aggregation can prevent the component Allee effect from manifesting at the population level or restrict it to the level of each independent group. These results provide a mechanistic understanding of how component Allee effects might operate for different spatial population structures and show at the population level. Because populations subjected to demographic Allee effects exhibit highly nonlinear dynamics, especially at low abundances, our results contribute to a better understanding of population dynamics in the presence of Allee effects and can potentially inform population management strategies.

Permalink: https://www.hzdr.de/publications/Publ-37907
Publ.-Id: 37907


Development Of A Novel ACE2 Decoy For Both SARS-CoV-2 Variant Neutralization And Infected Cell Elimination Via Unmodified Or CAR Modified Immune Cells

Drewitz, L.; Kegler, A.; Arndt, C.; Daglar, C.; Rodrigues Loureiro, L. R.; Mitwasi, N.; Neuber, C.; González Soto, K. E.; Bartsch, T.; Baraban, L.; Ziehr, H.; Heine, M.; Nieter, A.; Moreira-Soto, A.; Kühne, A.; Drexler, J. F.; Seliger, B.; Laube, M.; Máthé, D.; Pályi, B.; Hajdrik, P.; Forgách, L.; Kis, Z.; Sziget, K.; Bergmann, R.; Feldmann, A.; Bachmann, M.

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) caused a pandemic with millions of infections and deaths worldwide and devastating impact on global economy. Up to now, vaccines and monoclonal antibody (mAb) therapies lack to provide a long-lasting protection against rapidly evolving new emerging SARS-CoV-2 variants. Thus, novel therapeutic options are pressingly needed especially for immunocompromised patients and/or patients with high risk for developing a severe coronavirus disease 2019 (COVID-19).
In that regard, we developed a novel immunotherapeutic drug based on the SARS-CoV-2 entry receptor angiotensin-converting enzyme 2 (ACE2). This ACE2 decoy potently binds to the SARS-CoV-2 receptor binding domain (RBD), neutralizes SARS-CoV-2 as well as the Delta and Omicron variant and protects hamsters from a SARS-CoV-2 infection. To additionally use this ACE2 decoy for elimination of virus infected cells, we equipped it with an epitope tag. Thus, it can be applied as adapter molecule in the modular platform technologies UniMAB and UniCAR, which already demonstrated great success in the setting of malignant diseases. As adapter molecule the ACE2 decoy is able to efficiently recruit either universal chimeric antigen receptor (UniCAR) modified T cells or, in combination with an anti-peptide epitope-anti-CD3 bispecific Ab of the UniMAB system, unmodified T cells to efficiently kill SARS-CoV-2 RBD expressing human cells.
Taken together, the ACE2 decoy represents a very promising immunotherapeutic drug for both SARS-CoV-2 variant neutralization and infected cell killing via the UniMAB and UniCAR system and might, therefore, clearly improve the treatment of COVID-19 patients.

Permalink: https://www.hzdr.de/publications/Publ-37905
Publ.-Id: 37905


Gallium recovery by ion flotation using amphiphilic siderophores as a novel flotation reagent

Chakankar, M. V.; Pollmann, K.; Kutschke, S.; Rudolph, M.

Marinobactins are a suite of amphiphilic siderophores (microbial iron-chelators) produced by Marinobacter sp. They belong to the hydroxamate class of siderophores and are composed of peptidic group linked with fatty acid chain that varies in length and saturation. Amphiphilic nature of these siderophores and metal complexation ability make them an interesting molecule for an application in the flotation process. In this work, marinobactin was investigated as a potential Gallium (Ga) collector in an ion flotation process. Single metal flotation test suggested the Ga recovery and marinobactin-Ga complexation in the collected concentrates was confirmed by HPLC. Further, preliminary flotation test with metal mixture (1mM) containing both Ga and Arsenic (As) revealed nearly 60% and 24% recovery of Ga and As respectively, at pH 7 and 0.5mM marinobactin concentration. This study shows the feasibility of employing novel siderophores in the ion flotation process for the recovery of metals from low concentrated wastewater.

Keywords: Siderophore; Marinobactin; Ion flotation; metal recovery

  • Lecture (Conference)
    Flotation '23, 06.-09.11.2023, Cape Town, South Africa

Permalink: https://www.hzdr.de/publications/Publ-37904
Publ.-Id: 37904


Production of the PET radionuclide 61Cu via the 62Ni(p,2n)61Cu Nuclear Reaction

Brühlmann, S. A.; Walther, M.; Kopka, K.; Kreller, M.

Background
There are only a handful of true theranostic matched pairs, and in particular the theranostic radiocopper trio 61Cu, 64Cu and 67Cu, for diagnosis and therapy respectively, is a very attractive candidate. In fact, the alternative of two imaging radionuclides with different half-lives is a clear advantage over other theranostic pairs, since it offers a better matching for the tracer biological and radionuclide physical half-lives. Due to the high availability of 64Cu, its translation into the clinic is being successfully carried out, giving the example of the FDA approved radiopharmaceutical Detectnet (copper Cu 64 dotatate injection). However, a shorter-lived PET radionuclide such as 61Cu may as well be beneficial.
Results
Proton irradiation of enriched 62Ni electrodeposited targets with a compact cyclotron produced the desired radionuclide via the 62Ni(p,2n)61Cu nuclear reaction, leading to 61Cu activities of up to 20 GBq at end of bombardment and 8 GBq at end of purification. Furthermore, two purification methods are compared leading to comparable results regarding separation yield and product purity. Following the radiochemical separation, quality assessment of this product [61Cu]CuCl2 solution proved radionuclidic purities (RNP) over 99.6 % and apparent molar activities (AMA) of 260 GBq/µmol with the 1,4,8,11-tetraazacyclotetradecane-1,4,8,11-tetraacetic acid (TETA) chelator, end of purification corrected.
Conclusions
In the current article a comprehensive novel production method for the PET radionuclide 61Cu is presented, providing an alternative to the most popular production routes. Characterization of the [61Cu]CuCl2 product showed both high RNP as well as high AMA, proving that the produced activity presented high quality regarding radiolabeling up to 9 hours after EOP. Furthermore, production scalability could be easily achieved by increasing the irradiation time.

Keywords: copper-61; targetry; target chemistry; PET; theranostics; radiocopper; CopperNostics

Permalink: https://www.hzdr.de/publications/Publ-37903
Publ.-Id: 37903


openPMD – the Open Standard for Particle-Mesh Data

Huebl, A.; Wan, L.; Lehe, R.; Podhorszki, N.; Gu, J.; Thévenet, M.; Schnetter, E.; Pöschel, F.; Bussmann, M.

The Open Standard for Particle-Mesh Data (openPMD) is a F.A.I.R. metadata standard for tabular (particle/dataframe) and structured mesh data in science and engineering.
We show the basic components of openPMD, its extensions to specific domains, applications from laser-plasma physics, particle accelerators, material physics to imaging and the ability to bridge multiple heterogeneous scientific models with a commonly-understood markup.

The openPMD-api builds upon established portable I/O formats such as HDF5 and ADIOS2, enabling workflows that scale from single-user computers up to Exascale simulations, in-transit data processing, 3D visualization, GPU-accelerated data analytics and AI/ML. openPMD links into the existing ecosystems of its scalable I/O backends and extends them with tooling that understands the openPMD data markup.
An overview over the openPMD ecosystem and community is shown.

Attention is given to recent developments in openPMD that interplay with HDF5, including mesh refinement and the Helmholtz Metadata Collaboration's HELPMI project which aims for an easier integration of openPMD with other HDF5-based standards, this way bringing openPMD closer to experiment workflows.

References:

[1] Axel Huebl, Remi Lehe, Jean-Luc Vay, David P. Grote, Ivo F. Sbalzarini, Stephan Kuschel, David Sagan, Christopher Mayes, Frederic Perez, Fabian Koller, and Michael Bussmann. “openPMD: A meta data standard for particle and mesh based data,” DOI:10.5281/zenodo.591699 (2015)
[2] Homepage: https://www.openPMD.org
[3] GitHub Organization: https://github.com/openPMD
[4] Projects using openPMD: https://github.com/openPMD/openPMD-projects
[4] Reference API implementation: Axel Huebl, Franz Poeschel, Fabian Koller, and Junmin Gu. “openPMD-api 0.14.3: C++ & Python API for Scientific I/O with openPMD,” DOI:10.14278/rodare.1234 (2021)
https://openpmd-api.readthedocs.io
[5] Selected earlier presentations on openPMD:
https://zenodo.org/search?page=1&size=20&q=openPMD&type=presentation
[6] Axel Huebl, Rene Widera, Felix Schmitt, Alexander Matthes, Norbert Podhorszki, Jong Youl Choi, Scott Klasky, and Michael Bussmann. “On the Scalability of Data Reduction Techniques in Current and Upcoming HPC Systems from an Application Perspective,” ISC High Performance 2017: High Performance Computing, pp. 15-29, 2017. arXiv:1706.00522, DOI:10.1007/978-3-319-67630-2_2
[7] Franz Poeschel, Juncheng E, William F. Godoy, Norbert Podhorszki, Scott Klasky, Greg Eisenhauer, Philip E. Davis, Lipeng Wan, Ana Gainaru, Junmin Gu, Fabian Koller, Rene Widera, Michael Bussmann, and Axel Huebl. Transitioning from file-based HPC workflows to streaming data pipelines with openPMD and ADIOS2, Part of Driving Scientific and Engineering Discoveries Through the Integration of Experiment, Big Data, and Modeling and Simulation, SMC 2021, Communications in Computer and Information Science (CCIS), vol 1512, 2022. arXiv:2107.06108, DOI:10.1007/978-3-030-96498-6_6
[8] The Helmholtz Metadata Collaboration's ongoing HELPMI project: https://helmholtz-metadaten.de/de/inf-projects/helpmi-helmholtz-laser-plasma-metadata-initiative

Keywords: F.A.I.R.; openPMD; HDF5; ADIOS2; HPC

  • Open Access Logo Lecture (Conference)
    2023 European HDF User Group (HUG) plugins and data compression summit, 19.-21.09.2023, Hamburg, Deutschland
  • Open Access Logo Invited lecture (Conferences)
    9. Annual MT Meeting, 09.-11.10.2023, Karlsruhe, Deutschland
  • Open Access Logo Poster
    9. Annual MT Meeting, 09.-11.10.2023, Karlsruhe, Deutschland
  • Open Access Logo Poster
    DMA ST1 synergy workshop, 08.-10.11.2023, Hamburg, Deutschland

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Permalink: https://www.hzdr.de/publications/Publ-37902
Publ.-Id: 37902


Non-coaxial deformation of foreland basement involved in a fold-and-thrust belt: a strain partitioning approach to the Eastern Variscan orogen

Mareček, L.; Melichar, R.; Cerny, J.; Schnabl, P.; Hrdličková, K.; Buriánek, D.

The general SW–NE course of the Variscan orogen in Europe is abruptly bent to the N–S course at its eastern margin, where an oblique convergence occurred. The main suture in this part of the Variscan orogenic belt is called the Moldanubian Thrust, characterized by a dominant dextral strike‑slip kinematics and a minor thrust component. The deep level of erosion and the good exposure of this structure allowed us to study the mechanisms of oblique convergence and the incorporation of the foreland basement into the orogenic belt. The combination of small‑scale structures with the anisotropy of magnetic susceptibility studies allowed the recognition of two deformations in the studied rocks: dextral simple shearing and drag folding. Due to oblique convergence, the deformations induced by this mechanism were non‑coaxial; therefore, their contributions can be easily distinguished. Finally, an overturned, almost recumbent large‑scale synformal fold structure in the footwall and an antiformal structure in the hanging wall of the Moldanubian Thrust were formed. These two folds can be interpreted as structures formed by dragging along the Moldanubian Thrust. The previously described sinistral simple shearing in the upper limb of the synform resulted from the original dextral strike‑slip shearing, which was overturned during progressive deformation.

Permalink: https://www.hzdr.de/publications/Publ-37901
Publ.-Id: 37901


Data publication: On the anatomy and structural control of a dyke swarm that fed caldera-forming ignimbrite eruptions

Tomek, F.; Olšanská, I.; Trubač, J.; Cerny, J.; Rejšek, J.; Ackerman, L.

The whole-rock major, trace element and isotope geochemical tables, magnetic fabrics source data and details of methods.

Related publications

Permalink: https://www.hzdr.de/publications/Publ-37900
Publ.-Id: 37900


On the anatomy and structural control of a dyke swarm that fed caldera-forming ignimbrite eruptions

Tomek, F.; Olšanská, I.; Trubač, J.; Cerny, J.; Rejšek, J.; Ackerman, L.

The evolution of eruptive vents related to calderas is not fully understood. We focus on a structural, rock-magnetic, and geochemical investigation of a ∼314 Ma rhyolite dyke swarm associated with the late-orogenic Altenberg–Teplice Caldera, Bohemian Massif, eastern Variscan belt. The whole-rock major element, trace element, and Nd–Pb isotope geochemistry along with the published U-Pb zircon geochronology link the extra-caldera dyke swarm with intra-caldera ignimbrites. The magnetic fabrics determined using the anisotropy of magnetic susceptibility are interpreted to record a continuum from magma ascent, emplacement, and eruption during sinistral shearing. The latter evidences an interplay with regional tectonics associated with the activity of crustal-scale shear zones. The sinistral kinematics and strike of the dyke swarm, the elongation of caldera intrusive units, and the kinematics of major caldera faults are consistent with the dextral Riedel shear system, where the dykes correspond to antithetic Ŕ/X-shears. Such a kinematic configuration implies that the maximum and minimum principal stresses were oriented roughly north-south and east-west, respectively. The relation between the stress field with respect to the caldera elongation and orientation is not typical. We suggest that a pre-existing mutually perpendicular set of cross-cutting structural lineaments largely controlled the magma chamber and caldera formation.

Related publications

  • Journal of the Geological Society 180(2023), jgs2022-119
    Online First (2023) DOI: 10.1144/jgs2022-119

Permalink: https://www.hzdr.de/publications/Publ-37899
Publ.-Id: 37899


TransU-Net++: Rethinking attention gated TransU-Net for deforestation mapping

Jamali, A.; Kumar Roy, S.; Li, J.; Ghamisi, P.

Deforestation has become a major cause of climate change, and as a result, both characterizing the drivers and estimating segmentation maps of deforestation have piqued the interest of researchers. In the computer vision domain, Vision Transformers (ViTs) have shown their superiority compared to extensively utilized convolutional neural networks (CNNs) over the last couple of years. Although, ViTs has several challenges, specifically in remote sensing image processing, including their significant complexity that increases the computation costs and their need for much higher reference data than that of CNNs. As such, in this paper, we introduce an attention gates aided TransU-Net, called TransU-Net++ for semantic segmentation with an application of deforestation mapping in two South American forest biomes, i.e., the Atlantic Forest and the Amazon Rainforest. The heterogeneous kernel convolution (HetConv), U-Net, attention gates, and ViTs are all utilized in the proposed TransU-Net++ to their advantage. The TransU-Net++ significantly increased the performance of TransU-Net’s over the Atlantic Forest dataset by about 4%, 6%, and 16%, respectively, in terms of overall accuracy, F1-score, and recall, respectively.Moreover, the results show that the developed TrasnU-Net++ model (0.921) achieves the highest Area under the ROC Curve value in the 3-band Amazon forest dataset as compared to other segmentation models, including ICNet (0.667), ENet (0.69), SegNet (0.788), U-Net (0.871), Attention U-Net-2 (0.886), R2U-Net (0.888), TransU-Net (0.889), Swin U-Net (0.893), ResU-Net (0.896), U-Net+++ (0.9), and Attention U-Net (0.908), respectively. The code will be made publicly available at https://github.com/aj1365/TransUNetplus2.

Permalink: https://www.hzdr.de/publications/Publ-37898
Publ.-Id: 37898


Datengestützte Intralogistik zur Optimierung von Aufbereitungs- & Recyclingprozessen

Nagel, M.; Rau, F.; Pereira, L.

Intralogistik gewinnt bei der Produktionssteuerung für die Organisation und Optimierung von Zulieferung und Warenumschlag stetig an Bedeutung. Darüber hinaus werden durch Intralogistik innerbetriebliche Materialflüsse und Informationsströme gesteuert und – wenn möglich – die Produktionslogistik intelligent gesteuert.

Die Intralogistik von Aufbereitungs- und Recyclingprozesse unterscheidet sich erheblich von der Intralogistik bei Produktionsprozessen. Bei Herstellung von Produkten und Halbzeugen sind Eigenschaften von Ausgangsmaterialien meist chargengenau bekannt. Während bei der Aufbereitung von Bergbauhalden oder dem Recycling die relevanten Stoffe in den Ausgangsmaterialien in ihrer Zusammensetzung, Qualität und Quantität höchst inhomogen verteilt und weitgehend unbekannt sind. Die Intralogistik bei solchen Prozessen ist hochkomplex und muss daher bei der dynamischen Analyse des Ausgangsmaterials beginnen und mit Ergebnissen des Aufbereitungsprozesses enden. Die Steuerung des Aufbereitungsprozesses muss dynamisch und datengesteuert angepasst werden.

Am Beispiel der Aufbereitung von Haldenmaterial mit Hilfe der Flotation soll die Verknüpfung der Datenerfassung des Aufgabegutes mit der Prozesssteuerung, der Intralogisitk und weiteren Verarbeitungs- und Optimierungsschritten gezeigt werden.

Keywords: DigiFloat

  • Lecture (Conference)
    Finden statt Suchen – agieren statt reagieren, 24.11.2023, Chemnitz, Deutschland

Permalink: https://www.hzdr.de/publications/Publ-37897
Publ.-Id: 37897


WetMapFormer: A unified deep CNN and vision transformer for complex wetland mapping

Ali, J.; Swalpa, K. R.; Ghamisi, P.

The Ramsar Convention of 1971 encourages wetland preservation, but it is unclear how climate change will affect wetland extent and related biodiversity. Due to the use of the self-attention mechanism, vision transformers (ViTs) gain better modeling of global contextual information and become a powerful alternative to Convolutional Neural Networks (CNNs). However, ViTs require enormous training datasets to activate their image classification power, and gathering training samples for remote sensing applications is typically costly. As such, in this study, we develop a deep learning algorithm called (WetMapFormer), which effectively utilizes both CNNs and vision transformer architectures for precise mapping of wetlands in three pilot sites around the Albert county, York county, and Grand Bay-Westfield located in New Brunswick, Canada. The WetMapFormer utilizes local window attention (LWA) rather than the conventional self-attention mechanism for improving the capability of feature generalization in a local area by substantially reducing the computational cost of vanilla ViTs. We extensively evaluated the robustness of the proposed WetMapFormer with Sentinel-1 and Sentinel-2 satellite data and compared it with the various CNNs and vision transformer models which include ViT, Swin Transformer, HybridSN, CoAtNet, a multimodel network, and ResNet, respectively. The proposed WetMapFormer achieves F-1 scores of 0.94, 0.94, 0.96, 0.97, 0.97, 0.97, and 1 for the recognition of aquatic bed, freshwater marsh, shrub wetland, bog, fen, forested wetland, and water, respectively. As compared to other vision transformers, the WetMapFormer limits receptive fields while adjusting translational invariance and equivariance characteristics. The codes will be made available publicly at https://github.com/aj1365/WetMapFormer.

Permalink: https://www.hzdr.de/publications/Publ-37896
Publ.-Id: 37896


FlexiPlant

van den Boogaart, K. G.; Rau, F.

Mit der weltweit einmaligen Forschungsinfrastruktur FlexiPlant wollen wir Rohstoffe aller Art energie- und ressourceneffizient zurückgewinnen. Dafür entwickeln wir eine neue Generation adaptiver, flexibler & digitalisierter Aufbereitungstechnologien.

  • Invited lecture (Conferences)
    simul+Netzwerktreffen Kreislaufwirtschaft, 20.11.2023, Dresden, Deutschland

Permalink: https://www.hzdr.de/publications/Publ-37895
Publ.-Id: 37895


Changes to Captions: An Attentive Network for Remote Sensing Change Captioning

Shizhen, C.; Ghamisi, P.

In recent years, advanced research has focused on the direct learning and analysis of remote-sensing images using natural language processing (NLP) techniques. The ability to accurately describe changes occurring in multi-temporal remote sensing images is becoming increasingly important for geospatial understanding and land planning. Unlike natural image change captioning tasks, remote sensing change captioning aims to capture the most significant changes, irrespective of various influential factors such as illumination, seasonal effects, and complex land covers. In this study, we highlight the significance of accurately describing changes in remote sensing images and present a comparison of the change captioning task for natural and synthetic images and remote sensing images. To address the challenge of generating accurate captions, we propose an attentive changes-to-captions network, called Chg2Cap for short, for bi-temporal remote sensing images. The network comprises three main components: 1) a Siamese CNN-based feature extractor to collect high-level representations for each image pair; 2) an attentive encoder that includes a hierarchical self-attention block to locate change-related features and a residual block to generate the image embedding; and 3) a transformer-based caption generator to decode the relationship between the image embedding and the word embedding into a description. The proposed Chg2Cap network is evaluated on two representative remote sensing datasets, and a comprehensive experimental analysis is provided. The code and pre-trained models will be available online at https://github.com/ShizhenChang/Chg2Cap .

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Permalink: https://www.hzdr.de/publications/Publ-37894
Publ.-Id: 37894


BDD-Net+: A Building Damage Detection Framework Based on Modified Coat-Net

Seydi, S. T.; Hasanlou, M.; Chanussot, J.; Ghamisi, P.

The accurate and fast assessment of damaged buildings following a disaster is critical for planning rescue and reconstruction efforts. The damage assessment by the traditional methods is time-consuming and with limited performance. In this article, we propose an end-to-end deep-learning network named building damage detection network-plus (BDD-Net+). The BDD-Net+ is based on a combination of convolution layers and transformer blocks. The proposed framework takes the advantage of the multiscale residual convolution blocks and self-attention layers. The proposed framework consists of four main steps: data preparation, model training, damage map generation and evaluation, and the use of an explainable artificial intelligence (XAI) framework for understanding and interpretation of the operation model. The experimental results include two representative real-world benchmark datasets (i.e., the Haiti earthquake and the Bata explosion). The obtained results illustrate that BDD-Net+ achieves excellent efficacy in comparison with other state-of-the-art methods. Furthermore, the visualization of the results by XAI shows that BDD-Net+ provides more interpretable and explainable results for damage detection than the other studied methods.

Permalink: https://www.hzdr.de/publications/Publ-37893
Publ.-Id: 37893


X-ray Thomson Scattering as a high-precision tool for Warm Dense Matter diagnostics

Dornheim, T.

Warm dense matter (WDM)---an extreme state that is characterized by extreme densities and
temperatures---has emerged as one of the most active frontiers in plasma physics and material
science. In nature, WDM occurs in astrophysical objects such as giant planet interiors and brown
dwarfs. In addition, WDM is highly important for cutting-edge technological applications such as
inertial confinement fusion and the discovery of novel materials. In the laboratory, WDM is studied
experimentally in large facilities around the globe, and new techniques have facilitated
unprecedented insights. Yet, the interpretation of these experiments requires a reliable diagnostics
based on accurate theoretical modeling, which is a notoriously difficult task [1].

In this talk, I will explain how we can use X-ray Thomson scattering (XRTS) measurements [2] to infer important system parameters such as the temperature, density, and degree of ionization. Interestingly, standard forward modeling methods based on the widespread Chihara decomposition have neglected transitions between free and bound electrons (the inverse process of the usual bound-free transitions), which are negligible at ambient conditions, but become important in the WDM regime [3]. In addition, I will show how switching to the imaginary-time representation opens up new avenues towards the model-free interpretation of XRTS signals, and gives one direct access to the temperature [4,5] and electronic correlations [6] of the system. Finally, I will outline new PIMC capabilities [7,8] that allow for quasi-exact simulations of experiments conducted at the Gbar platform at the National Ignition Facility (NIF) in Livermore.

[1] M. Bonitz et al, Physics of Plasmas 27, 042710 (2020)
[2] S. Glenzer and R. Redmer, Reviews of Modern Physics 81, 1625 (2009)
[3] M. Böhme et al, arXiv:2306.17653 (submitted)
[4] T. Dornheim et al, Nature Communications 13, 7911 (2022)
[5] T. Dornheim et al, Physics of Plasmas 30, 042707 (2023)
[6] T. Dornheim et al, arXiv:2305.15305 (submitted)
[7] M. Böhme et al, Physical Review Letters 129, 066402 (2022)
[8] T. Dornheim et al, Journal of Chemical Physics 159, 164113 (2023)

  • Lecture (others)
    GSI Plasmaphysik-Seminar, 28.11.2023, Darmstadt, Deutschland

Permalink: https://www.hzdr.de/publications/Publ-37891
Publ.-Id: 37891


Studying the effect of hydrodynamics on flotation kinetics of complex particles using particle-based separation modelling

Hassan, A.; Gurdziel, M.; Bowden, J.; Guy, B. M.; Rudolph, M.; Pereira, L.

Impact of hydrodynamics on flotation kinetics has been heavily studied but research concerning their effect on complex individual particles recovery is lacking. This study aims at understanding the effect of superficial gas velocity (Jg) and impeller tip speed (Vs) on the flotation kinetics of a complex porphyry copper ore by investigating the recovery of individual particles in relation to their particulate properties (size, shape, mineral composition, i.e. surface liberation, mineral association and texture). Experiments were performed on FLSmidth’s 6L nextSTEPTM flotation cell following a full-factorial DoE approach. Jg (0.40–0.50 cm/s) and Vs (4.20–5.50m/s) were used as process parameters at constant pulp density, pH, and reagent dosages. Particle datasets pertaining all products were collected using 2D-automated mineralogy. Logistic regression-based models were trained using experimental data to compute the recovery probabilities of each particle at different operating conditions. This served to quantify the influence of hydrodynamics and particle properties on the process behavior of the main ore mineral (chalcopyrite), and gangue minerals including pyrite, quartz, micas, and other silicates.

Keywords: flotation hydrodynamics; particle-based separation modelling; recovery probability; automated mineralogy; superficial gas velocity; impeller tip speed; logistic regression; scanning electron microscopy

  • Lecture (Conference)
    MEI Flotation 2023, 06.-09.11.2023, Cape Town, South Africa

Permalink: https://www.hzdr.de/publications/Publ-37890
Publ.-Id: 37890


Hyperspectral Remote Sensing Benchmark Database for Oil Spill Detection With an Isolation Forest-Guided Unsupervised Detector

Duan, P.; Kang, X.; Ghamisi, P.; Li, S.

Oil spill detection has attracted increasing attention in recent years, since marine oil spill accidents severely affect environments, natural resources, and the lives of coastal inhabitants. Hyperspectral remote sensing images provide rich spectral information which is beneficial for the monitoring of oil spills in complex ocean scenarios. However, most of the existing approaches are based on supervised and semi-supervised frameworks to detect oil spills from hyperspectral images (HSIs), which require a massive amount of effort to annotate a certain number of high-quality training sets. In this study, we make the first attempt to develop an unsupervised oil spill detection method based on isolation forest (iForest) for HSIs. First, a Gaussian statistical model is designed to remove the bands corrupted by severe noise. Then, kernel principal component analysis (KPCA) is employed to reduce the high dimensionality of the HSIs. Next, the probability of each pixel belonging to one of the classes of seawater and oil spills is estimated with the iForest, and a set of pseudolabeled training samples is automatically produced using the clustering algorithm on the detected probability. Finally, an initial detection map can be obtained by performing the support vector machine (SVM) on the dimension-reduced data, and the initial detection result is further optimized with the extended random walker (ERW) model so as to improve the detection accuracy of oil spills. Experiments on hyperspectral oil spill database (HOSD) created by ourselves demonstrate that the proposed method obtains superior detection performance with respect to other state-of-the-art detection approaches. We will make HOSD and our developed library for oil spill detection publicly available at https://github.com/PuhongDuan/HOSD to further promote this research topic.

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Permalink: https://www.hzdr.de/publications/Publ-37889
Publ.-Id: 37889


Ab initio path integral Monte Carlo simulations of the uniform electron gas on large length scales

Dornheim, T.; Schwalbe, S.; Moldabekov, Z.; Vorberger, J.; Tolias, P.

The accurate description of non-ideal quantum many-body systems is of prime importance for a host of applications within physics, quantum chemistry, material science, and related disciplines. At finite temperatures, the gold standard is given by \textit{ab initio} path integral Monte Carlo (PIMC) simulations, which do not require any empirical input, but exhibit an exponential increase in the required compute time for fermionic systems with increasing the system size N. Very recently, it has been suggested to compute fermionic properties without this bottleneck based on PIMC simulations of fictitious identical particles. In the present work, we use this technique to carry out very large (N≤1000) PIMC simulations of the warm dense electron gas and demonstrate that it is capable of providing a highly accurate description of investigated properties, i.e., the static structure factor, the static density response function, and local field correction, over the entire range of length scales.

Related publications

Permalink: https://www.hzdr.de/publications/Publ-37888
Publ.-Id: 37888


Fully Linear Graph Convolutional Networks for Semi-Supervised and Unsupervised Classification

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

This article presents FLGC, a simple yet effective fully linear graph convolutional network for semi-supervised and unsupervised learning. Instead of using gradient descent, we train FLGC based on computing a global optimal closed-form solution with a decoupled procedure, resulting in a generalized linear framework and making it easier to implement, train, and apply. We show that (1) FLGC is powerful to deal with both graph-structured data and regular data, (2) training graph convolutional models with closed-form solutions improve computational efficiency without degrading performance, and (3) FLGC acts as a natural generalization of classic linear models in the non-Euclidean domain (e.g., ridge regression and subspace clustering). Furthermore, we implement a semi-supervised FLGC and an unsupervised FLGC by introducing an initial residual strategy, enabling FLGC to aggregate long-range neighborhoods and alleviate over-smoothing. We compare our semi-supervised and unsupervised FLGCs against many state-of-the-art methods on a variety of classification and clustering benchmarks, demonstrating that the proposed FLGC models consistently outperform previous methods in terms of accuracy, robustness, and learning efficiency. The core code of our FLGC is released at https://github.com/AngryCai/FLGC.

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  • Secondary publication expected

Permalink: https://www.hzdr.de/publications/Publ-37887
Publ.-Id: 37887


Local Window Attention Transformer for Polarimetric SAR Image Classification

Jamali, A.; Roy, S. K.; Bhattacharya, A.; Ghamisi, P.

Convolutional neural networks (CNNs) have recently found great attention in image classification since deep CNNs have exhibited excellent performance in computer vision. Owing to their immense success, of late, scientists are exploring the functionality of transformers in Earth observation applications. Nevertheless, the primary issue with transformers is that they demand significantly more training data than CNN classifiers. Thus, the use of these transformers in remote sensing is considered challenging, notably in utilizing polarimetric synthetic aperture radar (PolSAR) data, due to the insufficient number of existing labeled data. In this letter, we develop and propose a vision transformer (ViT)-based framework that utilizes 3-D and 2-D CNNs as feature extractors and, in addition, local window attention (LWA) for the effective classification of PolSAR data. Extensive experimental results demonstrated that the developed model PolSARFormer obtained better classification accuracy than the state-of-the-art vision Swin Transformer and FNet algorithms. The PolSARFormer outperformed the Swin Transformer and FNet by the margin of 5.86% and 17.63%, in terms of average accuracy (AA) in the San Francisco data benchmark. Moreover, the results over the Flevoland dataset illustrated that the PolSARFormer exceeds several other algorithms, including the ResNet (97.49%), Swin Transformer (96.54%), FNet (95.28%), 2-D CNN (94.57%), and AlexNet (91.83%), with a kappa index (KI) of 99.30%. The code will be made available publicly at https://github.com/aj1365/PolSARFormer .

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Permalink: https://www.hzdr.de/publications/Publ-37886
Publ.-Id: 37886


Scalable machine learning for predicting the electronic structure in many-particle systems

Cangi, A.

In this presentation, I will present our recent progress in integrating machine learning to significantly boost the computational efficiency of electronic structure calculations [1]. I will specifically address our efforts to speed up density functional theory calculations, for which we have developed the Materials Learning Algorithms framework [2]. Our findings illustrate significant improvements in calculation speed for metals at their melting point. Additionally, our use of automated machine learning has yielded significant reductions in computational resources required to identify optimal neural network architectures, laying the groundwork for extensive investigations [3]. Furthermore, I will show the transferability of our ML model across temperatures [4]. Most importantly, I will present our latest breakthrough, which enables fast neural-network driven electronic structure calculations for systems unattainable by conventional density functional theory calculations [5].

References
[1] L. Fiedler, K. Shah, M. Bussmann, A. Cangi, Phys. Rev. Materials, 6, 040301 (2022).
[2] J. Ellis, L. Fiedler, G. Popoola, N. Modine, J. Stephens, A. Thompson, A. Cangi, S. Rajamanickam, Phys. Rev. B, 104, 035120 (2021).
[3] L. Fiedler, N. Hoffmann, P. Mohammed, G. Popoola, T. Yovell, V. Oles, J. Austin Ellis, S. Rajamanickam, A. Cangi, Mach. Learn.: Sci. Technol., 3, 045008 (2022).
[4] L. Fiedler, N. A. Modine, K. D. Miller, and A. Cangi Phys. Rev. B 108, 125146 (2023).
[5] L. Fiedler, N. Modine, S. Schmerler, D. Vogel, G. Popoola, A. Thompson, S. Rajamanickam, A. Cangi, npj. Comput. Mater., 9, 115 (2023).

Keywords: Machine learning; Electronic structure theory; Density functional theory; Neural networks

  • Invited lecture (Conferences)
    Many-Particle Systems under Extreme Conditions, WE-Heraeus Seminar and Max Born Symposium, 03.-06.12.2023, Görlitz, Deutschland

Permalink: https://www.hzdr.de/publications/Publ-37883
Publ.-Id: 37883


Liquid Metal Batteries: transport phenomena and cycling behavior

Weier, T.

There is a close and multifaceted relation between fluid dynamics and
the charge/discharge behavior of liquid metal batteries. The talk will
give an overview of numerical and experimental work on transport
phenomena in liquid metal batteries and discuss how they influence
the cycling behavior of the cells.

Keywords: liquid metal batteries; transport phenomena; heat transfer; mass transfer; solutal convection; internally heated convection

  • Invited lecture (Conferences) (Online presentation)
    Annual Meeting of the Mexican Physical Society - Division of Fluid Dynamics (DDF-SMF), 04.-06.12.2023, Mexico City, Mexico

Permalink: https://www.hzdr.de/publications/Publ-37882
Publ.-Id: 37882


Report on research data management interviews conducted for HMC Hub Energy in 2022

Ballani, F.; Schaller, T.; Steinmeier, L.; Koubaa, M. A.; Schweikert, J.; Stucky, K.-U.; Süß, W.

The Energy Hub of the Helmholtz Metadata Collaboration (HMC) conducted interviews with various stakeholders from the Helmholtz Research Field Energy on the topic of research data management (RDM) in 2022. The intentions were to build and serve a metadata community in the energy research field and to extend the Helmholtz-wide survey conducted by HMC in 2021 Arndt et al., 2022). Besides the deeper insight into the current state of RDM and metadata handling at the Helmholtz sites relevant to the Energy Hub the interviews focused on the related needs and difficulties of researchers and their satisfaction with the current state. Furthermore, we tried to discover already existing workflows and software solutions, to establish contacts and to make HMC better known.

Keywords: Helmholtz Metadata Collaboration; Research data management

Permalink: https://www.hzdr.de/publications/Publ-37881
Publ.-Id: 37881


Data publication: Ion emission from warm dense matter produced by irradiation with a soft x-ray free-electron laser

Krása, J.; Burian, T.; Hájková, V.; Chalupský, J.; Jelínek, Š.; Frantálová, K.; Krupka, M.; Kuglerová, Z.; Kumar Singh, S.; Vozda, V.; Vyšín, L.; Smid, M.; Perez-Martin, P.; Kühlman, M.; Pintor, J.; Cikhardt, J.; Dreimann, M.; Eckermann, D.; Rosenthal, F.; Vinko, S. M.; Forte, A.; Gawne, T. D.; Campbell, T.; Ren, S.; Shi, Y.; Hutchinson, T.; Humphries, O. S.; Preston, T.; Makita, M.; Nakatsutsumi, M.; Pan, X.; Köhler, A.; Harmand, M.; Toleikis, S.; Falk, K.; Juha, L.

Data set on the ion emission of different materials. Each dataset is separate and titled with the chemical symbol or abbreviation of the specific material.

Related publications

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Permalink: https://www.hzdr.de/publications/Publ-37880
Publ.-Id: 37880


Effect of Chain Length on Swelling Transitions of Brodie Graphite Oxide in Liquid 1-Alcohols

Iakunkov, A.; Nordenström, A.; Boulanger, N.; Li, G.; Hennig, C.; Jørgensen, M. R. V.; Kantor, I.; Talyzin, . A. V.

Swelling is the most fundamental property of graphite oxides (GO). Here, a structural study of Brodie graphite oxide (BGO) swelling in a set of long chain 1-alcohols (named C11 to C22 according to the number of carbons) performed using synchrotron radiation X-ray diffraction at elevated temperatures is reported. Even the longest of tested alcohols (C22) is found to intercalate BGO with enormous expansion of the interlayer distance from ≈6Å up to ≈63Å, the highest expansion of GO lattice ever reported. Swelling transitions from low temperature alpha-phase to high temperature beta-phase are found for BGO in all alcohols in the C11–C22 set. The transitions correspond to decrease of inter-layer distance correlating with the length of alcohol molecules, and change in their orientation from perpendicular to GO planes to layered parallel to GO (Type II transitions). These transitions are very different compared to BGO swelling transitions (Type I) found in smaller alcohols and related to insertion/de-insertion of additional layer of alcohol parallel to GO. Analysis of general trends in the whole set of 1-alcohols (C1 to C22) shows that the 1-alcohol chain length defines the type of swelling transition with Type I found for alcohols with C<10 and Type II for C>10.

Related publications

Permalink: https://www.hzdr.de/publications/Publ-37879
Publ.-Id: 37879


Geometry Optimization in 2D Materials

Friedrich, R.

Tutorial on geometry optimization in 2D materials.

Related publications

  • Invited lecture (Conferences)
    DFG SPP 2244 Summer School 2023, 29.08.2023, Dresden, Deutschland

Permalink: https://www.hzdr.de/publications/Publ-37878
Publ.-Id: 37878


AFLOW: Integrated infrastructure for computational materials discovery

Friedrich, R.; Eckert, H.; Divilov, S.; Curtarolo, S.

Hands-on introduction to the AFLOW software for materials design.

Related publications

  • Invited lecture (Conferences)
    International Summer School Materials 4.0, 23.08.2023, Dresden, Deutschland

Permalink: https://www.hzdr.de/publications/Publ-37877
Publ.-Id: 37877


Predictive Design of Novel Two-Dimensional Materials

Friedrich, R.

The predictive power of physical theories has led to remarkable findings such as the discovery of planets,
new elementary particles, and gravitational waves. The Dresden-concept group “Autonomous Materials
Thermodynamics – AutoMaT” leverages ab initio density functional theory as a predictive tool for
materials design. We specifically focus on the data-driven discovery of novel two-dimensional (2D)
materials for future electronics and energy applications with strong partners from HZDR,
Forschungszentrum Jülich, the DFG collaborative research center “Synthetic Two-dimensional
Materials” hosted at TU Dresden, and Duke University (United States).
Two-dimensional (2D) materials are traditionally derived from bulk layered compounds. The recent
surprising experimental realization of some 2D sheets obtained from non-layered crystals [1,2]
foreshadows a new direction for this diverse class of nanostructures. Generalizing these findings, we
recently predicted by data-driven methods and autonomous ab initio calculations a large set of novel
representatives [3,4] (see Figure 1). They exhibit diverse magnetic properties such as complex surface
spin polarizations enabling spintronics. These systems are thus an attractive platform for fundamental and
applied nanoscience.
[1] A. Puthirath Balan et al., Nat. Nanotechnol. 13, 602 (2018).
[2] A. Puthirath Balan et al., Chem. Mater. 30, 5923 (2018).
[3] R. Friedrich et al., Nano Lett. 22, 989 (2022).
[4] T. Barnowsky et al., Adv. Electron. Mater. 2201112 (2023).

Related publications

  • Lecture (Conference)
    HZDR Science Conference, 16.11.2023, Dresden, Deutschland

Permalink: https://www.hzdr.de/publications/Publ-37876
Publ.-Id: 37876


Data-driven Design of Novel Materials and Interfaces Enabling Future Technologies

Friedrich, R.

Every technology is intimately connected to a certain materials platform. Information technology is based
on silicon, modern batteries are made from lithium compounds, and magnetic materials are important for
the energy sector. Moreover, interfaces between materials are often the enabler of dedicated
functionalities calling for not only the design of individual materials but also of their interfaces.
The Dresden-concept group “Autonomous Materials Thermodynamics – AutoMaT” leverages state of the
art predictive computational methods for materials and interface design. We specifically focus on the
data-driven discovery of novel two-dimensional (2D) materials for future electronics and energy
applications with strong partners from the DFG collaborative research center 1415 “Synthetic Two-dimensional
Materials” hosted at TU Dresden, HZDR, Forschungszentrum Jülich, and Duke University
(United States).
Two-dimensional materials are traditionally derived from bulk layered compounds. The recent surprising
experimental realization of some 2D sheets obtained from non-layered crystals foreshadows a new
direction for this diverse class of nanostructures. Generalizing these findings, we recently predicted by
data-driven methods and autonomous ab initio calculations a large set of novel representatives. They
exhibit appealing magnetic properties enabling spintronics. These systems and their interfaces are thus an
attractive platform for fundamental and applied nanoscience.

Related publications

  • Invited lecture (Conferences) (Online presentation)
    DRESDEN-concept lunch retreat, 21.11.2023, Dresden, Deutschland

Permalink: https://www.hzdr.de/publications/Publ-37875
Publ.-Id: 37875


Data-Driven Materials Science

Friedrich, R.

Invited talk at the HZDR data management day.

Related publications

  • Invited lecture (Conferences)
    HZDR Data Management Day, 21.11.2023, Dresden, Deutschland

Permalink: https://www.hzdr.de/publications/Publ-37874
Publ.-Id: 37874


The Multi-Dimensional Problem of Discovering Novel (Two-Dimensional) Materials

Friedrich, R.

Invited talk at the AFLOW seminar series.

Related publications

  • Invited lecture (Conferences) (Online presentation)
    AFLOW seminar, 09.11.2023, online, online

Permalink: https://www.hzdr.de/publications/Publ-37873
Publ.-Id: 37873


Ion Irradiation-Induced Sinking of Ag Nanocubes into Substrates

Choupanian, S.; Möller, W.; Seyring, M.; Pacholski, C.; Wendler, E.; Undisz, A.; Ronning, C.

Ion irradiation can cause burrowing of nanoparticles in substrates, strongly depending on the material properties and irradiation parameters. In this study, it is demonstrated that the sinking process can be accomplished with ion irradiation of cube-shaped Ag nanoparticles on top of silicon; how ion channeling affects the sinking rate; and underline the importance of the amorphous state of the substrate upon ion irradiation. Based on these experimental findings, the sinking process is described as being driven by capillary forces enabled by ion-induced plastic flow of the substrate.

Permalink: https://www.hzdr.de/publications/Publ-37872
Publ.-Id: 37872


Experimentelle und rechnerische Bestimmung der Aktivierung für die Rückbauplanung von Kernkraftwerken

Barkleit, A.; Rachamin, R.; Pönitz, E.; Konheiser, J.

Vorstellung der FORKA-Projekte EMPRADO und WERREBA

  • Lecture (Conference)
    55. Kraftwerkstechni­sches Kolloquium, 10.-11.10.2023, Dresden, Deutschland

Permalink: https://www.hzdr.de/publications/Publ-37871
Publ.-Id: 37871


Comparative structural and (radio-)chemical investigations of activated cement and concrete samples

Zilbermann, M. E.

To help with the decommissioning of the unit 2 of the Greifswald NPP, this study aims at determining the activities of 3H, 14C, 60Co, 152Eu and 154Eu in the concrete to estimate the maximal activity in the entire bioshield.
The study will focus on the activity as a function of depth in the concrete layer, as well as composition of the mineral phases. As the flux of neutrons generated during fission reaction encounters the mineral phases of concrete, the natural elements present in these phases absorb neutrons, which leads to the formation of their radioactive isotopes. Therefore, the elemental composition of each mineral phase in the concrete is important in the activation process, and the concrete being a heterogeneous material, different phases will present different activities.
A precise knowledge of the activities and of the elemental composition of the concrete and its mineral phases helps refining the models to calculate and predict the activities in a long-term scale. The calculations and the experimental results support the sorting of the materials for disposal.
This study will analyze the concrete with three main objectives:

  • Activation;
  • Chemical composition;
  • Structure of the concrete and mineral phases.
  • Master thesis
    TU Dresden, 2023
    Mentor: Prof. Dr. Thorsten Stumpf, Dr. Astrid Barkleit

Permalink: https://www.hzdr.de/publications/Publ-37870
Publ.-Id: 37870


Multi-scale and multi-source hyperspectral imaging for mapping lithium-bearing minerals

Booysen, R.; Kirsch, M.; Thiele, S. T.; Lorenz, S.; Madriz Diaz, Y. C.; Nex, P.; Kinnaird, J.; Gloaguen, R.

The transition towards a net-zero economy has led to an increased need for several critical raw materials required for green technologies. Lithium (Li) is one of these materials. Significant mineral exploration using sustainable, efficient and innovative methods is required to not only improve mineral detection and mapping, but also to foster social acceptability for the mining and exploration industry. Hyperspectral imaging (HSI) allows for fast and systematic identification of key minerals. In this contribution, we propose an innovative approach for exploration by using hyperspectral data from multiple sensors at various scales to non-invasively map ore and pathfinder minerals. We showcase this approach in an open-pit and under-ground sites in South Africa, Namibia and Germany by acquiring data in the short-wave infrared (SWIR) with both a tripod and a drone. Hand-samples and drill-cores were used to identify the relevant minerals as well as for training/validation purposes. Using computer vision techniques, we were able to create a three-dimensional (3D) point cloud of the sites with HSI attributes to allow for the subsequent spectral mapping of relevant Li-bearing minerals. Results were validated using drill-core data, LIBS measurements and geochemical analyses of hand samples.

Keywords: Lithium-bearing minerals; Hyperspectral imaging; Multi-scale

  • Contribution to proceedings
    17th SGA Biennial Meeting, 28.08.-01.09.2023, Zurich, Switzerland

Permalink: https://www.hzdr.de/publications/Publ-37869
Publ.-Id: 37869


Hyperspectral Imaging for Mapping Outcropping Li-bearing Pegmatites

Booysen, R.; Lorenz, S.; Madriz Diaz, Y. C.; Fuchsloch, W.; Nex, P.; Marais, T.; Gloaguen, R.

The transition towards a net-zero economy has led to an increased need for several critical raw materials required for green technologies. Lithium (Li) is one of these materials, which is experiencing a sharp increase in demand that recycling alone is not capable of meeting. Significant mineral exploration using sustainable, efficient and innovative methods is required to not only improve mineral detection and mapping, but also foster social acceptability for the mining and exploration industry. Hyperspectral imaging (HSI) is a rapidly developing technology that allows for fast and systematic identification of key minerals and provides information about mineral abundances and associations. In this contribution, we propose an innovative approach for exploration by using hyperspectral data from multiple sensors at various scales to non-invasively map ore and pathfinder minerals. We showcase this approach at the Uis pegmatite complex located in Namibia. Hand-samples taken at the Uis pit were used to identify the relevant minerals as well as for training/validation purposes, and we acquired HSI data of the pit using a short-wave infrared (SWIR) camera mounted on a tripod. Using machine learning and computer vision techniques, we upscaled this information to the outcrop scale and created a three-dimensional (3D) point cloud of the pit with HSI attributes to map relevant Li-bearing minerals, such as cookeite and montebrasite. Results were validated using drill-core data, LIBS measurements and XRF analyses. We recently acquired uncrewed-aerial vehicle (UAV)-based SWIR data, to allow flexible data acquisition and mitigate access limitations. With in-house tools, the data is being processed (e.g., geometric and radiometric corrections) and we expect to map Li-bearing minerals in a similar manner. This approach enables rapid and efficient mapping of complex terrains in a sustainable exploration scheme, and can be used for monitoring and optimisation of ore extraction.

Keywords: UAV; Drones; Hyperspectral imaging; Pegmatites; Lithium

  • Contribution to proceedings
    Society of Economic Geologists 2022 Conference: Minerals For Our Future, 27.-30.08.2022, Denver, USA

Permalink: https://www.hzdr.de/publications/Publ-37868
Publ.-Id: 37868


Innovative hyperspectral imaging for Lithium exploration

Booysen, R.; Thiele, S. T.; Lorenz, S.; Madriz Diaz, Y. C.; Nex, P.; Gloaguen, R.

The current transition towards a sustainable future is rooted in the use of green technologies. These technologies have led to a large rise in demand for previously obscure minerals and metals. One such sought-after element is lithium (Li), due to its use in Li-ion batteries for electric vehicles. Recycling alone cannot meet the present demand for this material, thus exploration of new resources and the improvement of existing mining activities are required. Conventional exploration methods are typically performed by a team of geoscientists and involve geological fieldwork, geophysical surveys and extensive drilling. These methods are time-consuming, expensive, vulnerable to weather conditions or in-accessible terrains and often carry a considerable environmental impact. In the case of Li exploration, the typical geochemical analyses and assaying methods fall short in accurately identifying and quantifying the presence of Li. Therefore, we suggest a non-invasive, hyperspectral imaging (HSI) approach for the detection of mineralized outcrops. HSI is a fast developing technology that allows for rapid mineral mapping, facilitating mineral exploration at various scales. In this contribution, we demonstrate our approach at the Uis Li-bearing pegmatite mine in Namibia by utilizing a variety of platforms and sensors in order to map key minerals associated with Li-mineralization. We collected hand samples from the main pit to identify relevant minerals. In addition, we captured hyperspectral data covering the main pit in the visible and near infrared (VNIR) and short-wave infrared (SWIR) range of the electromagnetic spectrum with a tripod mounted hyperspectral sensor. We acquired RGB photos of the main pit for Structure-from-Motion (SfM) multi-view stereo (MVS) photogrammetry to create a three-dimensional (3D) model. By using computer vision and machine learning techniques, we combined the hyperspectral data with the 3D information to produce a 3D point cloud with hyperspectral attributes. This workflow was performed using the open-source python based toolbox hylite and allowed us to produce a geometrically correct and spatially continuous 3D map of Li-bearing minerals. We validated our result with drill-core data as well as laser induced breakdown spectroscopy (LIBS) measurements and X-ray fluorescence (XRF) analyses of the hand samples. Additionally, we recently acquired drone-borne SWIR data over the same mine, allowing for more flexible data acquisition in order to mitigate access limitation. Taking a HSI approach enables us to rapidly and efficiently map complex terrains in a non-invasive and sustainable exploration scheme.

Keywords: Lithium; Hyperspectral imaging; Pegmatite

  • Open Access Logo Contribution to proceedings
    12th IEEE Whispers Conference - Hyperspectral Image and Signal Processing, 13.-16.09.2022, Rome, Italy

Permalink: https://www.hzdr.de/publications/Publ-37867
Publ.-Id: 37867


On the missing single collision peak in low energy heavy ion scattering

Wilhelm, R. A.; Deuzeman, M. J.; Rai, S.; Husinsky, W.; Szabo, P. S.; Biber, H.; Stadlmayr, R.; Cupak, C.; Hundsbichler, J.; Lemell, C.; Möller, W.; Mutzke, A.; Hobler, G.; Versolato, O. O.; Aumayr, F.; Hoekstra, R.

We present experimental and simulation data on the oblique angle scattering of heavy Sn ions at 14 keV energy from a Mo surface. The simulations are performed with the binary collision approximation codes TRIM, TRIDYN, TRI3DYN, SDTrimSP, and IMSIL. Additional simulations were performed in the molecular dynamics framework with LAMMPS. Our key finding is the absence of an expected peak in the experimental energy spectrum of backscattered Sn ions associated with the pure single collision regime. In sharp contrast to this, however, all simulation codes we applied do show a prominent single collision signature both in the energy spectrum and in the angular scatter pattern. We discuss the possible origin of this important discrepancy and show in the process, that widely used binary collision approximation codes may contain hidden parameters important to know and to understand.

Keywords: Binary collision approximation; Heavy ions; Ion scattering; Molecular dynamics

Permalink: https://www.hzdr.de/publications/Publ-37866
Publ.-Id: 37866


Der Einbrennvorgang des Bethe-Weizsäcker-Zyklus

Bemmerer, D.; Rümmler, S.; Herrera, Y.

Das Wasserstoffbrennen in der Sonne wird von der sogenannten Proton-Proton-Kette bestimmt. Ein zweiter, parallel ablaufender Prozess ist der Bethe-Weizsäcker- oder CNO-Zyklus. Bei der Sonne trägt er nur etwa 0,8 % zur Energieerzeugung bei, kann aber zur Bestimmung der Kohlenstoffhäufigkeit im Sonneninnern genutzt werden. Neue Labordaten zur ersten Reaktion im Zyklus zeigen für massereiche Sterne eine 25 % geringere Rate als bislang angenommen, während sich für unsere Sonne wenig ändert.

Permalink: https://www.hzdr.de/publications/Publ-37865
Publ.-Id: 37865


Post growth thermal treatments of Si1-x-yGexSny alloys

Steuer, O.; Schwarz, D.; Oehme, M.; Hübner, R.; Ganss, F.; Khan, M. M.; Cheng, Y.; Rebohle, L.; Zhou, S.; Helm, M.; Cuniberti, G.; Georgiev, Y.; Prucnal, S.

Si1-x-yGexSny alloys are promising materials for future applications in opto- and nanoelectronics. These alloys enable effective band gap engineering, a broad adjustability of the lattice parameter, exhibit much higher carrier mobility than pure Si and are compatible with CMOS technology. Unfortunately, the equilibrium solid solubility of Sn in Si1-xGex is less than 1% and pseudomorphic growth of Si1-xyGexSny on Ge or Si causes in-plane compressive strain in the grown layer, which degrades the superior properties of the alloys. Therefore, the post-growth strain engineering using ultrafast non-equilibrium thermal treatments like flash lamp annealing (FLA) or pulsed laser annealing (PLA) to improve the layer quality is needed. In this contribution, we discuss the influence of millisecond FLA and nanosecond PLA on Si1-x-yGexSny alloys and present an efficient way to improve the layer quality of thin film Si1-x-yGexSny on insulator by PLA. Different Si1-xyGexSny alloys are directly grown on commercial silicon-on-insulator (SOI) wafers and treated by FLA or PLA. The material is analysed by micro-Raman spectroscopy, Rutherford backscattering spectrometry (RBS) and X-ray diffraction (XRD) before and after the thermal treatments. It is shown that after annealing, the material is single-crystalline with much better crystallinity than the as-grown layer.

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  • Poster
    E-MRS 2023 Spring Meeting, 29.05.-02.06.2023, Strasbourg, Frankreich

Permalink: https://www.hzdr.de/publications/Publ-37864
Publ.-Id: 37864


Post growth thermal treatments of Silicon-Germanium-Tin-on-insulator alloys

Steuer, O.; Schwarz, D.; Oehme, M.; Hübner, R.; Ganss, F.; Khan, M. M.; Cheng, Y.; Rebohle, L.; Zhou, S.; Helm, M.; Cuniberti, G.; Georgiev, Y.; Prucnal, S.

Si1-x-yGexSny alloys are promising materials for future applications in opto- and nanoelectronics. These alloys enable effective band gap engineering, a broad adjustability of the lattice parameter, exhibit much higher carrier mobility than pure Si and are compatible with CMOS technology. Unfortunately, the equilibrium solid solubility of Sn in Si1-xGex is less than 1% and pseudomorphic growth of Si1-xyGexSny on Ge or Si causes in-plane compressive strain in the grown layer, which degrades the superior properties of the alloys. Therefore, the post-growth strain engineering using ultrafast non-equilibrium thermal treatments like flash lamp annealing (FLA) or pulsed laser annealing (PLA) to improve the layer quality is needed. In this contribution, we discuss the influence of millisecond FLA and nanosecond PLA on Si1-x-yGexSny alloys and present an efficient way to improve the layer quality of thin film Si1-x-yGexSny on insulator by PLA. Different Si1-xyGexSny alloys are directly grown on commercial silicon-on-insulator (SOI) wafers and treated by FLA or PLA. The material is analysed by micro-Raman spectroscopy, Rutherford backscattering spectrometry (RBS) and X-ray diffraction (XRD) before and after the thermal treatments. It is shown that after annealing, the material is single-crystalline with much better crystallinity than the as-grown layer.

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  • Poster
    3rd Joint International Conference on Silicon Epitaxy and Heterostructures & International SiGe Technology and Device Meeting, 22.-25.05.2023, Como, Italy

Permalink: https://www.hzdr.de/publications/Publ-37863
Publ.-Id: 37863


Evolution of point defects in pulsed-laser-melted Ge1-xSnx probed by positron annihilation lifetime spectroscopy

Steuer, O.; Liedke, M. O.; Butterling, M.; Schwarz, D.; Schulze, J.; Li, Z.; Wagner, A.; Fischer, I. A.; Hübner, R.; Zhou, S.; Helm, M.; Cuniberti, G.; Georgiev, Y.; Prucnal, S.

Rohdaten und analysedaten der Publikation

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Permalink: https://www.hzdr.de/publications/Publ-37862
Publ.-Id: 37862


Data publication: Aluminium substituted yttrium iron garnet thin films with reduced Curie temperature

Scheffler, D.; Steuer, O.; Zhou, S.; Siegl, L.; Goennenwein, S. T. B.; Lammel, M.

RBS Messungen der Aluminium substituted yttrium iron garnet thin films

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Permalink: https://www.hzdr.de/publications/Publ-37861
Publ.-Id: 37861


Aluminium substituted yttrium iron garnet thin films with reduced Curie temperature

Scheffler, D.; Steuer, O.; Zhou, S.; Siegl, L.; Goennenwein, S. T. B.; Lammel, M.

Magnetic garnets such as yttrium iron garnet (Y3 Fe 5 O12 , YIG) are widely used in spintronic and magnonic
devices. Their magnetic and magneto-optical properties can be modified over a wide range by tailoring their
chemical composition. Here, we report the successful growth of Al-substituted yttrium iron garnet (YAlIG) thin
films via radio frequency sputtering in combination with an ex situ annealing step. Upon selecting appropriate
process parameters, we obtain highly crystalline YAlIG films with different Al 3+ substitution levels on both
single crystalline Y 3 Al 5 O12 (YAG) and Gd 3 Ga 5 O12 (GGG) substrates. With increasing Al 3+ substitution levels,
we observe a reduction of the saturation magnetization as well as a systematic decrease of the magnetic ordering
temperature to values well below room temperature. YAlIG thin films thus provide an interesting material
platform for spintronic and magnonic experiments in different magnetic phases.

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Permalink: https://www.hzdr.de/publications/Publ-37860
Publ.-Id: 37860


Comparando las estimaciones de selección de hábitat mediante modelos de distribución de especies y step selection functions

Saraiva De Menezes, J. F.

Recently, two methods of habitat selection have gained more relevance in the scientific literature: step selection functions (SSF) and MaxEnt. Despite their similarity these models are hardly ever used in the same context. The former is usually associated with studies based in movement ecology, and the latter is connected to species distribution modeling. Motivated by the difficulty in estimating habitat preferences using SSF, I compared the accuracy of predictions from both models based on movement data. As a case study, I utilized jaguar movement data from 5 countries in Latin American and created SSF and MaxEnt models based on climatic data and land use available from WorldClim and satellite imagery. I compared the accuracy of both types of models using the “Area Under Curve” (AUC) metric, on a separate subset of data. SSF models presented an average AUC of 0.5510 ± 0.0147 in comparison with 0.7544 ± 0.0185 of their MaxEnt equivalents. I believe those differences are partially caused by the convergence difficulties of SSF and conditional logistic regression. Consequently, I recommend the use of MaxEnt in predictive modelling, such as the ones needed in reserve and corridor design.

Keywords: Latin America; Jaguars; niche modelling; resource selection function; trajectory

Permalink: https://www.hzdr.de/publications/Publ-37859
Publ.-Id: 37859


Data publication: SAPPHIRE - Establishment of small animal proton and photon image-guided radiation experiments

Schneider, M.; Schilz, J.; Schürer, M.; Gantz, S.; Dreyer, A.; Rothe, G.; Tillner, F.; Bodenstein, E.; Horst, F. E.; Beyreuther, E.

This repository contains the data shown in the results part of the paper entitled: SAPPHIRE - Establishment of small animal proton and photon image-guided radiation experiments.

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Permalink: https://www.hzdr.de/publications/Publ-37852
Publ.-Id: 37852


Data publication: Preparation of 18F-Labeled Tracers Targeting Fibroblast Activation Protein via Sulfur [18F]Fluoride Exchange Reaction

Craig, A.; Kogler, J.; Laube, M.; Ullrich, M.; Donat, C.; Wodtke, R.; Kopka, K.; Stadlbauer, S.

The data concerns the preparation of two new 18F-labeled radiotracers using a ultra-fast radiolabeling method for tumor detection using positron emission tomography (PET) imaging.

Keywords: Automation; cancer-associated fibroblast; FAPI; 18F-fluorination; positron emission tomography (PET); [18F]SuFEx

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Permalink: https://www.hzdr.de/publications/Publ-37850
Publ.-Id: 37850


Nontrivial Aharonov-Bohm effect and alternating dispersion of magnons in cone-state ferromagnetic rings

Uzunova, V.; Körber, L.; Kavvadia, A.; Quasebarth, G.; Schultheiß, H.; Kakay, A.; Ivanov, B.

Soft magnetic dots in the form of thin rings have unique topological properties. They can be in a vortex state with no vortex core. Here, we study the magnon modes of such systems both analytically and numerically. In an external magnetic field, magnetic rings are characterized by easy-cone magnetization and shows a giant splitting of doublets for modes with the opposite value of the azimuthal mode quantum number. The effect of the splitting can be refereed as a magnon analog of the topology-induced Aharonov-Bohm effect. For this we develop an analytical theory to describe the non-monotonic dependence of the mode frequencies on the azimuthal mode number, influenced by the balance between the local exchange and non-local dipole interactions.

Keywords: Spin waves; Topology; Vortex; Magnetism; Aharonov-Bohm effect; Micromagnetism

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Permalink: https://www.hzdr.de/publications/Publ-37849
Publ.-Id: 37849


Using Julia to Accelerate Monte Carlo Event Generation with Neural Importance Sampling

Jungnickel, T.; Steiniger, K.; Bussmann, M.; Hernandez Acosta, U.

Monte Carlo event generation is essential for analysis in high energy physics and fast implementations are required to keep up with the large amounts of data measured by experiments. Therefore, these methods need to reflect the theoretical predictions accurately to enable efficient data generation, e.g. by rejection sampling. However, traditional importance sampling algorithms, such as the commonly used VEGAS algorithm, often struggle with adapting targets with multiple or non-coordinate aligned features, as is common in high energy physics. Especially in strong-field QED, processes dynamically depend on field parameters, which means the use of established codes for these problems needs to be questioned. An importance sampling approach using neural networks applied to strong-field processes is presented within the framework QED.jl. The quality of the generated proposals, e.g. the unweighting efficiency, is compared to VEGAS, providing insights beneficial to applications beyond strong-field QED.

Keywords: strong field QED; machine learning; Julia; QED.jl; neural importance sampling

  • Lecture (Conference)
    JuliaHEP 2023, 06.-09.11.2023, Erlangen, Deutschland

Permalink: https://www.hzdr.de/publications/Publ-37848
Publ.-Id: 37848


Investigation of Mixing using Microfocus X-ray Computed Tomography (µCT)

Baecke, A. M.

Fine-grained solid particles from various industrial sources, which would otherwise be discarded, should ideally be processed to valuable products or inert residues. Among others, a) shredder fines from electronics and end-of-life vehicles, and b) flue dusts from non-ferrous metallurgical processes are of timely interest. They contain valuable residuals, such as metals, that can be returned to the industrial cycle instead of being landfilled. This is one aim of the Helmholtz project FINEST in which this work is embedded. In this work, mixing and agglomeration of such particles with a size below 1 mm are investigated for further use in the metallurgical industry. Different particle sizes and densities are considered. The process is observed experimentally using camera imaging technique and µCT. From the µCT images a mixing index is acquired. We present an experimental setup and methods for the aforementioned investigations.

Keywords: Microfocus X-Ray Computed Tomography; Particle Flow; Mixing and Segregation

  • Lecture (Conference)
    Bałdyga Technical Seminars - Mixing meets reality, 14.-15.09.2023, Berlin, Deutschland

Permalink: https://www.hzdr.de/publications/Publ-37846
Publ.-Id: 37846


Accelerating Event Generation in Strong-Field QED with Neural Importance Sampling

Jungnickel, T.; Steiniger, K.; Hernandez Acosta, U.; Bussmann, M.

Efficient Monte Carlo integreation is crucial for modeling processes at the European XFEL. However, traditional approaches to importance sampling like VEGAS do not perform well when integrands display multiple features or non-coordinate aligned features. In this work, we present an implementation of neural importance sampling (NIS) in the Julia programming language to address this challenge. We demonstrate the effectiveness of NIS by applying it to processes in strong-field QED at high energies, showing superior adaption of the integrand and thus enabling efficient event generation.

Keywords: strong field QED; machine learning; Julia; QED.jl; neural importance sampling

  • Poster
    Helmholtz AI Conference 2023, 12.-14.06.2023, Hamburg, Deutschland

Permalink: https://www.hzdr.de/publications/Publ-37845
Publ.-Id: 37845


Probing Iron in Earth's Core With Molecular-Spin Dynamics

Nikolov, S.; Ramakrishna, K.; Rohskopf, A.; Lokamani, M.; Tranchida, J.; Carpenter, J.; Cangi, A.; Wood, M. A.

Dynamic compression of iron to Earth-core conditions is one of the few ways to gather important elastic and transport properties needed to uncover key mechanisms surrounding the geodynamo effect. Herein a new machine-learned ab-initio derived molecular-spin dynamics (MSD) methodology with explicit treatment for longitudinal spin-fluctuations is utilized to probe the dynamic phase-diagram of iron. This framework uniquely enables an accurate resolution of the phase-transition kinetics and Earth-core elastic properties, as highlighted by compressional wave velocity and adiabatic bulk moduli measurements. In addition, a unique coupling of MSD with time-dependent density functional theory enables gauging electronic transport properties, critically important for resolving geodynamo dynamics.

Keywords: Molecular dynamics; Density functional theory; Machine Learning; Phase transitions; Geodynamo

Permalink: https://www.hzdr.de/publications/Publ-37844
Publ.-Id: 37844


Critical review on production, characterization and applications of microalgal hydrochar: Insights on circular bioeconomy through hydrothermal carbonization

Supraja, K. V.; Doddapaneni, T. R. K. C.; Ramasamy, P. K.; Kaushal, P.; Ahammad, S. Z.; Pollmann, K.; Jain, R.

Exploitation of microalgal biomass as a valuable resource is hindered by the challenges associated with high downstream
processing costs, including biomass harvesting, drying, and product extraction. Direct utilization of microalgae as a solid fuel
source, soil conditioner, capacitor or adsorbent material raises environmental concerns. Hydrothermal carbonization (HTC)
is a highly efficient and promising technology for microalgal biomass conversion. This comprehensive review provides an indepth
understanding of the HTC reaction mechanisms involved in microalgal hydrochar production, shedding light on the
underlying processes and factors affecting the quality of hydrochar. HTC has the potential to improve fixed carbon content,
thermal stability and nutrient availability in the resulting hydrochar. Furthermore, this review explores the integration of HTC
with anaerobic digestion (AD) to establish a circular bioeconomy, thereby promoting sustainability in energy generation. The
synergistic combination offers a promising approach for the efficient utilization of microalgal biomass, where hydrochar can
serve as a renewable energy source while the aqueous fraction can be utilized as a nutrient-rich feedstock for biogas
production. By highlighting the potential benefits and futuristic directives associated with microalgal biomass valorisation
through HTC, this review aims to contribute to the development of sustainable waste management strategies for recovery of
value-added compounds from microalgae. Ultimately, this review strives to foster the transition towards a more
environmentally friendly and resource-efficient bioeconomy.

Keywords: Algae; Anaerobic digestion; Bioconversion; Biomass; Carbonization; Microorganisms; Nutrients; Soils

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  • Secondary publication expected from 01.10.2024

Permalink: https://www.hzdr.de/publications/Publ-37842
Publ.-Id: 37842


Rohstoffe und Ressourcen

Möckel, R.

Im Vortrag geht es um Resourcen und Rohstoffe, Einteilung, Kritikalität, circular economy, Recycling und Alternativen, sowie als Beispiel um Seltene Erden

  • Lecture (others)
    Schulische Veranstaltung, 27.10.2023, Chemnitz, Montessori-Gymnasium, Deutschland

Permalink: https://www.hzdr.de/publications/Publ-37839
Publ.-Id: 37839


Mineralogy, Geochemistry, and Genesis of Agates from Chihuahua, Northern Mexico

Mrozik, M.; Götze, J.; Pan, Y.; Möckel, R.

The present study aimed to investigate the genesis and characteristics of some of the world-famous agate deposits in the state of Chihuahua, Mexico (Rancho Coyamito, Ojo Laguna, Moctezuma, Huevos del Diablo, Agua Nueva). Geochemical and textural studies of host rocks showed that all the studied deposits are related to the same rock type within the geological unit of Rancho el Agate andesite, a quartz-free latite that shows clear indications of magma mixing. As a result of their large-scale distribution and various differentiation processes, as well as transport separation, different textures and local chemical differences between rocks of different localities can be observed. These differences have also influenced the properties of SiO2 mineralization in the rocks. The mixing of near-surface fluids from rock alterations with magmatic hydrothermal solutions led to the accumulation of various elements in the SiO2 matrix of the agates, which were, on the one hand, mobilized during secondary rock alteration (Fe, U, Ca, K, Al, Si) and, on the other hand, transported with magmatic fluids (Zn, Sb, Si, Zr, Cr). Different generations of chalcedony indicate a multi-stage formation as well as multiple cycles of filling the cavities with fluids. The hydrothermal fluids are presumably related to the residual solutions of a rhyolitic volcanism, which followed the latitic extrusions in the area and probably caused the formation of polymetallic ore deposits in the Chihuahua area. The enrichment of highly immobile elements indicates the involvement of volatile fluids in the agate formation. The vivid colors of the agates are almost exclusively due to various mineral inclusions, which consist mainly of iron compounds.

Keywords: agate; chalcedony; trace elements; EPR spectroscopy; silica minerals; agate colors; cathodoluminescence; geology; Rancho Coyamito; Ojo laguna; Moctezuma; Agua Nueva

Permalink: https://www.hzdr.de/publications/Publ-37838
Publ.-Id: 37838


Characterisation of the grain morphology of artificial minerals (EnAMs) in lithium slags by correlating multi-dimensional 2D and 3D methods

Rachmawati, C.; Weiss, J.; Lucas, H.; Löwer, E.; Leißner, T.; Ebert, D.; Möckel, R.; Friedrich, B.; Peuker, U. A.

Slags from the metallurgical recycling process are an important source of resources classified as critical elements by the EU. One example is Lithium from Li-ion battery recycling. In this context, the thermodynamic properties of the recycled component system play a significant role in the formation of the Li-bearing phases in the slag, in this case, LiAlO2. The LiAlO2 crystal formation could be engineered and result in varying sizes and occurrences by different metallurgical processing conditions. This study uses pure ingredients to provide synthetic model material used to generate the valuable phase in the slag, or so-called engineered artificial minerals (EnAMs). The goal is to study the crystallisation of the LiAlO2 as EnAM by controlling cooling conditions of the 23
model slag to optimise the EnAM formed during crystallisation. Characterisation of the EnAMs is an important step before further mechanically processing the material to recover the valuable element Li, the Li bearing species respectively. Investigations with powder X-ray diffraction (XRD), X-ray fluorescence (μXRF), and X-ray Computer Tomography (XCT) of two different artificial lithium slags from MnO-Al2O3-SiO2-CaO systems with different cooling temperature gradients show the different EnAM morphology along the height of the slag that is formed with different slag production condition in a semi-pilot scale experiment of 5 kg. Three defined qualities of the EnAM are identified based on the different EnAM morphologies, which show granular shape, dendritic shape, or by imaging techniques hardly visible EnAM structures.

Keywords: engineered artificial mineral (EnAM); slag characterisation; LiAlO2 (lithium aluminate); X-ray micro-CT; micro-XRF

Permalink: https://www.hzdr.de/publications/Publ-37837
Publ.-Id: 37837


A new approach to model the fluid dynamics in sandwich packings

Franke, P.; Shabanilemraski, I.; Schubert, M.; Hampel, U.; Kenig, E. Y.

Sandwich packings represent new separation column internals, with a potential to intensify mass
transfer. They comprise two conventional structured packings with different specific geometrical surface areas.
In this work, the complex fluid dynamics in sandwich packings is modeled using a novel approach based on a onedimensional,
steady momentum balance of the liquid and gas phases. The interactions between the three present
phases (gas, liquid, and solid) are considered by closures incorporated into the momentum balance. The
formulation of these closures is derived from two fluid-dynamic analogies for the film and froth flow patterns.
The adjustable parameters in the closures are regressed for the film flow using dry pressure drop measurements
and liquid hold-up data in trickle flow conditions. For the froth flow, the tuning parameters are fitted to overall
pressure drop measurements and local liquid hold-up data acquired from ultra-fast X-ray tomography (UFXCT).
The model predicts liquid hold-up and pressure drop data with an average relative deviation of 16.4 % and 19 %,
respectively. Compared to previous fluid dynamic models for sandwich packings, the number of adjustable
parameters could be reduced while maintaining comparable accuracy.

Keywords: sandwich packings; modeling; tomography; fluid dynamics

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Permalink: https://www.hzdr.de/publications/Publ-37836
Publ.-Id: 37836


Data publication: Fluid Transport in Ordinary Portland Cement and Slag Cement from in-situ Positron Emission Tomography

Reiss, A.; Kulenkampff, J.; Fischer, C.
RelatedPerson: Gruhne, Stefan; RelatedPerson: Lösel, Dagmar; RelatedPerson: Schößler, Claudia

Supplemental Primary PET Data to Fluid Transport in Ordinary Portland Cement and Slag Cement from in-situ Positron Emission Tomography Reiss, A.; Kulenkampff, J.; Bar-Nes, G.; Fischer, C.; Emmanuel, S. Submitted to Cement and Concrete Research 02.11.24 Material and procedure are characterized in the paper. PET data are supplied in Interfile format (Original: Cradduck T.D., Bailey D.L., Hutton BF, Deconinck F., Busemann Sokole E., Bergmann H., Noelpp U.: “A standard protocol for the exchange of nuclear medicine image files. Nucl Med Commun; 10:703-713 (1989), used version: https://stir.sourceforge.net/links/petinterfile03.pdf). The interfile format includes an ASCII header file (.hv) and a binary file containing the volume data (.v). Import filters exist for many visualization frameworks (e.g. Matlab, Avizo); otherwise the binary data files can be imported as raw data, taking into account the format given in the header file. The header tags were extended for relevant experimental parameters of non-medical PET experiments and in this way serve as experimental protocol. List of data files: cem1_F-18.7z: 17 PET frames from the 18F intrusion experiment cem1_Cu-64.7z: 31 PET frames from the 64Cu intrusion experiment cem1_I-124.7z: 34 PET frames from the 124I intrusion experiment The PET data sets (LMFs) were acquired with a tilted ClearPET-scanner (Elysia-Raytest) with a vertical axis of the cylindrical FOV at HZDR. The “trues”-projections were corrected for attenuation and scatter with a procedure based on the STIR-library (https://stir.sourceforge.net, version 3.0, Kris Thielemans, Charalampos Tsoumpas, Sanida Mustafovic, Tobias Beisel, Pablo Aguiar, Nikolaos Dikaios, and Matthew W Jacobson, STIR: Software for Tomographic Image Reconstruction Release 2, Physics in Medicine and Biology, 57 (4), 2012 pp.867-883).

Keywords: Positron Emission Tomography (PET); Imbibition; Cement paste; Fluid transport

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Permalink: https://www.hzdr.de/publications/Publ-37835
Publ.-Id: 37835


Large-Scale Formation of DNA Origami Lattices on Silicon

Tapio, K.; Kielar, C.; Parikka, J. M.; Keller, A.; Järvinen, H.; Fahmy, K.; Jussi Toppari, J.

In recent years, hierarchical nanostructures have found applications in fields like diagnostics, medicine, nano-optics, and nanoelectronics, especially in challenging applications like the creation of metasurfaces with unique optical properties. One of the promising materials to fabricate such nanostructures has been DNA due to its robust self-assembly properties and plethora of different functionalization schemes. Here, we demonstrate the assembly of a two-dimensional fishnet-type lattice on a silicon substrate using cross-shaped DNA origami as the building block, i.e., tile. The effects of different environmental and structural factors are investigated under liquid atomic force microscopy (AFM) to optimize the lattice assembly. Furthermore, the arm-to-arm binding affinity of the tiles is analyzed, revealing preferential orientations. From the liquid AFM results, we develop a methodology to produce closely-spaced DNA origami lattices on silicon substrate, which allows further nanofabrication process steps, such as metallization. This formed polycrystalline lattice has high surface coverage and is extendable to the wafer scale with an average domain size of about a micrometer. Further studies are needed to increase the domain size toward a single-crystalline large-scale lattice.

Permalink: https://www.hzdr.de/publications/Publ-37834
Publ.-Id: 37834


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