Publications Repository - Helmholtz-Zentrum Dresden-Rossendorf

Nb-94 is a constituent of the radioactive waste in the dismantling process of nuclear power plants. It has a half-life of 20300 a and has to be considered in the risk assessment [1]. This motivates the need for a suitable Nb-radiotracer, which allows to investigate the interaction of Nb in future waste repositories. Half-life and decay mode suggest the isotope Nb-95 as promising candidate.

Hydrogen isotopes are studied in many research areas to clarify fundamental and applied aspects of their physicochemical behavior. Besides deuterium, the isotope tritium has become the focus of current investigations. One important application is the separation of hydrogen isotopes. Currently available methods have low separation efficiency and high energy consumption. Therefore, approaches to increase efficiency are presently being explored, with a focus on gaseous deuterium.
In our work we will investigate two types of materials, on the one hand membrane materials (graphene and Nafion) and on the other hand nanoporous materials (metal-organic frameworks) with respect to tritium separation. For these studies, we needed to establish an analytical routine for working with gaseous tritium, from access to quantification methods. For this purpose, we employed a tritium manifold that uses heat to release gaseous tritium from a reservoir in a defined manner. The tritium gas under defined pressure and, in the future, mixtures of hydrogen isotopes will be used for separation experiments in flow cells. The gas will eventually be converted to HTO, which will be analyzed by liquid scintillation counting (LSC), where the measured activity directly corresponds to the concentration of tritium in the analyzed sample. To assess the quality of the proposed analytical method, the data obtained from the LSC measurements were compared with the calculated values and with the pressures applied during tritium dosing from the manifold. The measured values correspond directly to the applied pressures and agree well with the calculated data. These results indicate the proficiency of the established analytical approach, which allows to explore the proposed separation methods with high precision.

Bergmann’s Rule—which posits that larger animals live in colder areas—is thought to influence variation in body size within species across space and time, but evidence for this claim is mixed. We tested four competing hypotheses for spatio-temporal variation in body size within bat species during the past two decades across North America: (1) the heat conservation hypothesis, which posits that increased body size facilitates body heat conservation (and which is the traditional explanation for the mechanism underlying Bergmann’s Rule); (2) the heat mortality hypothesis, which posits that increased body size increases susceptibility to acute heat stress; (3) the resource availability hypothesis, which posits that increased body size is enabled in areas with more abundant food; and (4) the starvation resistance hypothesis, which posits that increased body size reduces susceptibility to starvation during acute food shortages. Bayesian hierarchical models revealed that spatial variation in body mass was most consistently (and negatively) correlated with mean annual temperature, supporting the heat conservation hypothesis. Across time, variation in body mass was most consistently (and positively) correlated with net primary productivity, supporting the resource availability hypothesis. Climate change could influence body size in animals through both changes in mean annual temperature and in resource availability. Rapid reductions in body size associated with increasing temperatures have occurred in short-lived, fecund species, but such reductions likely transpire more slowly in longer-lived species.

Background: The photon strength functions (PSFs) and nuclear level density (NLD) are key ingredients for
calculation of the photon interaction with nuclei, in particular the reaction cross sections. These cross sections are
important especially in nuclear astrophysics and in the development of advanced nuclear technologies.
Purpose: The role of the scissors mode in the M1 PSF of (well-deformed) actinides was investigated by several
experimental techniques. The analyses of different experiments result in significant differences, especially on the
strength of the mode. The shape of the low-energy tail of the giant electric dipole resonance is uncertain as well.
In particular, some works proposed a presence of the E1 pygmy resonance just above 7 MeV. Because of these
inconsistencies additional information on PSFs in this region is of great interest.
Methods: The γ -ray spectra from neutron-capture reactions on the 234U, 236U, and 238U nuclei have been
measured with the total absorption calorimeter of the n_TOF facility at CERN. The background-corrected
sum-energy and multi-step-cascade spectra were extracted for several isolated s-wave resonances up to about
140 eV.
Results: The experimental spectra were compared to statistical model predictions coming from a large selection
of models of photon strength functions and nuclear level density. No combination of PSF and NLD models from
literature is able to globally describe our spectra. After extensive search we were able to find model combinations
with modified generalized Lorentzian (MGLO) E1 PSF, which match the experimental spectra as well as the total
radiative widths.
Conclusions: The constant temperature energy dependence is favored for a NLD. The tail of giant electric dipole
resonance is well described by the MGLO model of the E1 PSF with no hint of pygmy resonance. The M1 PSF
must contain a very strong, relatively wide, and likely double-resonance scissors mode. The mode is responsible
for about a half of the total radiative width of neutron resonances and significantly affects the radiative cross
section.

Nuclear astrophysics with accelerator mass spectrometry

Most patients with head and neck squamous cell carcinomas (HNSCC) are diagnosed at a locally advanced stage and show heterogeneous treatment responses. Low SLC3A2 (solute carrier family 3 member 2) mRNA and protein (CD98hc) expression levels are associated with higher locoregional control in HNSCC patients treated with primary radiochemotherapy or postoperative radiochemotherapy, suggesting that CD98hc could be a target for HNSCC radiosensitization. One of the targeted strategies for tumor radiosensitization is precision immunotherapy, e.g., the use of chimeric antigen receptor (CAR) T cells. This study aimed to define the potential clinical value of new treatment approaches combining conventional radiotherapy with CD98hc-targeted immunotherapy. To address this question, we analyzed the antitumor activity of the combination of fractionated irradiation and switchable universal CAR (UniCAR) system against radioresistant HNSCC cells in 3D culture. CD98hc-redirected UniCAR T cells showed the ability to destroy radioresistant HNSCC spheroids. Also, the infiltration rate of the UniCAR T cells was enhanced in the presence of the CD98hc target module. Furthermore, sequential treatment with fractionated irradiation followed by CD98hc-redirected UniCAR T treatment showed a synergistic effect. Taken together, our obtained data underline the improved antitumor effect of the combination of radiotherapy with CD98hc-targeted immunotherapy. Such a combination presents an attractive approach for the treatment of high-risk HNSCC patients.

The oxygen evolution reaction is central to making chemicals and energy carriers using electrons. Combining the great tunability of enzymatic systems with known oxide-based catalysts can create breakthrough opportunities to achieve both high activity and stability. Here we report a series of metal hydroxide–organic frameworks (MHOFs) synthesized by transforming layered hydroxides into two-dimensional sheets crosslinked using aromatic carboxylate linkers. MHOFs act as a tunable catalytic platform for the oxygen evolution reaction, where the π–π interactions between adjacent stacked linkers dictate stability, while the nature of transition metals in the hydroxides modulates catalytic activity. Substituting Ni-based MHOFs with acidic cations or electron-withdrawing linkers enhances oxygen evolution reaction activity by over three orders of magnitude per metal site, with Fe substitution achieving a mass activity of 80 A g_catalyst ^-1 at 0.3 V overpotential for 20 h. Density functional theory calculationscorrelate the enhanced oxygen evolution reaction activity with the MHOF-based modulation of Ni redox and the optimized binding of oxygenated intermediates.

Density Functional Theory (DFT) is the most common tool for investigating materials under extreme conditions, yet its scaling behavior with respect to both system size and temperature prohibits large scale simulations in such regimes. Progress in this regard would enable accurate modeling of planetary interiors or radiation damage in fusion reactor walls.
One possible route to alleviate these scaling problems is through the use of surrogate models, i.e., machine-learning models. These are trained on DFT data and are able to reproduce DFT predictions of energies and forces at comparable accuracy, but negligible computational cost.
Yet, in order to avoid repeated costly training data generation, models need to be able to transfer across length scales. Here, we present such transferability results. They show how learning local information can allow models to extrapolate to length scales that are not attainable with standard DFT methods. The models are based upon the Materials Learning Algorithms (MALA) package [1] and the therein implemented LDOS based machine learning workflow [2].

[1]: https://github.com/mala-project
[2]: J. A. Ellis et al., Phys. Rev. B 104, 035120, 2021

While the high efficiency of Density Functional Theory (DFT) calculations have enabled many important materials science application over the past decades, modern scientific problems require accurate electronic structure data beyond the scales attainable with DFT. For instance, the modeling of materials at extreme conditions across multiple length and time scales, which is important for the understanding for physical phenomena such as radiation damages in fusion reactor walls, evades ab-initio treatment.
One possible method to obtain such models at near ab-initio accuracy are DFT surrogate models, that, based on machine learning (ML) algorithms, reproduce DFT results at a fraction of the cost. One drawback of the ML workflow is the need for hyperparameter optimization, i.e., the need to tune the employed ML algorithm in order to best perform on the given dataset. Manually performing this optimization becomes prohibitive if a wide range of materials and conditions is eventually to be treated. Here, we present results of an hyperparameter study in an effort to find optimal surrogate models for aluminium at ambient conditions [1], that investigates how modern hyperparameter optimization techniques can be used to automate large parts of the model selection process and eventually move towards automated surrogate model creation. The models are based upon the Materials Learning Algorithms (MALA) package [2] and the therein implemented LDOS based machine learning workflow [3].
[1]: https://www.doi.org/10.14278/rodare.1107
[2]: https://www.doi.org/10.5281/zenodo.5557254
[3]: https://www.doi.org/10.1103/PhysRevB.104.035120

We have successfully employed high-brightness liquid metal ion sources (LMIS) for the investigation of the
interaction of metal and metalloid ions with strong field laser beams. The gold and silicon ions, generated in the
LMIS by electrostatic field ionization, can be further ionized up to Au11+ and Si4+ with Thales laser (1 kHz)
at intensities of up to 4e16 W/cm2. Furthermore, we employed the fiber laser with 100 kHz to manipulate
the recoil momenta with subcycle resolution.

Due to the growing importance of Computational Fluid Dynamics (CFD) for reactor safety research, there have been activities aimed at qualifying the associated methods for many years. This entails the development and validation of models on the basis of detailed experimental data, generated in comprehensive projects. There was and is a need for development, among other things, for multiphase flows, in particular for accident scenarios in the reactor coolant system (RCS). In order to be able to use the model developments and validation data generated throughout the various projects funded by the German Federal Ministry for Economic Affairs and Energy in the long term, these are carried out using the reference code OpenFOAM, which is thereby qualified for application. The OpenFOAM_RCS project includes the OpenFOAM_RCS Addon for the C++ library OpenFOAM from the OpenFOAM Foundation, which gathers additional software that is relevant for the simulation of the reactor cooling system. This entails solvers, physical models, functionObjects, boundary conditions as well as pre- and post-processing utilities. The associated simulation setups are maintained along with the code.

Aggressive pheochromocytomas and paragangliomas (PPGLs) are difficult to treat, and molecular targeting is being increasingly considered, but with variable results. This study investigates established and novel molecular-targeted drugs and chemotherapeutic agents for the treatment of PPGLs in human primary cultures and murine cell line spheroids. In PPGLs from 33 patients, including 7 metastatic PPGLs, we identified germline or somatic driver-mutations in 82% of cases, allowing us to assess potential differences in drug responsivity between pseudohypoxia-associated cluster 1- (n=11) and kinase signaling-associated cluster 2-related (n=14) PPGL primary cultures. Single anti-cancer drugs were either more effective in cluster 1 (cabozantinib, selpercatinib, 5-FU) or similarly effective in both clusters (everolimus, sunitinib, alpelisib, trametinib, niraparib, gemcitabine, AR-A014418, high-dose zoledronic acid). Estrogen and low-dose zoledronic acid were the only single substances more effective in cluster 2. Neither cluster 1- nor cluster 2-related patient primary cultures responded to HIF-2α inhibitors, temozolomide, dabrafenib, or octreotide. We showed particular efficacy of targeted combination treatments (cabozantinib/everolimus, alpelisib/everolimus, alpelisib/trametinib) in both clusters, with higher efficacy in cluster 2 and overall synergistic effects (cabozantinib/everolimus, lpelisib/trametinib) or synergistic effects in cluster 2 (alpelisib/everolimus). Cabozantinib/everolimus combination therapy, gemcitabine, and high-dose zoledronic acid appear to be the very promising treatment options with particularly high efficacy in SDHB-mutant and metastatic tumors. In conclusion, only minor differences regarding drug responsivity were found between cluster 1 and cluster 2: Some single anti-cancer drugs were more effective in cluster 1 and targeted combination treatments were more effective in cluster 2.

2D transition metal carbides and/or nitrides, so-called MXenes, are noted as ideal fast-charging cation-intercalation electrode materials, which nev-ertheless suffer from limited specific capacities. Herein, it is reported that constructing redox-active phosphorus−oxygen terminals can be an attractive strategy for Nb4C3 MXenes to remarkably boost their specific capacities for ultrafast Na+ storage. As revealed, redox-active terminals with a stoichio-metric formula of PO2- display a metaphosphate-like configuration with each P atom sustaining three PO bonds and one PO dangling bond. Compared with conventional O-terminals, metaphosphate-like terminals empower Nb4C3 (denoted PO2-Nb4C3) with considerably enriched carrier density (four-fold), improved conductivity (12.3-fold at 300 K), additional redox-active sites, boosted Nb redox depth, nondeclined Na+-diffusion capability, and buffered internal stress during Na+ intercalation/de-intercalation. Consequently, com-pared with O-terminated Nb4C3, PO2-Nb4C3 exhibits a doubled Na+-storage capacity (221.0 mAh g-1), well-retained fast-charging capability (4.9 min at 80% capacity retention), significantly promoted cycle life (nondegraded capacity over 2000 cycles), and justified feasibility for assembling energy−power-balanced Na-ion capacitors. This study unveils that the molecular-level design of MXene terminals provides opportunities for developing simulta-neously high-capacity and fast-charging electrodes, alleviating the energy−power tradeoff typical for energy-storage devices.

The study of matter under extreme densities and temperatures as they occur e.g. in astrophysical
objects and nuclear fusion applications has emerged as one of the most active frontiers in physics,
material science, and related disciplines. In this context, a key quantity is given by the dynamic
structure factor S(q, ω), which is probed in scattering experiments—the most widely used method
of diagnostics at these extreme conditions. In addition to its crucial importance for the study of
warm dense matter, the modelling of such dynamic properties of correlated quantum many-body
systems constitutes one of the most fundamental theoretical challenges of our time. Here we report
a hitherto unexplained roton feature in S(q, ω) of the warm dense electron gas, and introduce a
microscopic explanation in terms of a new electronic pair alignment model. This new paradigm
will be highly important for the understanding of warm dense matter, and has a direct impact on
the interpretation of scattering experiments. Moreover, we expect our results to give unprecedented
insights into the dynamics of a number of correlated quantum many-body systems such as ultracold
helium, dipolar supersolids, and bilayer heterostructures.

MXenes are emerging layered materials that are promising for electrochemical energy storage and (opto-)electronic applications. A fundamental understanding of charge transport in MXenes is essential for such applications, but has remained under debate. While theoretical studies pointed to efficient band transport, device measurements have revealed thermally activated, hopping-type transport. Here we present a unifying picture of charge transport in two model MXenes by combining ultrafast terahertz and static electrical transport measurements to distinguish the short- and long-range transport characteristics. We find that band-like transport dominates short-range, intra-flake charge conduction in MXenes, whereas long-range, inter-flake transport occurs through thermally activated hopping, and limits charge percolation across the MXene flakes. Our analysis of the intra-flake charge carrier scattering rate shows that it is dominated by scattering from longitudinal optical phonons with a small coupling constant (α ≈ 1), for both semiconducting and metallic MXenes. This indicates the formation of large polarons in MXenes. Our work therefore provides insight into the polaronic nature of free charges in MXenes, and unveils intra- and inter-flake transport mechanisms in the MXene materials, which are relevant for both fundamental studies and applications.

We present extensive new direct path-integral Monte Carlo results for electrons in quantum dots in two and three dimensions. This allows us to investigate the nonclassical rotational inertia (NCRI) of the system, and we find an abnormal negative superfluid fraction [Phys. Rev. Lett. 112, 235301 (2014)] under some conditions. In addition, we study the structural properties by computing a sophisticated center-two particle correlation function. Remarkably, we find no connection between the spatial structure and the NCRI, since the former can be nearly identical for Fermi- and Bose-statistics for parameters where the superfluid fraction is diverging towards negative infinity.

We present extensive new ab initio path integral Monte Carlo (PIMC)
simulations of the uniform electron gas (UEG) in the high-temperature regime,
8 ≤ θ = kBT /EF ≤ 128. This allows us to study the convergence of different
properties towards the classical limit. In particular, we investigate the classical relation
between the static structure factor S(q) and the static local field correction G(q),
which is only fulfilled at low densities. Moreover, we compare our new results for
the interaction energy to the parametrization of the UEG by Groth et al. [PRL 119,
135001 (2017)], which interpolates between PIMC results for θ ≤ 8 and the Debye-
H ̈uckel limit, and to higher order analytical virial expansions. Finally, we consider the
momentum distribution function n(q) and find an interaction-induced increase in the
occupation of the zero-momentum state even for θ & 32. All PIMC data are freely
available online, and can be used as input for improved parametrizations and as a
rigorous benchmark for approximate methods.

The properties of hydrogen under extreme conditions are important for many applications, including inertial confinement fusion and astrophysical models. A key quantity is given by the electronic density response to an external perturbation, which is probed in X-ray Thomson scattering (XRTS) experiments -- the state of the art diagnostics from which system parameters like the free electron density , the electronic temperature , and the charge state can be inferred. In this work, we present highly accurate path integral Monte Carlo (PIMC) results for the electronic density response of hydrogen. We obtain the exchange-correlation (XC) kernel , which is of central relevance for many applications, such as time-dependent density functional theory (TD-DFT). This gives us a first unbiased look into the electronic density response of hydrogen in the warm-dense matter regime, thereby opening up a gamut of avenues for future research.

We combine ab initio path integral Monte Carlo (PIMC) simulations with fixed ionic configurations, obtained by DFT-MD simulations, in order to solve the electronic problem for hydrogen under warm dense matter conditions. To solve the divergence problem in the Ewald-sum for attractive potentials we employ the pair-approximation. This approach is compared against the much simpler Kelbg pair-potential. We find very favorable convergence behavior towards the latter. Since PIMC does not require any further assumptions regarding exchange and correlations of the many-body system, we then compare electronic densities obtained from our snapshot PIMC calculations with DFT calculations in the metallic regime. Furthermore, we investigate the manifestation of the resulting fermionic sign problem in our snapshot PIMC simulations. This gives us the unique capability to study the properties of warm dense hydrogen from ab initio simulations without any further assumptions, like the functional form of the exchange-correlation effects or fixed fermionic nodes. Thus, snapshot PIMC enables us to obtain the exact density response of warm dense hydrogen. This is extremely valuable to both experiments, like X-Ray Thomson scattering, as well as the development of new XC-functionals.

Long-term care facilities have been widely affected by the COVID-19 pandemic. Retirement homes are particularly vulnerable due to the higher mortality risk of infected elderly individuals. Once an outbreak is happening, suppressing the spread of the virus in retirement homes is challenging because the residents are in contact with each other and isolation measures cannot be widely enforced. Regular testing strategies, on the other hand, have been shown to effectively prevent outbreaks in retirement homes. However, high frequency testing may consume substantial staff working time, which results a trade-off between the time invested in testing, and the time spent providing essential care to residents.
Thus, developing an optimal testing strategy is crucial to proactively detect infections while guaranteeing efficient use of limited staff time in these facilities.
Although numerous efforts have been made to prevent the virus from spreading in long-term care facilities, this is the first study to develop testing strategies based on formal optimization methods.
This paper proposes two novel optimization models for testing schedules. The models aim to minimize the risk of infection in retirement homes, considering the trade-off between the probability of infection and staff workload. We employ a probabilistic approach in conjunction with the optimization models, to compute the risk of infection, including contact rates, incidence status, and the probability of infection of the residents.
To solve the models, we propose an enhanced local search algorithm by leveraging the \textit{symmetry property} of the optimal solution. We perform several experiments with realistically sized instances and show that the proposed approach can derive optimal testing strategies.

We provide post-processing data of daily dead and infected COVID-19 cases for a county (Landkreise) and a state (Bundesland) level. The data are extracted from the following link the data source, and subsequently transferred to the Casus-HZDR database server (see Fig above). The age-based and gender-based data are then aggregated and prepared in csv file.

The current data for county level is prepared on Germany_Counties_COVID19_Death_Infections.csv and its daily version is stored in Archive folder. Likewise, the actual data for state level is prepared on Germany_States_COVID19_Death_Infections.csv and its daily version is stored in Archive folder. The file consists of six columns such as region, name, date, dead, infected and population. The region denotes the ID of a county/state followed by its name in the next column. The inserted date of data is prepared in the third column followed by the number of dead and infected cases. Last but not least, the population of the county is provided in the last column.

Average-atom (AA) models are an important tool in the modelling of warm dense matter, being both a computationally cheap and conceptually straightforward alternative to full DFT MD simulations. AA models are typically based on a common premise - namely, an atom immersed in a plasma environment - but use a range of different assumptions and approximations, which can cause inconsistent predictions for various properties. In this talk, I will compare results across several models, differing for example in their choice of boundary conditions and exchange-correlation functional. I will focus on the mean ionization state (MIS), an important property in WDM. I will compare different methods for computing the MIS, including methods which are historically popular and still widely-used in AA codes, and also consider more novel approaches using the electron localization function and Kubo-Greenwood formalism. If time permits, these results with also be compared with results from full DFT-MD simulations.

Density-functional average-atom (AA) models are an important tool in simulations of the warm dense matter (WDM) regime, because they account for quantum interactions at favourable computational cost. AA models are typically based on a common premise - namely, an atom immersed in a plasma environment - but use a range of different assumptions and approximations, leading to inconsistent predictions for various properties. We compare results across several models, differing for example in their choice of boundary conditions and exchange-correlation functional, focussing on the mean ionization state (MIS), an important property in WDM. Furthermore, we compare different methods for evaluating the MIS: a simple energy threshold, and approaches based on the inverse participation function and electron localization function. We evaluate the relative merits of these approaches and, time-permitting, compare our AA results with full Kohn-Sham density-functional theory calculations.

With the merits of quantum dots (QDs) (e.g., high molar extinction coefficient, strong visible light absorption, large specific surface area, and abundant functional surface active sites) and aerogels (e.g., self-supported architectures, porous network), semiconductor QD aerogels show great prospect in photocatalytic applications. However, typical gelation methods rely on oxidative treatments of QDs. Moreover, the remaining organic ligands (e.g., mercaptoacids) are still present on the surface of gels. Both these factors inhibit the activity of such photocatalysts, hampering their widespread use.
Herein, we present a facile 3D assembly of II−VI semiconductor QDs capped with inorganic (NH₄)₂S ligands into aerogels using H₂O as a dispersion solvent. Without any sacrificial agents, the resulting CdSe QD aerogels achieve a high CO generation rate of 15 μmol g^-1 h^-1, which is 12-fold higher than that of pristine-aggregated QD powders. Our work not only provides a facile strategy to fabricate QD aerogels but also offers a platform for designing advanced aerogel-based photocatalysts.

Transglutaminase 2 (TGase 2) represents a multifunctional protein, which is involved in various physiological and pathophysiological processes. The latter also include its participation in the development and progression of malignant neoplasms, which is often accompanied by an in-creased protein synthesis. Besides the elucidation of the molecular functions of TGase 2 in tumor cells, knowledge of its concentration that is available for targeting by theranostic agents repre-sents a valuable information. Herein, we describe the application of a recently developed fluo-rescence anisotropy (FA)-based assay for the quantitative expression profiling of TGase 2 by means of transamidase-active enzyme in cell lysates. The assay is based on the incorporation of rhodamine B‑isonipecotyl‑cadaverine (R-I-Cad) into N,N-dimethylated casein (DMC), which results in an increase of FA signal over time. It was shown that this reaction is not only catalyzed by TGase 2 but also by TGases 1, 3, and 6 and factor XIIIa using recombinant proteins. Therefore, control measurements in the presence of a selective irreversible TGase 2 inhibitor were manda-tory to ascertain the specific contribution of TGase 2 to the overall FA rate. To validate the assay regarding the quality of quantification, spike/recovery and linearity of dilution experiments were performed. A total of 25 cancer and 5 non-cancer cell lines were characterized with this as-say method in terms of their activatable TGase 2 concentration (fmol/µg protein lysate) and the results were compared to protein synthesis data obtained by western blotting. Moreover, com-plementary protein quantification methods using a biotinylated irreversible TGase 2 inhibitor as activity-based probe and a commercially available ELISA were applied for selected cell lines to further validate the results obtained by the FA-based assay. Overall, the present study demonstrates that the FA-based assay using the substrate pair R-I-Cad and DMC represents a facile, homogenous and continuous method for quantifying TGase 2 activity in cell lysates.

Modern particle accelerators are a key component of today’s research landscape and indispensable in industry and medicine. In special application areas, the portfolio of these facilities will be expanded by laser-driven compact plasma accelerators that generate short, high-intensity pulses of ions with unique beam properties. Though intensely explored by the community, scaling the maximum beam energies of laser-driven ion accelerators to the required level is one of the most significant challenges of this field. This endeavor is inherently linked to a fundamental understanding of the underlying acceleration processes. The prospect to effciently increase the beam energy relies on the ability to control the accelerating field structures beyond the well-established acceleration from the stationary target rear side. However, manipulating the interaction in such micrometer-sized accelerators proves to be challenging due to the transient nature of the plasma fields and requires precise tuning of the temporal laser pulse shape and the volumetric density distribution of the plasma target to a level that could so far not be achieved.
This thesis investigates laser-proton acceleration using a cryogenic hydrogen target that combines the capabilities of predictive three-dimensional simulation and the in-situ realtime monitoring of the density distribution in the experiment to explore the fundamental physical principles of plasma based acceleration mechanisms. The corresponding experiments were performed at the DRACO laser facility at the Helmholtz-Zentrum Dresden-Rossendorf. The key to the success of these studies was the advancement of the cryogenic target system that generates a self-replenishing pure hydrogen jet. Using a mechanical chopping device, which protects the target system from the disruptive influence originating from the high-intensity interaction, allowed, for the first time, systematic experiments with a large number of laser shots in the harsh environment of the ultra-short pulse DRACO petawatt laser. The performance of a cylindrical hydrogen jet can be substantially optimized by a flexible all-optical tailoring of the target profile. Guided by real-time multi-color probing, the target density, the decisive parameter of the interaction, was scanned over two orders of magnitude allowing the exploration of different advanced acceleration regimes in a controlled manner. This approach led to the experimental realization of proton beams with energies up to 80 MeV and application relevant high particle yield from advanced acceleration mechanisms occurring in near-critical density plasmas, a regime so far mostly investigated in numerical studies. Besides cylindrical jets, the formation of thin hydrogen sheets was studied to gain insight into the fluid and crystallization dynamics that can be used to tailor the target shape for laser-proton acceleration. Using these jets, the onset of target transparency was explored, a regime that promises increased proton energies when optimized. Furthermore, after irradiation of the hydrogen jet with a high-intensity laser pulse, an unexpected axial modulation in the plasma density distribution was observed that can play a role in structuring the proton beam profile. This modulation is caused by instabilities that originate from the laser-plasma interaction, for example due to laser-driven return currents or the plasma expansion dynamics.

Background: Gold mining activities in South Africa resulted in contamination of residential environment with uranium-rich wastes from mine tailings. Health of the people living around the mine tailings could be affected by uranium exposure due to its hazardous chemotoxic and radiological properties.
Methods: We conducted a cross-sectional study to assess i) uranium (U) concentrations in individual hair samples of children and adults living in close proximity to mine tailings in Northeast-Soweto in Johannesburg, South Africa, and ii) the association between U concentrations in hair and various factors, including zone of residence, socio-demographic and housing characteristics. Sampling sites were divided into three zones based on the distance between a dwelling and a cluster of mine tailings (zone 1: <= 500 m, zone 2: 2-3 km away, zone 3: 4-5 km away). U concentrations in hair samples were measured using inductively coupled plasma mass spectrometry. To test the association between U concentrations and selected factors we used robust regression models with log-transformed U concentrations.

Heterogeneous hardware landscapes will define the Exascale era. At the same time, keeping scientific libraries and applications portable across different hardware setups while maintaining high performance is no trivial matter. Vendor-provided programming platforms often cannot target accelerators from other vendors, and different hardware types like CPUs, GPUs and FPGAs require differently tuned algorithms for optimal performance.

A solution to these issues can be found in abstraction layers that provide the user with a single programming interface while still maintaining portability and performance. In this talk, we introduce the Caravan HPC ecosystem. With the alpaka abstraction library for accelerator programming at its core and many sibling libraries for related use cases --- such as the memory access abstraction layer LLAMA or the C++ primitives library vikunja --- the Caravan ecosystem is an ideal choice for scientists and programmers setting out to tackle the challenges of the Exascale era.

It is common in the HPC community that the achieved performance with just CPUs is limited for many computational cases. The EuroHPC pre-exascale and the coming exascale systems are mainly focused on accelerators, and some of the largest upcoming supercomputers such as LUMI and Frontier will be powered by AMD Instinct™ accelerators. However, these new systems create many challenges for developers who are not familiar with the new ecosystem or with the required programming models that can be used to program for heterogeneous architectures. In this paper, we present some of the more well-known programming models to program for current and future GPU systems. We then measure the performance of each approach using a benchmark and a mini-app, test with various compilers, and tune the codes where necessary. Finally, we compare the performance, where possible, between the NVIDIA Volta (V100), Ampere (A100) GPUs, and the AMD MI100 GPU.

The management of mine tailings presents a global challenge. Re-mining of tailings to recover remaining metals and other valuable constituents could play a crucial role in reducing the volume of stored tailings. To assess the resource potential of tailings storage facilities, 3D resource models must be constructed. This is not straightforward owing to the heterogeneous nature of tailings. In this case study, modelling of the Davidschacht tailings deposit was performed using universal sequential Gaussian simulation, to account for the strong trends and heterogeneity. The tonnages of the valuable elements were estimated with reasonable certainty, confirming that relatively few drill holes are required for robust resource estimates of tailings storage facilities. Zinc is the most abundant valuable metal (6,270 t ±10 %), followed by Pb (2,480 t ±10 %), Cu (654 t ±11 %), and In (12.6 t ±9 %), with errors given for 95 % confidence levels. Although the In tonnage is low compared to the other elements, its in situ value is around half that of Cu and Pb, demonstrating the importance of high value by-products for re-mining potential. Although tailings deposits typically have lower grades and tonnages than primary ore deposits, and the quantities of recoverable valuable elements may be even lower due to current technological limitations, re-mining of TSFs should also be considered for rehabilitation purposes and may help to diversify raw materials supply chains. Geostatistical modelling, particularly universal kriging-based simulation, has been proven to produce robust tonnage estimates of tailings storage facilities and should be adopted in industry to reduce the technical and financial uncertainties associated with re-mining.

We report the development of a multipurpose differential X-ray calorimeter with a broad energy bandwidth. The absorber architecture is combined with a Bayesian unfolding algorithm to unfold high-energy X-ray spectra generated in high-intensity laser-matter interactions. Particularly, we show how to extract absolute energy spectra and how our unfolding algorithm can reconstruct features not included in the initial guess. The performance of the calorimeter is evaluated via Monte Carlo generated data. The method accuracy to reconstruct electron temperatures from bremsstrahlung is shown to be 5 % for electron temperatures from 1 MeV to 50 MeV. We study bremsstrahlung generated in solid target interaction showing an electron temperature of 0.56±0.04MeV for a 700 µm Ti titanium target and 0.53±0.03MeV for a 50 µm target. We investigate bremsstrahlung from a target irradiated by laser wakefield accelerated electrons showing an endpoint energy of 551 ± 5 MeV, inverse Compton generated X-rays with a peak energy of 1.1 MeV and calibrated radioactive sources. The total energy range covered by all these sources ranges from 10 keV to 551 MeV.

The openPMD API is a DSL used in plasma physical simulations for the description of particle-mesh data according to the openPMD standard. By defining only the logical structure, but not the physical implementation of such data, this standard allows the openPMD API to offer a number of flexibly interchangeable efficient implementations in terms of IO backends. Performance trends in the HPC domain show the increasing necessity for such IO flexibility in data analysis pipelines. This seminar talk will give an introduction on openPMD as well as the openPMD API. It will further discuss current IO trends and the role of the openPMD API therein. A short hands-on demonstration will show the current state of affairs.

BACKGROUND
Amide proton transfer (APT) imaging is a chemical exchange saturation transfer (CEST) technique offering potential clinical applications in patients with brain tumors.

PURPOSE
To investigate whether cerebral APT-CEST is sufficiently reproducible in healthy tissue and glioma for clinical use at 3T.

STUDY TYPE
Prospective, longitudinal

SUBJECTS
Twenty-one healthy volunteers (M:F = 10:11; age 39±11 years) and six glioma patients (M:F = 3:3; age 50±17 years: four glioblastomas, one oligodendroglioma, one suspected low-grade glioma).

FIELD STRENGTH/SEQUENCE
3T, SPACE-CEST

ASSESSMENT
APT-CEST measurement reproducibility was assessed within-session (glioma patients, healthy volunteers), and between-sessions and between-days (healthy volunteers). The standard deviation of the within-subject difference (SDdiff) was calculated in tumor regions of interest (ROI), and eight ROIs at relevant locations including a whole-brain ROI.

STATISTICAL TESTS
Brown-Forsythe tests and variance component analyses (VCA) were used to assess the reproducibility of ROIs for the three reproducibility time intervals. Intraclass correlation coefficient (ICC) was used to assess agreement between the ROIs for the three reproducibility time intervals.

RESULTS
APT-CEST magnetization transfer ratio asymmetry (MTRasym) was 0.89±0.96% on average in healthy brain tissue and 1.59±0.67% in tumor tissue. Intratumoral mean MTRasym was significantly higher than MTRasym in healthy-appearing tissue in patients (0.5±0.46%; P< 0.001). The APTCEST difference between GBMs and contralateral tissue was 1.11%. The average within-session, between-sessions, and between-days SDdiff of healthy control brains was 0.2%. The within-session SDdiff of whole-brain was 0.2% in both healthy volunteers and patients, and 0.21% in the segmented tumor. The orbitofrontal gyri were the ROI with the highest within-session SDdiff (0.61%). Within-session reproducibility of ROIs did not differ significantly from between-sessions or between-day reproducibility (0.76>P>0.22) and VCA showed that within-session variance was the most important factor (60%), but differed from between-days reproducibility in putamen and the central brain (P<0.05). ICC within-session agreement was excellent for glioma (ICC=0.97) and healthy brain in volunteers (ICC=0.81). The effect size of the APTCEST between healthy brain and GBM was 5.

CONCLUSION
Cerebral APT-CEST imaging has good scan-rescan reproducibility in healthy tissue and tumors with clinically feasible scan times at 3T. Short-term measurement effects are dominant components in reproducibility.

Plasmonic sensing in the infrared region employs the direct interaction of the vibrational fingerprints of molecules with the plasmonic resonances, creating surface-enhanced sensing platforms that are superior to traditional spectroscopy. However, the standard noble metals used for plasmonic resonances suffer from high radiative losses as well as fabrication challenges, such as tuning the spectral resonance positions into mid- to far-infrared regions, and the compatibility issue with the existing complementary metal–oxide-semiconductor (CMOS) manufacturing platform. Here, we demonstrate the occurrence of mid-infrared localized surface plasmon resonances (LSPR) in thin Si films hyperdoped with the known deep-level impurity tellurium. We show that the mid-infrared LSPR can be further enhanced and spectrally extended to the far-infrared range by fabricating two-dimensional arrays of micrometer-sized antennas in a Te-hyperdoped Si chip. Since Te-hyperdoped Si can also work as an infrared photodetector, we believe that our results will unlock the route toward the direct integration of plasmonic sensors with the on-chip CMOS platform, greatly advancing the possibility of mass manufacturing of high-performance plasmonic sensing systems.

In case radionuclides (RN) enter the food chain and are incorporated by humans, they pose a possible health risk due to their radio- and chemotoxicity. To precisely assess the health risk after oral incorporation of RN with food and beverages and to apply effective decontamination methods, it is mandatory to understand the processes of RN biokinetics on both cellular and molecular scale. Within the joint research project RADEKOR: “Speciation and transfer of radionuclides in the human organism especially taking into account decorporation agents”, quantitative excretion analysis and biokinetic modeling of orally incorporated RN are performed. Additionally, these macroscopic investigations are combined with molecular speciation studies of RN in artificial fluids of the alimentary tract of humans and cytotoxicity studies with respective human and rat cell lines both in the absence and presence of decorporation agents. Aim of the project is to expand the knowledge of processes underlying RN interactions within the human alimentary tract on a cellular and molecular scale to establish a precise biokinetic model as well as to contribute to the development and improvement of nuclide specific decontamination methods.
This joint project is funded by the German Federal Ministry of Education and Research (grant number 02NUK057). The funding period is from July 2020 to December 2023 and cooperation partners are: Helmholtz-Zentrum Dresden-Rossendorf (HZDR), Technische Universität Dresden (TUD), Leibniz-Universität Hannover (LUH), Karlsruhe Institute of Technology (KIT), and VKTA - Radiation Protection, Analytics & Disposal (VKTA).

Due to the “German Energiewende”, all nuclear power plants (NPPs) in Germany will have been shut down by the end of 2022. Consequently, a safe, economical, and efficient dismantling of the NPPs will be an important challenge for the next decades. This is not only valid for the very particular German case but will certainly foster progress with methods for optimal planning and implementation of decommissioning.
The decommissioning strategy for an NPP requires knowledge of the neutron activation and contamination levels, which have emerged during its operation. Such knowledge can significantly minimize the radioactive waste and contribute to the safety of the operating personnel and the public.
This study considered two strategies. In the first one, the radionuclide inventory in the material of an NPP already under dismantling was investigated. Among others, Co-60 and C-14 in steel samples from the reactor pressure vessel (RPV) and Eu-152, Ba-133 and C-14 in concrete drill cores from biological shielding were quantitatively determined. C-14 was measured by liquid scintillation counting (LSC) after oxidative combustion and the other RN by gamma spectrometry. In the second strategy, the neutron flux in NPPs still under operation was determined with activation monitors. Small metal foils, covering a broad neutron energy range (i.e. thermal, epithermal, and fast energy range), e.g., Ti, Fe, Ni, Cu, In, Sn, Zn, Ta, were placed near the RPV and at the interior and exterior biological shield during the regular annual revision and irradiated for one fuel cycle (approximately one year). After the activation monitors were removed and recovered, the activation of the metal foils was quantitatively determined by gamma spectrometry. The experimental data from both strategies were compared with results from Monte-Carlo simulations.
This work is funded by the German Federal Ministry of Education and Research (BMBF) under grant numbers 15S9412 (WERREBA) and 15S9409A (EMPRADO) and is carried out in cooperation with PreussenElektra GmbH and EWN Greifswald GmbH.

Racemic [18F]FBFP ([18F]1) proved to be a potent σ1 receptor radiotracer with superior imaging properties. The pure enantiomers of unlabeled compounds (S)- and (R)-1 and the corresponding iodonium ylide precursors were synthesized and characterized. The two enantiomers (S)-1 and (R)-1 exhibited comparable high affinity for σ1 receptors and selectivity over σ2 receptors. The Ca2+ fluorescence assay indicated that (R)-1 behaved as an antagonist and (S)-1 as an agonist for σ1 receptors. The 18F-labeled enantiomers (S)- and (R)-[18F]1 were obtained in > 99% enantiomeric purity from the corresponding enantiopure iodonium ylide precursors with radiochemical yield of 24.4% ± 2.6% and molar activity of 86 – 214 GBq/μmol. In ICR mice both (S)- and (R)-[18F]1 displayed comparable high brain uptake, brain-to-blood ratio, in vivo stability and binding specificity in the brain and peripheral organs. In micro-positron emission tomography (PET) imaging studies in rats, (S)-[18F]1 exhibited faster clearance from the brain than (R)-[18F]1, indicating different brain kinetics of the two enantiomers. Both (S)- and (R)-[18F]1 warrant further evaluation in primates to translate a single enantiomer with more suitable kinetics for imaging the σ1 receptors in humans.

Printed magnetic field sensorics enable a new generation of human-machine interfaces and contactless switches for resource efficient printed interactive electronics. As printed magnetoresistors rely on scarce or hard to manufacture magnetosensitive powders, their scalability and demonstration of printing with industry-grade technologies are the key material science challenges. Here, we report dispenser printing of a commodity scale nonmagnetic bismuth-based paste processed by large area laser sintering to obtain printed magnetoresistive sensors. The sensors are printed on different substrates including ceramics, paper and polymer foils. We validate experimentally that the peculiar quantum large orbital magnetoresistive effect remains effective in printed bismuth sensors, allowing their operation in high magnetic fields. The sensors reveal up to 146% resistance change at 5 T at room temperature with a maximum resolution of 2.8 µT. If printed on flexible foils, our sensors show resilience to bending deformation for more than 2000 bending cycles and withstand even thermal forming, as relevant for smart wearables and in-mold electronics. The freedom in the substrate choice and sensor design enabled by dispenser printing allowed us to implement the proposed sensor technology for different applications focused on touchless interactive platforms, such as advertisement materials, interactive wallpapers and printed security panels.

In this introduction, we provide an overview of the papers that were accepted for publication in the feature issue on ultrafast phenomena and terahertz (THz) waves. This feature issue presents cutting-edge research on ultrafast phenomena and highlights recent developments inTHz technology.

The understanding of the formation of the elements has been an intriguing topic within the last decades. It is now approved that the heaviest naturally occurring elements on earth, the actinides, are produced in the astrophysical r-process. However, the exact site of this process is still disputed. Recently, the amount of interstellar Pu-244 (T1/2 = 80.6 Ma) in various geological archives like deep-sea ferromanganese crusts and sediments has been investigated by applying highly sensitive accelerator mass spectrometry measurements (AMS). Correlation of the influx of supernova-produced Fe-60 (T1/2 = 2.6 Ma) and Pu-244 could point to a possible origin of the r-process in the universe. To further prove this hypothesis, recent investigations focus on the determination of another long-lived radionuclide which is also produced in the r process, Cm-247 (T1/2 = 15.6 Ma), by AMS. However, the separation of the expected ultra-trace amounts of actinides (a few 100 atoms per gram) from huge amounts of matrix and interfering elements represents a major analytical challenge. Thus, this contribution aims to compare existing chemical separation strategies for trivalent actinides (Am, Cm) from deep-sea reservoirs, like ferromanganese crusts or nodules based on extraction chromatography. Our investigations show that procedures based on trivalent actinide separation by TRU™ resin fail to extract trivalent actinides from matrices with high concentrations of rare-earth elements. Thus, an alternative separation method based on anion exchange (DOWEX 1x8 for Pu separation) and solvent extraction (DGA™ resin for An/Ln separation and TEVA™ resin for the separation of Am/Cm from rare-earths) has been adapted in our studies. Am-241 and Cm-244 in kBq quantities were used as tracers to determine the yield of the full separation procedure by γ-counting and α spectrometry. The effective separation of trivalent actinides from major matrix elements, like iron and manganese, as well as various rare-earth elements allow for processing multi-gram amounts of deep-sea ferromanganese crusts. This could finally lead to the detection of live Cm-247 in geological archives. Furthermore, this adapted method can be used for the analysis of environmental samples regarding their content and isotopic ratio of anthropogenically produced Pu, Am and Cm which holds potential for nuclear safeguards and nuclear forensics studies.

Due to their applications in catalysis, energy storage or biomedicine, many studies report synthesis and characterizations of CeO2 NPs and intensively use X-ray sources for characterization. In this study, we report a comprehensive interpretation of X-ray measurements on CeO2 models with atomically resolved structure, namely oxo-hydroxo polynuclear Ce complexes. A set of Ce clusters with growing size (0.6 nm to 1.2 nm) and nuclearity (from 6 to 38 Ce atoms) were synthetized and characterized by single crystal XRD. The samples were then analyzed using HEXS and HERFD technics and compared to larger CeO2 NPs and bulk CeO2. Both spectroscopic methods reveal consistent trends as the particle grows or shrink from the set of molecular Ce-{n} clusters up to bulk CeO2. HEXS reveals a broadening in distribution for the short Ce-oxygen bonds for the small clusters. Concomitantly, the HERFD performed at the Ce LIII edge indicates a gradual splitting of the cerium 5d states as the particles become more CeO2 like. From the crystallographic determination of the clusters structure, atomically resolved Ce LIII edge simulation were undertaken. These simulations allow to isolate structural and electronic properties for individual Ce sites within clusters and evidence the great difference between surface and core Ce atoms. It also shows how a combination of simulations from different sites results in the accurate reproduction of the corresponding experimental data. This approach based on clusters atomic sites was then successfully extended to model larger CeO2 NPs Ce LIII edge HERFD spectra. By linking atomically resolved structures to nanoparticles and bulk material using crystallography, X-ray technics and simulation, this work extends the knowledge on cerium oxide nanomaterial and supports a better understanding and predictability of their crystalline and electronic structure

Global road networks continue to expand, and the wildlife responses to these landscape-level changes need to be understood to advise long-term management decisions. Roads have high mortality risk to snakes because snakes typically move slowly and can be intentionally targeted by drivers.
We investigated how radio-tracked King Cobras (Ophiophagus hannah) traverse a major highway in northeast Thailand, and if reproductive cycles were associated with road hazards.
We surveyed a 15.3 km stretch of Highway 304 to determine if there were any locations where snakes could safely move across the road (e.g., culverts and bridges). We used recurse analyses to detect possible road-crossing events, and used dynamic Brownian Bridge Movement Models (dBBMMs) to show movement pathways association with possible unintentional crossing structures. We further used Integrated Step Selection Functions (ISSF) to assess seasonal differences in avoidance of major roads for adult King Cobras in relation to reproductive state.
We discovered 32 unintentional wildlife crossing locations capable of facilitating King Cobra movement across the highway. While our dBBMMs broadly revealed underpasses as possible crossing points, they failed to identify specific underpasses used by telemetered individuals; however, the tracking locations pre- and post-crossing and photographs provided strong evidence of underpass use. Our ISSF suggested a lower avoidance of roads during the breeding season, although the results were inconclusive. With the high volume of traffic, large size of King Cobras, and a 98.8% success rate of crossing the road in our study (nine individuals: 84 crossing attempts with one fatality), we strongly suspect that individuals are using the unintentional crossing structures to safely traverse the road.
Further research is needed to determine the extent of wildlife underpass use at our study site. We propose that more consistent integration of drainage culverts and bridges could help mitigate the impacts of roads on some terrestrial wildlife.

Applications such as actuation by (magnetic) shape memory effects, magnetocaloric cooling and thermomagnetic energy harvesting benefit from a fast martensitic transformation, because using devices at high frequencies increases their power density. Still, data on the speed limit of theses transformations is scarce, as it is difficult to induce the phase transition in short time spans and measure it non-invasively. Up to now, shape memory wires have been heated with currents by Joule heating, which induces a transformation in as short as 20 µs. With magnetic pulses, magnetic shape memory alloys can be transformed within 13 ms. In both cases, however, transformation dynamics are limited by the duration of the current or magnetic pulse.
To increase knowledge about the speed limit of martensitic transformations, here, we heat a 500 nm thick epitaxial Ni-Mn-Ga film with a 7 ns long laser pulse and probe the martensite to austenite transformation with in situ synchrotron diffraction. With this experimental set-up, we can vary the heating rate by changing the laser fluence and additionally adjust the initial sample temperature with a furnace. We observe a linear dependence of the heating rate on the transformation speed. Thus, the transformation can be completed in as little as 10 ns; however, this requires an overheating of several hundreds of Kelvin. For most applications, only a much smaller overheating is feasible, which gives a switching time in the sub-microsecond range. The austenite to martensite transformation can be completed at least within hundreds of ns. This leaves plenty of room to speed up the performance of all applications based on martensitic transformations.

Recycling is part of the circular economy contributing to the sustainable and secure supply of raw materials. Most consumer products, from cars to domestic appliances, consist of multi-material structures which form complex wastes after their use phase. Therefore and with the focus on sustainability, the design decisions of product manufacturers have a significant influence on recyclability. So far, methods exist to evaluate the performance of metallurgical recycling systems through process simulation. However, there is a lack of methods to estimate the impact of design decisions on the liberation behaviour during crushing.
In a case study, a large-scale recycling campaign examined 100 refrigerators from the household sector in a commercial primary waste treatment facility. Initially, the fridges were analysed regarding e.g. initial mass, size, outer appearance, and manufacturer in order to be categorized into three fractions. Then the conventional pre-treatment steps were documented such as depollution, removal of glass shelfs, printed circuit boards and compressors. Finally, the mechanical processing started beginning with a two-stage crushing and subsequent separation in an air classifier (density sorting), magnetic and eddy current separator.
The main products of the mechanical processing are a PU rich, a ferrous, a non-ferrous and a plastics fraction. The last three of those were analysed in more detail in order to quantify the degree of liberation as well as the separation efficiency. Liberation was evaluated at particle level in terms of unliberated connections between different materials (material mixed particles) as well as connections of different components consisting of the same material (component mixed particles). This data allows deducing the liberation efficiency, which affects sorting and final product qualities.
Furthermore, the liberation efficiency of different connection types (e.g. screwing, gluing, coating, snap-fitting) was identified. Coupling these insights with a material compatibility assessment for subsequent recovery processes, design recommendations have been derived for liberation-oriented choice of connection types and specific material combinations. For example, steel in the PU rich fraction causes problems during conveying and pelletizing and is therefore regarded as hazardous pollutant for subsequent processing. In contrast to that, aluminium in the ferrous fraction deceases slightly the product quality but can be removed easily during subsequent metallurgical refinement.
As an ongoing research topic, finite element method (FEM) simulations supplement these experimental investigations to enable the analysis of various multi-material designs. In these simulations, composites of metal and fibre-reinforced plastics are modelled in a crushing process and compared to laboratory scale experiments (figure 2) regarding their liberation potential during crushing and their overall recyclability. In the future, this methodical approach will allow assessing the effects of the product design on recyclability already in the design stage assisting the development of recycling-friendly products.

Martensitic transformations are important for many materials exhibiting magneto-, elasto- and barcaloric effects and
often the functional properties benefit from additional magnetic transformations. For caloric applications, thin films
are of particular interest due to their fast heat exchange, which promises a high cooling power. In particular epitaxial
films are a model system to understand the formation of the martensitic microstructure.[1] However, commonly
transformations from austenite to martensite only occur during cooling. The recent observation of a so-called reentrant
transformation obtained much interest, as an additional transformation from martensite to austenite was observed
during further cooling.[2,3] A reentrant transition increases both, the number of new physical effects and the possible
applications. However, reports are currently very few and only on bulk materials. Will this phenomenon occur also in
thin films? Will the martensitic transformation and microstructure differ when induced by heating or cooling? Also
for caloric applications, reentrant martensite is interesting as it may enable bidirectional caloric effects driven by
deformation and recovery of the ferromagnetic shape memory alloys (FSMA) through both, heating and cooling.
As a model system, epitaxial Co-Cr-Ga-Si ferromagnetic shape memory thin films were grown by DC magnetron
sputtering. To obtain epitaxial growth, films were deposited on different substrates as well as orientations. We identify
MgO(100) as the optimum substrate. Films were grown at different deposition temperatures and the influence of an
additional postannealing process was examined to understand the influence on elemental composition, structure,
microstructure and the transformation behavior. As a kind of summary, Fig.1-a depicts a phase diagram of all samples
prepared. Under optimum conditions, we obtain epitaxial growth, as evident from pole figure measurements of an
austenitic film (Fig. 1-b). When films are subjected to an additional heat treatment at 800°C, films are martensitic at
room temperature, which is evident the peak splitting in pole figure measurements (Fig. 2-a) and agree well with pole
figures calculated by the phenomenological theory of martensite with a c/a ratio of 1.37 (Fig. 2-b). Furthermore, the
microstructure becomes granular and twin boundaries become visible. Though annealing improves the martensitic
transformation, we observe a degradation of the ferromagnetic transition. To sum up, we could demonstrate epitaxial
growth of Co-Cr-Ga-Si films, which are martensitic and ferromagnetic at room temperature. This is a key step to
utilize the additional possibilities of reentrant martensite also for thin films.

Zyklotrone bilden als Ressource medizinischer Radionuklide eine zentrale Infrastruktur für die Entwicklung neuer und die Produktion klinisch etablierter Radiotracer zur molekularen Hybridbildgebung. Da die letzte umfassende Veröffentlichung zu Zyklotronen ca. 15 Jahre alt ist, wurde eine Statuserhebung zu den für die Nuklearmedizin und Radiopharmazie in Deutschland, Österreich und der Schweiz (D-A-CH-Länder) betriebenen Zyklotronen angestrebt.

The performance gap between CPU and memory widens continuously. Choosing the best memory layout for each hardware architecture is increasingly important as more and more programs become memory bound. For portable codes that run across heterogeneous hardware architectures, the choice of the memory layout for data structures is ideally decoupled from the rest of a program. This can be accomplished via a zero-runtime-overhead abstraction layer, underneath which memory layouts can be freely exchanged.
We present the Low-Level Abstraction of Memory Access (LLAMA), a C++ library that provides such a data structure abstraction layer with example implementations for multidimensional arrays of nested, structured data. LLAMA provides fully C++ compliant methods for defining and switching custom memory layouts for user-defined data types. The library is extensible with third-party allocators.
Providing two close-to-life examples, we show that the LLAMA-generated AoS (Array of Structs) and SoA (Struct of Arrays) layouts produce identical code with the same performance characteristics as manually written data structures. Integrations into the SPEC CPU® lbm benchmark and the particle-in-cell simulation PIConGPU demonstrate LLAMA's abilities in real-world applications. LLAMA's layout-aware copy routines can significantly speed up transfer and reshuffling of data between layouts compared with naive element-wise copying.
LLAMA provides a novel tool for the development of high-performance C++ applications in a heterogeneous environment.

Classical Random Neural Networks (RNNs) have demonstrated effective applications in decision making, signal processing, and image recognition tasks. However, their implementation has been limited to deterministic digital systems that output probability distributions in lieu of stochastic behaviors of random spiking signals. We introduce the novel class of supervised Random Quantum Neural Networks (RQNNs) with a robust training strategy to better exploit the random nature of the spiking RNN. The proposed RQNN employs hybrid classical-quantum algorithms with superposition state and amplitude encoding features, inspired by quantum information theory and the brain’s spatial-temporal stochastic spiking property of neuron information encoding. We have extensively validated our proposed RQNN model, relying on hybrid classical-quantum algorithms via the PennyLane Quantum simulator with a limited number of qubits. Experiments on the MNIST, FashionMNIST, and KMNIST datasets demonstrate that the proposed RQNN model achieves an average classification accuracy of 94.9%. Additionally, the experimental findings illustrate the proposed RQNN’s effectiveness and resilience in noisy settings, with enhanced image classification accuracy when compared to the classical counterparts (RNNs), classical Spiking Neural Networks (SNNs), and the classical convolutional neural network (AlexNet). Furthermore, the RQNN can deal with noise, which is useful for various applications, including computer vision in NISQ devices. The PyTorch code is made available on GitHub to reproduce the results reported in this manuscript.

Understanding the electronic transport properties of iron under high temperatures and pressures is essential for constraining geophysical processes. The difficulty of reliably measuring these properties under Earth-core conditions calls for sophisticated theoretical methods that can support diagnostics. We present results of the electrical conductivity within the pressure and temperature ranges found in Earth's core from simulating microscopic Ohm's law using time-dependent density functional theory. Our predictions provide a new perspective on resolving discrepancies in recent experiments.

Mefenamic acid represents a widely used nonsteroidal anti-inflammatory drug (NSAID) to treat pain of postoperative sur-gery and heavy menstrual bleeding. Like other NSAIDs, mefenamic acid inhibits the synthesis of prostaglandins by non-selectively blocking cyclooxygenase (COX) isoforms COX-1 and COX-2. For improved selectivity of the drug and thereby reduced related side effects, the carborane analogues of mefenamic acid were evaluated. The ortho-, meta- and para-carborane derivatives were synthesized in three steps: halogenation of the respective cluster, followed by a Pd-catalyzed B–N coupling and hydrolysis of the nitrile derivatives under acidic conditions. COX inhibitory activity and cytotoxicity for different cancer cell lines revealed that the carborane analogues have stronger anti-tumor potential compared to their parent organic compound.

The long-term and safe storage of high-level radioactive waste (HLW) in general, remains a challenge world-wide. The deep geological repository (DGR) is a concept of applying multi barriers to store the HLW and to ensure the long-term safety. Bentonite is proposed as a potential material for sealing the space between the canister containing the HLW and the surrounding host rock. To investigate the microbial diversity and metabolic activity of naturally occurring microorganisms in Bavarian bentonite B25 as well as their influence on the used canister materials (copper & cast iron), we conducted anaerobic microcosm experiments, incubating Bavarian bentonite B25, synthetic pore waters (synthetic Opalinus Clay pore water or diluted cap rock solution) and metal plates (copper or cast iron coupons) up to 400 days at 37 °C. We also added H2 or lactate to stimulate microbial activities in certain microcosms. Geochemical analyses showed a decrease of Eh, potassium and sulfate as well as an increase of Fe(II) in microcosms that contained synthetic Opalinus Clay pore water, H2 and cast iron. Statistical analysis indicated that these observations have no significant correlation in shaping microbial communities in the respective microcosms. Moreover, SEM images provided strong evidence that no clear corrosion on cast iron and copper was observed that is due to microbial activity. Overall, this study shows that B25 bentonite may be an ideal barrier material for a DGR due to its negative microbial effects, which prolong the entire lifespan of a DGR.

Swelling is a property of hydrophilic layered materials, which enables the penetration of polar solvents into an interlayer space with expansion of the lattice. Here we report an irreversible swelling transition, which occurs in MXenes immersed in excess dimethyl sulfoxide (DMSO) upon heating at 362-370 K with an increase in the interlayer distance by 4.2 Å. The temperature dependence of MXene Ti3C2Tx swelling in several polar solvents was studied using synchrotron radiation X-ray diffraction. MXenes immersed in excess DMSO showed a step-like increase in the interlayer distance from 17.73 Å at 280 K to 22.34 Å above ∼362 K. The phase transformation corresponds to a transition from the MXene structure with one intercalated DMSO layer into a two-layer solvate phase. The transformation is irreversible and the expanded phase remains after cooling back to room temperature. A similar phase transformation was observed also for MXene immersed in a 2 : 1 H2O : DMSO solvent ratio but at a lower temperature. The structure of MXene in the mixed solvent below 328 K was affected by the interstratification of differently hydrated (H2O)/solvated (DMSO) layers. Above the temperature of the transformation, the water was expelled from MXene interlayers and the formation of a pure two-layer DMSO-MXene phase was found. No changes in the swelling state were observed for MXenes immersed in DMSO or methanol at temperatures below ambient down to 173 K. Notably, MXenes do not swell in 1-alcohols larger than ethanol at ambient temperature. Changing the interlayer distance of MXenes by simple temperature cycling can be useful in membrane applications, e.g. when a larger interlayer distance is required for the penetration of ions and molecules into membranes. Swelling is also very important in electrode materials since it allows penetration of the electrolyte ions into the interlayers of the MXene structure.

Molecular imaging offers the possibility to investigate biological and biochemical processes non-invasively and to obtain information on both anatomy and dysfunctions. Based on the data obtained, a fundamental understanding of various disease processes can be derived and treat-ment strategies can be planned. In this context, methods that combine several modalities in one probe are increasingly being used. Due to a comparable, very high sensitivity and provided complementary information, the combination of nuclear and optical probes has taken on a special significance. In this review article, dual-labelled systems for biomodal nuclear and optical imaging based on both modular ligands and nanomaterials are discussed. Particular attention is paid to radiometal-labelled molecules for single-photon emission computed tomography (SPECT) and positron emission tomography (PET), and metal complexes combined with fluorescent dyes for optical imaging. The clinical potential of such probes, especially for fluorescence-guided surgery is assessed.

Recent numerical investigations revealed that the heterogeneity of the dissolution rate observed in numerous experiments cannot be explained by fluid transport effects. This heterogeneity is attributed to intrinsic surface reactivity. Therefore, reactive transport models (RTM) require parameterization of the surface reactivity for accurate predictions. For this purpose, a nanotopographic parametrization based on surface slope has been recently suggested. In this study, we utilize and improve this parametrization for RTMs of pore-scale systems, from the crystal surface to the single crystal geometry, going beyond the previous reactivity parametrization. 2D and 3D RTMs were developed using COMSOL Multiphysics for calcite systems based on experimental measurements. We compared the results between classically parameterized RTMs, RTMs with new slope parameterization, and experimental data. The effect of flow on dissolution under conditions far-from-equilibrium is found to be negligible, highlighting the importance of surface reactivity in the dissolution reaction. For the first time, the new slope factor was able to accurately reproduce the experimental results on a crystal surface with large field-of-view, large height variability of the topography, and over a long-term reaction period. The new parameterization had greatly improved sensitivity for intermediate reactivity ranges compared to the previous parameterization. A 3D model is used to present the general applicability of the parameterization for use in realistic geometric data sets. Thus, we also show that neglecting surface reactivity in an RTM leads to incorrect predictions regarding the porosity, pore geometry, and surface topography of the system. Our new slope factor can successfully serve as a first-order proxy for the distribution of surface reactivity in 3D pore-scale rock systems. The description of surface reactivity is crucial for accurate long-term modeling of natural rock systems.

Radionuclide migration is one of the key problems for the long-term safety of nuclear waste repositories. One possible mechanism to retard or prevent the migration of radionuclides from the repository to the biosphere is the adsorption onto mineral surfaces of the surrounding host rock. Clay rock formations such as the Opalinus Clay are being considered for potential sites for nuclear waste repositories, partly due to the strong sorption potential of clay minerals. Phyllosilicates, such as clay minerals or mica, have shown a high affinity for adsorption of various radionuclides in several experimental studies. However, mineral surfaces in natural environments are often subjected to reactions (e.g., dissolution) that may alter the surface nanotopography and, consequently, affect the overall adsorption process. Recently, it has been reported that the nanotopography of calcite surfaces leads to heterogonous sorption of europium due to differences in the atomic configuration of the adsorption sites [1].
In this study, we investigate the influence of surface site coordination on the adsorption energy barrier and the resulting overall distribution of radionuclide adsorption on the mineral surface. We utilize numerical methods to study the adsorption of Eu(OH)3 on a muscovite (001) surface with different nanotopographic structures. Density Functional Theory (DFT) calculations are performed to obtain the adsorption energy barriers of several surface sites present on muscovite. For each site, the adsorption energy is calculated based on a series of geometry optimizations with increasing Eu–site distance. The values of the site-specific adsorption energy barriers are then implemented in a Kinetic Monte Carlo (KMC) model based on a previous study [2]. In the KMC model, larger surface structures, such as steps or etch pits, are placed on the muscovite surface and a dissolution simulation is performed to create a realistic nanotopography. Based on the adsorption energy barriers obtained with DFT, Eu(OH)3 is adsorbed on the generated muscovite surface in a second KMC model step. The KMC model is then used to predict the distribution of adsorbed Eu(OH)3 and the temporal evolution of the adsorption. Using this combined numerical approach, we show the effect of surface site coordination on radionuclide adsorption reactions and the resulting adsorption heterogeneity on mineral surfaces at large scales.

The long-term safety of nuclear waste repositories heavily depends on their potential to prevent the migration of the contained radionuclides. In the host rock, adsorption onto mineral surfaces is a key mechanism to bind radionuclides and inhibit further transport to the biosphere. Several experimental studies have shown that phyllosilicates (e.g., clay minerals or mica) provide surfaces with strong sorption potential. Therefore, clay rock formations such as the Opalinus clay are being investigated as repository sites in several countries. In the natural environment of host rock formations, the mineral surfaces are exposed to a variety of reactions altering the surface nanotopography (e.g., dissolution). These changes can affect radionuclide adsorption processes. A recent study revealed that calcite surfaces show heterogeneous europium sorption due to their nanotopography [1]. The nanotopography leads to a heterogeneous distribution of reactive sites that are available for adsorption reactions.

In this study, we use numerical methods to investigate the adsorption of Eu(OH)3 on muscovite (001) surfaces with varying nanotopography. Density Functional Theory (DFT) is used to calculate adsorption energy barriers of several atomic sites that are present on the muscovite surface. The sites differ in their first and second order coordination environment, which influences their adsorption potential. A series of geometry optimizations with increasing Eu–site distance is computed to obtain the adsorption energy for each site. The site-specific adsorption energy barriers values are then used for the parameterization of a Kinetic Monte Carlo (KMC) model based on a previous study [2]. The KMC model allows for the simulation of adsorption on larger muscovite surfaces. It is separated into: (1) placement of structures (e.g., pits) and subsequent dissolution simulation for nanotopography generation and (2) Eu(OH)3 adsorption based on the available surface sites and their DFT-derived adsorption energy barrier. This combined numerical approach can show the effect of surface site coordination on radionuclide adsorption and predict the resulting adsorption heterogeneity on mineral surfaces.

[1] Yuan et al. (2021) Environ. Sci. Technol., 55, 15797–15809.
[2] Schabernack et al. (2021) Minerals, 11, 468.

Making research reproducible and FAIR (Findable, Accessible, Interoperable, and Reusable) often requires more information than what is commonly published within scientific articles. There is a growing number of repositories for publishing additional material like data or code. However, articles are still at the center of most scientific work and thus efforts on gathering information which is important for reproducibility but not for the article itself are often only started at a later stage. This usually makes the collection more tedious, error-prone, and less comprehensive.

In order to lower the barrier for recording all relevant information directly when it is generated, we propose a design for a data and metadata entry and editing tool. It should allow researchers to create metadata for the files and assets which they already have and offer a possibility for structured entry of new data. To support consistent (meta)data entry over time, the user will be able to create forms which can enforce comprehensiveness and correctness. Furthermore, data FAIRness is supported through the automated usage of established ontologies for (meta)data annotation. This will be done by a background process so the user isn´t involved in these technologies. Nevertheless the tool will grant further possibilities to those who are aware of ontologies used in their domain. Resources can be referenced consistently across (meta)data sets of many stakeholders through identifiers provided by central sources. In conjunction, the usage of these common identifiers and ontologies forms large knowledge graphs of the data recorded with our tool.

This contribution will be a discussion of the various components of such a tool, potentially used metadata standards, possible variations, important features, and most relevant: How it can be useful for your work!

Introduction: Potential radiopharmaceuticals are usually evaluated in small animals. Aligned with the 3R principle, animal numbers could be reduced by using “Micro-Physiological Systems (MPS)” which is an organ-on-chip technology. In MPS modules, cultured cells and human organoids can be analysed in a circulatory system under defined conditions [1,2].
In this study, preliminary tests with radiolabeled anti-EGFR antibody cetuximab (C225) were performed using 2D or 3D (spheroid) cultures of A431 cells. The aim was to determine selected pharmacological parameters such as binding affinity of radiolabeled C225 using the MPS.
Methods: 104 A431 cells were placed in the 6-well chamber of the MPS module, either as monolayer or as spheroids (0.8 ± 0.3 mm) and cultured for 24 hours. The conjugate NOTA-C225 was radiolabeled with 68Ga or 64Cu (molar activity: 81.1 ± 14.7 MBq/nmol). An integrated micropump, driven by a controller, generates a pulsatile fluid flow through the fluidic channels upon the cells (Fig.1).
Medium (total binding) and medium with an EGFR blocking C225 concentration of 2 µM (nonspecific binding) (1mL) was pumped through the MPS for 5 min (80 bpm at a volume flow of 6.4 µL/s). Under saturation conditions, 1.2 to 15 nM of radiolabeled C225 were applied to cells and spheroids. Using the micropump, a total volume of 1 mL of the compound solutions were distributed through the MPS over 15 min. After washing with PBS for 10 min, the MPS modules were exposed to an imaging plate, and bound radiolabeled C225 was determined by phosphor imaging. Evaluation was realised with AIDA /GraphPadPrism.
Results/Discussion: We demonstrate that a MPS environment can be employed to determine radioligand binding parameters. The first saturation assays show high binding affinity of the radiolabeled C225 with Kd values in the low nanomolar range (1.7 to 25 nM), being in the range of previous reports [3,4]. Kd of A431 monolayers was similar to that of A431 spheroids. Nonspecific binding on the integrated channels and on empty wells was < 15% of the specifically bound tracer molecule.
Our data provides a rationale to pursue further studies with multi-organ chips using MPS in order to reduce animal numbers used in preclinical radiotracer evaluation. Further steps include trials with kidney- and liver organoids, and an investigation of how radiolabeled C225 is bound, trapped and metabolized using this preclinical model.
Conclusion: Herein, we show that binding parameters of the radiolabeled C225 can be determined in a MPS environment using 2D and 3D cell culture systems. Further studies are required to confirm these data for other EGFR positive and negative cells and for other antibody receptor pairs.
Acknowledgement: W.S. and F.S. acknowledge the financial support by the Federal Ministry of Education and Research of Germany (BMBF) in the project MPS-RP (project number AKZ161L0275A/B).
References: [1] Busek et al., J Sens Sens Syst 2016, 5, 228. [2] Schmieder et al., Proc SPIE 2020, 11268, 1126804_1. [3] Eiblmaier et al., J Nucl Med 2008, 9, 1472. [4] Bellaye et al., Clin Transl Oncol 2018, 12, 1557.

In deep geological repositories for radioactive waste, interactions of radionuclides with mineral surfaces occur under complex geochemical conditions involving complex solution compositions and high pH resulting from degradation of cementitious geo-engineered barriers. Ca2+ cations have been hypothesized to play an important role as mediators for the retention of U(VI) on Ca-bentonite at (hyper)alkaline conditions, despite the anionic character of both the mineral surface and the aqueous uranyl species. To gain deeper insight into this sorption process, the effect of Ca2+ on U(VI) and Np(VI) retention on alumosilicate minerals has been comprehensively evaluated, using batch sorption experiments and time-resolved laser-induced luminescence spectroscopy (TRLFS). Sorption experiments with Ca2+ or Sr2+ and zeta potential measurements showed that the alkaline earth metals sorb strongly onto Ca bentonite at pH 8–13, leading to a partial compensation of the negative surface charge, thereby generating potential sorption sites for anionic actinyl species. U(VI) and Np(VI) sorption experiments in the absence and presence of Ca2+ or Sr2+ confirmed that these cations strongly enhance radionuclide retention on kaolinite and muscovite at pH ≥ 10. Concerning the underlying retention mechanisms, site-selective TRLFS provided spectroscopic proof for two dominating U(VI) species at the alumosilicate surfaces: (i) A ternary U(VI) complex, where U(VI) is bound to the surface via bridging Ca cations with the configuration surface ≡ Ca – OH – U(VI) and, (ii) U(VI) sorption into the interlayer space of calcium (aluminum) silicate hydrates (C-(A-)S-H), which form as secondary phases in the presence of Ca due to partial dissolution of alumosilicates under hyperalkaline conditions. Consequently, the present study confirms that alkaline earth elements, which are ubiquitous in geologic systems, enable strong retention of hexavalent actinides on clay minerals under hyperalkaline repository conditions.

A myriad of phenomena in materials science and chemistry rely on quantum-level simulations of the electronic structure in matter. While moving to larger length and time scales has been a pressing issue for decades, such large-scale electronic structure calculations are still challenging despite modern software approaches and advances in high-performance computing.
The silver lining in this regard is the use of machine learning to accelerate electronic structure calculations -- this line of research has recently gained growing attention.
The grand challenge therein is finding a suitable machine-learning model during a process called hyperparameter optimization. This, however, causes a massive computational overhead in addition to that of data generation.
We accelerate the construction of machine-learning surrogate models by roughly two orders of magnitude by circumventing excessive training during the hyperparameter optimization phase. We demonstrate our workflow for Kohn-Sham density functional theory, the most popular computational method in materials science and chemistry.

The development of PSMA-targeting low-molecular-weight hybrid molecules aims at advancing preoperative imaging and accurate intraoperative fluorescence guidance for improved diagnosis and therapy of prostate cancer. In hybrid probe design, the major challenge is the introduction
of a bulky dye to peptidomimetic core structures without affecting tumor-targeting properties and pharmacokinetic profiles. This study developed a novel class of PSMA-targeting hybrid molecules based on the clinically established theranostic agent PSMA-617. The fluorescent dye-bearing candidates
of the strategically designed molecule library were evaluated in in vitro assays based on their PSMA-binding affinity and internalization properties to identify the most favorable hybrid molecule composition for the installation of a bulky dye. The library’s best candidate was realized with IRDye800CW providing the lead compound. Glu-urea-Lys-2-Nal-Chx-Lys(IRDye800CW)-DOTA (PSMA-927) was investigated in an in vivo proof-of-concept study, with compelling performance in organ distribution studies, PET/MRI and optical imaging, and with a strong PSMA-specific tumor uptake comparable to that of PSMA-617. This study provides valuable insights about the design of PSMA-targeting low-molecular-weight hybrid molecules, which enable further advances in the field
of peptidomimetic hybrid molecule development.

The mean ionization state (MIS) is a critical property in dense plasma and warm dense matter research, for example as an input to hydrodynamics simulations and Monte--Carlo simulations. Unfortunately, however, the best way to compute the MIS remains an open question. Average-atom (AA) models are widely-used in this context due to their computational efficiency, but as we show here, the canonical approach for calculating the MIS in AA models is typically insufficient. We therefore explore three alternative approaches to compute the MIS. Firstly, we modify the canonical approach to change the way electrons are partitioned into bound and free states; secondly, we develop a novel approach using the electron localization function; finally, we extend a method which uses the Kubo--Greenwood conductivity to our average-atom model. Through comparisons with higher-fidelity simulations and experimental data, we find that any of the three new methods usually out-performs the canonical approach, with the electron localization function and Kubo--Greenwood methods showing particular promise.

Background:

The PET nuclide and reconstruction method can have a considerable influence on spatial resolution and image quality of PET/CT scans, which can, for example, influence the diagnosis in oncology. The individual impact of the positron energy of 18 F, 68 Ga and 64 Cu on spatial resolution and image quality of PET/CT scans acquired using a clinical, digital scanner was compared. Furthermore, the impact of different reconstruction parameters on image quality and spatial resolution was evaluated for 18 F-FDG PET/CT scans acquired with a scanner of the newest generation.
Methods:
PET/CT scans of a Jaszczak phantom and a NEMA PET body phantom, filled with 18 F-FDG, 68 Ga-HCl and 64 Cu-HCl, respectively, were performed on a Siemens Biograph Vision. Images were assessed using spatial resolution and image quality (Recovery Coefficients (RC), coefficient of variation within the background, Contrast Recovery Coefficient (CRC), Contrast-Noise-Ratio (CNR), and relative count error in lung insert). In a subsequent analysis, the scan of the NEMA PET body phantom filled with 18 F-FDG was reconstructed applying different parameters (with/without the application of Point Spread Function (PSF), Time of Flight (ToF) or post-filtering; matrix size). Spatial resolution and quantitative image quality were compared between reconstructions.
Results:
We found that image quality was comparable between 18 F-FDG and 64 Cu-HCl PET/CT measurements featuring similar maximal endpoint energy. In comparison, RC, CRC and CNR were worse in 68 Ga-HCl data, despite similar count rates. Spatial resolution was up to 18 % worse in 68 Ga-HCl compared to 18 F-FDG images. Post-filtering of 18 F-FDG acquisitions changed image quality the most and reduced spatial resolution by 52 % if a Gaussian filter with 5 mm FWHM was applied. ToF measurements especially improved the recovery of the smallest lesion (RC mean = 1.07 compared to 0.65 without ToF) and improved spatial resolution by 29 %.
Conclusions:
The positron energy of PET nuclides influences spatial resolution and image quality of digital PET/CT scans. Image quality of 68 Ga-HCl PET/CT images was worse compared to 18 F-FDG and 64 Cu-HCl, respectively, despite similar count rates. Reconstruction parameters have a high impact on image quality and spatial resolution and should be considered when comparing images of different scanners or centers.

Various factors have been identified that influence quantitative accuracy and image interpretation in positron emission tomography (PET). Through the continuous introduction of new PET technology—both imaging hardware and reconstruction software—into clinical care, we now find ourselves in a transition period in which traditional and new technologies coexist. The effects on the clinical value of PET imaging and its interpretation in routine clinical practice require careful reevaluation. In this review, we provide a comprehensive summary of important factors influencing quantification and interpretation with a focus on recent developments in PET technology. Finally, we discuss the relationship between quantitative accuracy and subjective image interpretation.

Magnetoelectric antiferromagnets like Cr2O3 are attractive for the realization of energy-efficient and high-speed spin-orbitronic-based memory devices. Here, we demonstrate that fabrication of polycrystalline bulk Cr2O3 samples in conditions far out of equilibrium relying on spark plasma sintering allows to realize high-quality material with density close to that of a single crystal. The sintered sample possesses a preferential [001] texture at the surface, which can be attributed to uniaxial strain applied to the sample during the sintering process. The antiferromagnetic state of the sample and linear magnetoelectric effect are accessed all-electrically relying on the spin Hall magnetoresistance effect in the Pt electrode interfaced with Cr2O3. In line with the integral magnetometry measurements, the magnetotransport characterization reveals that the sample possesses the magnetic phase transition temperature of about 308 K, which is the same as in a single crystal. The antiferromagnetic domain pattern consists of small domains with sizes in the range of several micrometers only, which is formed due to the granular structure of the sample. The possibility to access the magnetoelectric properties of the samples relying on magnetotransport measurements indicates the potential of the polycrystalline Cr2O3 samples for prospective research in antiferromagnetic spintronics.

Thin films of the magnetoelectric insulator α-Cr2O3 are technologically relevant for energy-efficient magnetic memory devices controlled by electric fields. In contrast to single crystals, the quality of thin Cr2O3 films is usually compromised by the presence of point defects and their agglomerations at grain boundaries, putting into question their application potential. Here, we study the impact of the defect nanostructure including sparse small-volume defects and their complexes on the magnetic properties of Cr2O3 thin films. By tuning the deposition temperature, we tailor the type, size, and relative concentration of defects, which we then analyze based on positron annihilation spectroscopy complemented with local electron microscopy studies. The structural characterization is correlated with magnetotransport measurements and nitrogen vacancy microscopy of antiferromagnetic domain patterns. Defects pin antiferromagnetic domain walls and stabilize complex multidomain states with a typical domain size in the sub-micrometer range. Despite their influence on the domain configuration, we demonstrate that neither small open-volume defects nor grain boundaries in Cr2O3 thin films affect the Néel temperature in a broad range of deposition parameters. Our results pave the way towards the realization of spin-orbitronic devices where magnetic domain patterns can be tailored based on defect nanostructures without affecting their operation temperature.

Nanoparticles (NPs) are relevant in medicine, catalysis and environmental remediation. Among them, magnetite (Fe(II)Fe(III)2O4) NPs are especially interesting due to their redox and magnetic properties and their tunability of size and surface properties, which makes them suited for the removal of many redox-active pollutants. Tc is of great concern for the safety assessment of nuclear waste repositories, since 99Tc is a fission product with a long half-life (t1/2 = 2.1∙105 years). Under oxidative conditions Tc forms an anionic species, pertechnetate (Tc(VII)O4-), which is mobile due to its weak interactions with minerals. Under anaerobic conditions, pertechnetate is reduced by reducing agents to Tc(IV), which sorbs on minerals, forms insoluble oxides like TcO2, or is structurally incorporated by stable natural minerals. [1]
Previous studies by Yalcintas et al. [2] suggested that Tc(VII) reduction by magnetite resulted in the precipitation and surface adsorption of TcO2-like oligomers at pH 9, i.e. close to the pH of magnetite solubility minimum, while reduction at lower pH of 6 7 resulted in a partial incorporation of Tc(VI) in octahedral Fe sites of magnetite [3]. A working hypothesis was that the incorporation happens only at higher magnetite solubility, while the final retention mechanism remains enigmatic. Thus, our investigations are aimed to carry out a systematic approach covering a wide pH range (3 13), initial Tc concentration ([Tc] = µM-mM) and equilibration time (teq = 1 210 days).
The results show that magnetite removes at least 98 % dissolved Tc. To characterize the molecular geometry of the Tc vicinity, mainly X-ray absorption spectroscopy (XAS) has been used. XANES analysis reveals the predominance of Tc(IV) at all evaluated pH values, supporting that reductive Tc immobilization is the main retention mechanism. A detailed EXAFS analysis with different preparation methods (sorption, coprecipitation, Fe(II)-recrystallization) is currently underway to elucidate the molecular structure of the retained Tc species.
We thank the German Federal Ministry of Economic Affairs and Energy (BMWi) for funding the KRIMI project (02NUK056C).
[1] A.H. Meena, Y. Arai, ENVIRONMENTAL CHEMISTRY LETTERS, 2017, 15, 241.
[2] E. Yalcintas et al., DALTON TRANSACTIONS, 2016, 45, 17874.
[3] T. Kobayashi et al., Radiochimica Acta, 2013, 101, 323.

Thick steel casks are used for radioactive waste disposal in deep geological repositories. However, it is expected that steel corrodes over time. The corrosion products are expected to form mixed iron oxides, mainly magnetite. After tens of thousands of years, casks may breach allowing leaching of the radiotoxic elements, such as plutonium and technetium, by host rock pore-water. The dissolved radionuclides can then interact with the steel corrosion products and be adsorbed or incorporated into the solids [1]. But since these interaction mechanisms are poorly understood at the atomistic scale, our goal is to better understand them by using computer simulations alongside experiments [2].
In this computational study we identified the dominant low index surfaces on nano-magnetite particles and their termination at the relevant conditions based on Kohn-Sham density functional theory (DFT). This was done using the open source CP2K code and, for highly correlated chemical elements such as iron or plutonium, utilizing the DFT+U method because of the highly localized d and f electrons. The U parameter was determined by comparing experimental cell constants and band gaps to our result [3]. With this revised model, we examined the preferential magnetite crystal orientation plane (111) with different surface terminations as a function of oxygen and water fugacity. Based on our modelling, we found the most stable magnetite (111) surfaces under real repository conditions being Fe_oct1-O-H and Fe_tet1-O-H. Further, we used classical and ab initio MD simulations to investigate the behaviour of radionuclides at the water-magnetite interface in deep geological repositories.
[1] Dumas, T.; Fellhauer, D.; Schild, D.; Gaona, X.; Altmaier, M.; Scheinost, A. C. Plutonium Retention Mechanisms by Magnetite Under Anoxic Conditions: Entrapment Versus Sorption. ACS Earth and Space Chemistry 2019, 3 (10), 2197–2206.
[2] Yalçıntaş, E.; Scheinost, A. C.; Gaona, X.; Altmaier, M. Systematic XAS Study on the Reduction and Uptake of Tc by Magnetite and Mackinawite. Dalton Transactions 2016, 45 (44), 17874–17885.
[3] Kéri, A.; Dähn, R.; Krack, M.; Churakov, S. V. Combined XAFS Spectroscopy and Ab Initio Study on the Characterization of Iron Incorporation by Montmorillonite. Environmental Science & Technology 2017, 51 (18), 10585–10594.

The design of a nuclear waste repository is a challenging technological entreprise. The reasons are intrinsically related to the nature of the problem: the storage of a variety of radioactive materials for a period longer than human history. The potential consequences of a repository failure are dramatic because they lead to high environmental impact and economical costs of remediation [1]. Repository implementation should therefore rely on deep process understanding and intrinsic passive safety of geological systems. Modern approaches to the geological storage of nuclear wastes deal with a careful site selection and a multi-barrier system. The Swiss waste disposal program is currently in the final stage of the site selection process. Three geological location identified as potential disposal sites are located in Opalinus Clay formations. The multi-barrier disposal concept is heavily relying on the physical and chemical properties of clay minerals, in particular, their interaction with radionuclides [2].
The minerals clays of interest (illite and montmorillonite) were studied over years to derive empirically the sorption properties necessary for the safety assessments. Natural systems are heterogeneous in terms of mineralogical and chemical composition. The experimental studies are limited to a finite number of scenarios, simplified chemistry and short timescale. A mechanistic description of the sorption processes is necessary to transfer the data obtained from simplified reference systems to complex natural environments using computational models based on physical and chemical process understanding. A synthetic clay, saponite, was selected as the customizable and chemically pure starting material. Sorption experiments were carried out to obtain sorption isotherms for a divalent transition metal (nickel) and a trivalent lanthanide (lutetium). The mechanistic information about the sorption processes was achieved by X-ray spectroscopy techniques that have been carried out at the Rossendorf Beamline at the European Synchrotron Radiation Facility. The spectroscopic data are interpreted with help of ab initio molecular dynamics simulations.

References:

[1] Ilg, P., Gabbert S. and Weikard, H.P. Nuclear Waste Management under Approaching Disaster: A Comparison of Decommissioning Strategies for the German Repository Asse II. Risk Analysis 2017, 37, 7, 1213-1232. https://doi.org/10.1111/risa.12648
[2] Churakov, S.V., Hummel, W. and Marques Fernandes, M. Fundamental Research on Radiochemistry of Geological Nuclear Waste Disposal. Chimia 2020, 74, 1000-1009. https://doi.org/10.2533/chimia.2020.1000

DNA and RNA offer fascinating possibilities for the self-organisation of complex patterns, which can be used in various combinations.
Since this self-organisation occurs at the nanometer scale, it can possibly offer ways for the creation of nanooptical or nanoelectronic devices.
Therefore, the quest for conductivity of DNA or RNA has inspired a vast amount of experiments which have led to a large number of diverse results.
In the recent past, a coherent picture has emerged which describes charge transport along DNA or RNA in various environments.
Based on this, electronic applications of these biomolecules have been developed.

The global extent and temporally asynchronous pattern of COVID-19 spread have repeatedly highlighted the role of international borders in the fight against the pandemic. Additionally, the deluge of high resolution, spatially referenced epidemiological data generated by the pandemic provides new opportunities to study disease transmission at heretofore inaccessible scales. Existing studies of cross-border infection fluxes, for both COVID-19 and other diseases, have largely focused on characterizing overall border effects. Here, we couple fine-scale incidence data with localized regression models to quantify spatial variation in the inhibitory effect of an international border. We take as a case study the border region between the German state of Saxony and the neighboring regions in northwestern Czechia, where municipality-level COVID-19 incidence data are available on both sides of the border. Consistent with past studies, we find an overall inhibitory effect of the border, but with a clear asymmetry, where the inhibitory effect is stronger from Saxony to Czechia than vice versa. Furthermore, we identify marked spatial variation along the border in the degree to which disease spread was inhibited. In particular, the area around Löbau in Saxony appears to have been a hotspot for cross-border disease transmission. The ability to identify infection flux hotspots along international borders may help to tailor monitoring programs and response measures to more effectively limit disease spread.

An automated and reliable processing of bubbly flow images is highly needed to analyse large data sets of comprehensive experimental series. A particular difficulty arises due to overlapping bubble projections in recorded images, which highly complicates the identification of individual bubbles. Recent approaches focus on the use of deep learning algorithms for this task and have already proven the high potential of such techniques. The main difficulties are the capability to handle different image conditions, higher gas volume fractions and a proper reconstruction of the hidden segment of a partly occluded
bubble. In the present work, we try to tackle these points by testing three different methods based on Convolutional Neural Networks (CNN’s) for the two former and two individual approaches that can be used subsequently to address the latter. To validate our methodology, we created test data sets with synthetic images that further demonstrate the capabilities as well as limitations of our combined approach. The generated data, code and trained models are made accessible to facilitate the use as well as further developments in the research field of bubble recognition in experimental images.

Masers as telecommunication amplifiers have been known for decades, yet their application is strongly limited due to extreme operating conditions requiring vacuum techniques and cryogenic temperatures. Recently, a new generation of masers has been invented based on optically pumped spin states in pentacene and diamond. In this study, we pave the way for masers based on spin S = 3/2 silicon vacancy (VSi) defects in silicon carbide (SiC) to overcome the microwave generation threshold and discuss the advantages of this highly developed spin hosting material. To achieve population inversion, we optically pump the VSi into their mS = ±1/2 spin sub-states and additionally tune the Zeeman energy splitting by applying an external magnetic field. In this way, the prerequisites for stimulated emission by means of resonant microwaves in the 10 GHz range are fulfilled. On the way to realising a maser, we were able to systematically solve a series of subtasks that improved the underlying relevant physical parameters of the SiC samples. Among others, we investigated the pump efficiency as a function of the optical excitation wavelength and the angle between the magnetic field and the defect symmetry axis in order to boost the population inversion factor, a key figure of merit for the targeted microwave oscillator. Furthermore, we developed a high-Q sapphire microwave resonator (Q 10^4 – 10^5) with which we find indications of superradiant stimulated microwave emission. In summary, SiC with optimized spin defect density and thus spin relaxation rates is well on its way of becoming a suitable maser gain material with wide-ranging applications.

The Helmholtz-Center Dresden-Rossendorf operates several user beamlines for materials research using positron annihilation energy and lifetime spectroscopy. The superconducting electron LINAC ELBE [2] drives a hard X-ray source, which generates positrons through pair production. The high-intensity Mono-energetic Positron Source MePS utilizes moderated positrons with adjustable kinetic energies ranging from 500 eV to 16 keV for depth profiling of defects in thin films. A magnetic beam transport system consisting of a beam chopper, a beam buncher, and a post-accelerator guides the positron beam towards the sample under investigation. Fully digital data processing of positron annihilation lifetime events generates high-quality spectra with timing resolutions down to about 210 ps and count rates in excess of 120 kcps.
The MePS facility is currently complemented by an additional beamline named Apparatus for In-situ Defect Analysis, AIDA-II, where in-situ defect studies are to be performed in a wide temperature range during thin film growth and under ion irradiation. A complimentary but functionally similar setup, AIDA-I, is operated at a 22Na-based mono-energetic continuous positron beam used for in-situ (coincidence) Doppler-broadening positron annihilation spectroscopy experiments. Recent developments figuring the formation and time dynamics of hydrogen-induced vacancies in nickel and niobium and the role of defects in magneto-ionics and ZnO semiconductor films will be presented.
The MePS facility has partly been funded by the Federal Ministry of Education and Research (BMBF) with the grant PosiAnalyse (05K2013). The initial AIDA system was funded by the Impulse- und Networking fund of the Helmholtz-Association (FKZ VH-VI-442 Memriox). The AIDA facility was funded through the Helmholtz Energy Materials Characterization Platform.

DNA origami technology enables the folding of DNA strands into complex nanoscale shapes whose properties and interactions with molecular species often deviate significantly from that of genomic DNA. Here, we investigate the salting-out of different DNA origami shapes by the kosmotropic salt ammonium sulfate that is routinely employed in protein precipitation. We find that centrifugation in the presence of 3 M ammonium sulfate results in notable precipitation of DNA origami nanostructures but not of double-stranded genomic DNA. The precipitated DNA origami nanostructures can be resuspended in ammonium sulfate-free buffer without apparent formation of aggregates or loss of structural integrity. Even though quasi-1D six-helix bundle DNA origami are slightly less susceptible toward salting-out than more compact DNA origami triangles and 24-helix bundles, precipitation and recovery yields appear to be mostly independent of DNA origami shape and superstructure. Exploiting the specificity of ammonium sulfate salting-out for DNA origami nanostructures, we further apply this method to separate DNA origami triangles from genomic DNA fragments in a complex mixture. Our results thus demonstrate the possibility of concentrating and purifying DNA origami nanostructures by ammonium sulfate-induced salting-out.

PtSe2 is one of the most promising materials for the next generation of piezoresistive sensors. However, the large-scale synthesis of homogeneous thin films with reproducible electromechanical properties is challenging due to polycrystallinity. We show that stacking phases other than the 1T phase become thermodynamically available at elevated temperatures that are common during synthesis. We show that these phases can make up a significant fraction in a polycrystalline thin film and discuss methods to characterize them, including their Seebeck coefficients. Lastly, we estimate their gauge factors, which vary strongly and heavily impact the performance of a nanoelectromechanical device.

Mineral deposits are metal enrichment anomalies, occurring as local manifestations of the interplay between various geological processes that operate at a wide range of temporal and spatial scales. Mineral prospectivity maps are generated by integrating several proxy maps that represent critical geological processes in a mineral system conceptual model. The derivation of mineral prospectivity maps is subject to several types of uncertainty, including systematic (inadequate knowledge of mineralisation processes), stochastic (incomplete geoscience data), and model uncertainty (multiple choices for predictive models and their parameters). Traditional approaches to mineral prospectivity mapping often fail to fully appreciate different sources of uncertainty and spatiotemporal interdependencies between proxy maps associated with the mineral system components. Therefore, these traditional approaches are biased and understate the overall uncertainty. For instance, spatial proxies are mapped using univariate deterministic approaches that ignore stochastic uncertainty and spatial dependencies (i.e., auto- and cross-correlations). This study presents a multivariate stochastic model for prediction and uncertainty quantification of mineral exploration targets by combining multivariate geostatistical simulations and spatial machine learning algorithms. The spatial machine learning algorithm used in the stochastic model is a spatially aware random forests algorithm based on higher-order spatial statistics. It is demonstrated that the proposed approach can detect intrinsic heterogeneity, spatial interdependencies, and complex spatial patterns in proxy maps that are related to the mineralisation type of interest. The approach is illustrated using a synthetic case study with multiple geochemical, geophysical, and lithological attributes.

Data for the pre-print "First-principles derivation and properties of density-functional average-atom models", https://arxiv.org/abs/2103.09928.

Each data folder is named according to the corresponding figure in the paper. For any questions, please contact the authors.

The necessity of exhaustive documentation of research data arises from an increasing depth of scientific understanding and investigations of unknown phenomena with research teams of different areas and fields. Different methods and definitions and insufficient documentation of field work, experimental and numerical examinations lead to information loss, especially over time. To counteract this problem the scientific community aims to make research data Findable, Accessible, Interoperable and Reusable (FAIR). Unfortunately infrastructure, tools, personnel and acceptability for these additional steps are often missing and result in the mentioned paucity of information and data. Within the Helmholtz Association the Helmholtz Metadata Collaboration (HMC) has taken on the task of building this infrastructure to support high quality data documentation and publication throughout the entire lifecycle of research data and to raise the awareness for necessary structural changes in the wider scientific community.
One goal of HMC is the mapping of existing data management structures and demands in the different research fields of the Helmholtz Community. These fields are especially addressed with Hubs, being the connection between HMC and the specific needs of the research fields. Based on the collected information HMC will implement tools to assist scientists, data managers and IT administrators in making their research data FAIR. Furthermore members of HMC will connect with other (meta-)data initiatives to work towards necessary structural changes in the world of scientific research by e.g. defining standards.
In this poster we will discuss the FAIR principles and introduce the Helmholtz Metadata Collaboration and their tasks. Also, we will show concrete examples from the geoscientific part of Hub Energy. The Hub in which we are active.

Radionuclide speciation inside long-term radioactive waste repositories needs to be understood in order to ensure effective containment of the waste. Organic ligands originating from the degradation of organic components inside such a repository can possibly affect the mobility of radionuclides in solution. The present study focuses on nitrilotriacetic acid, NTA, as a model molecule and europium, Eu(III), as a nonradioactive analog with outstanding luminescence and magnetic properties.
The complexation of NTA with Eu(III) (in ratios of 1:2 and 1:1 Eu:NTA) as a function of pH was studied using nuclear magnetic resonance (NMR) spectroscopy in 1 M NaCl D₂O solution. The ¹H and ¹³C NMR spectra of the NTA solutions with Eu(III) show clearly distinguishable signals for the free NTA and two Eu-NTA complexes, which is indicative of a 1:1 and a 1:2 Eu-NTA complex. The interaction of Eu(III) with NTA is relatively strong and favors the 1:2 Eu-NTA complex even in solution containing 1:1 Eu-NTA ratio, unless in very acidic solutions.
As a repository relevant cationic groundwater components, the influence of Ca(II) and Al(III) on Eu(III) complexation is studied in detail.
A combination of NMR spectroscopy and time-resolved laser-induced fluorescence spectroscopy yields qualitative and quantitative information on the coordination environment from the ligand’s and the metal ion’s perspective, respectively. In subsequent studies focusing on ternary systems comprising repository relevant solid phases, radionuclides and organic ligands this will allow the identification of radionuclide speciation in solution and their sorption to solid phases.
Acknowledgement: The German Federal Ministry for Economic Affairs and Energy (BMWi) is thanked for financial support within the GRaZ II project, no. 02E11860B.

Structural martensitic transformations enable various applications, which range from high stroke actuation and sensing to energy efficient magnetocaloric refrigeration and thermomagnetic energy harvesting. All these emerging applications benefit from a fast transformation, but up to now the speed limit of martensitic transformations has not been explored. Here, we demonstrate that a martensite to austenite transformation can be completed in under ten nanoseconds. We heat an epitaxial Ni-Mn-Ga film with a laser pulse and use synchrotron diffraction to probe the influence of initial sample temperature and overheating on transformation rate and ratio. We demonstrate that an increase of thermal energy drives this transformation faster. Though the observed speed limit of 2.5 x 10^27 (Js)^-1 per unit cell leaves plenty of room for a further acceleration of applications, our analysis reveals that the practical limit will be the energy required for switching. Our experiments unveil that martensitic transformations obey similar speed limits as in microelectronics, which are expressed by the Margolus–Levitin theorem.

Enhancement of the surface of the catalyst is desirable in the interest of mass transport maximizing. However, without a well-defined method of determination of its active surface, catalyst deposited with different conditions cannot be accurately compared. In this work, Co-Fe alloy cones were synthesized from the electrolyte containing ammonium chloride as a crystal modifier. It controls the direction of the deposit growth, and consequently, develops the active surface area. Moreover, the influence of the direction of the applied magnetic field on the ferromagnetic Co-Fe alloy was investigated. It affected noticeably the morphology and composition of layers and therefore, the catalytic activity of the samples in the Hydrogen Evolution Reaction (HER). Linear Sweep Voltammetry (LSV) measurements were used to test the catalytic activity in 1 M NaOH electrolyte. The expected development of the real active surface area was determined using two different methods: Brunauer-Emmett-Teller (BET) and Helmholtz Double-Layer Capacitance (DLC). Results show that no specific value of the sample surface multiplication can be found based on these methods. All conical structures were hydrophobic.

Presentation to the session: "Reproducible Science - Research Data and Research Software in Interaction" - "Reproduzierbare Wissenschaft – Forschungsdaten und Research Software im Zusammenspiel".
Reproducibility is a prerequisite for open science, but results must also be reusable in accordance with FAIR principles, and this applies in particular to research software! But how can research software, even if it is developed in open source projects, be made known to a broad user community? And how can better visibility and recognition be achieved for the developers of successful software solutions?
A new approach is currently being implemented in the Helmholtz Association. First of all, the necessary database is being created by building up a software directory as automatically as possible on the basis of standardised metadata. By evaluating these entries, successful solutions will be marked and prepared for a broad community. Finally, the best software products will be published in a "Software Flagship Store" and offered to a broad community.

High data quality is characterized by good accuracy of measurement results but equally important by a good estimation of data uncertainty (JCGM 100:2008). Using a good estimate of the uncertainty for data analysis might significantly change the data interpretation: Ignoring or underestimating uncertainties projects too high confidence into the measurand values, while overestimation of uncertainties could blur relevant information in the data. The information carried by the data can be exploited best, if the measurement result would be reported as original (not rounded) number accompanied by the values of the measurement uncertainty (Eggen, et al. 2019). This requires methods to calculate or estimate uncertainties for each analytical datum. Including uncertainties as separate values into the data interpretation is especially important if the data set has individual uncertainties, i.e., every data point has a its ‘own’ uncertainty.

Earth scientists need a method of estimating individual uncertainties based on a few multiple measurements. This method should consider the sample materials' characteristics for which the uncertainty should be assessed, e.g. range of potential measurand values, variability in sample material and heterogeneities. It should also allow to model several sources of uncertainties to account for the multi-step measurement procedure. And last but not least, the method should remain affordable and practical, e.g. the method should also be applicable if samples are send to external laboratories.

In this contribution, we present a method to quantify individual uncertainties with respect to the analyte level (Ellison and Williams 2012)[Annex E.5], including uncertainty model component which allows to model Poisson type error, e.g. due to heterogeneities which are typical for samples in the geosciences. Case studies and examples in data science languages are presented to facilitate the implementation.