Publications Repository - Helmholtz-Zentrum Dresden-Rossendorf

Daten sind ein essentieller Bestandteil heutiger Forschungsaktivitäten. Ein leistungsfähiges und zukunftsorientiertes Forschungsdatenmanagement kann die Effizienz von Forschung, die langfristige Verfügbarkeit generierter Daten und die Reproduzierbarkeit entsprechender Ergebnisse verbessern. Ein wesentlicher Baustein, wie er in den FAIR-Prinzipien umrissen wird, sind dabei Metadaten. Um dieses Thema aufzugreifen, hat die Helmholtz-Gemeinschaft Deutscher Forschungszentren die Plattform "Helmholtz Metadata Collaboration (HMC)" ins Leben gerufen und mit der Aufgabe betraut, Beratungsangebote, Informationen und Werkzeuge für einen effizienten Umgang mit Metadaten und damit zur Verbesserung der FAIRness von Helmholtz-Forschungsdaten zur Verfügung zu stellen.
Von großer Bedeutung für den Erfolg von HMC ist die Vernetzung in den Communities der Helmholtz-Forschungsbereiche Energie, Erde und Umwelt, Gesundheit, Materie, Information sowie Luft- und Raumfahrt und Verkehr. HMC stützt sich daher auf eine verteilte Struktur von sechs disziplinspezifischen Metadaten-Hubs, die innerhalb ihrer Communities Kompetenzen aktivieren, Ideen fördern und Anforderungen sammeln, um daraus Lösungen für die aktuellen Herausforderungen im Bereich der Metadaten zu entwickeln. Ein mit den technischen Entwicklungen beauftragtes, zentral verankertes Team wirkt unterstützend bei der Implementierung empfohlener Lösungen, Dienste und Werkzeuge mit. Derartige technische Lösungen, allgemein verwendbare Prozesse sowie Angebote zu Schulung, Weiterbildung und Beratung werden fortlaufend erweitert und zur Verfügung gestellt.
HMC ist Teil eines größeren Helmholtz-Förderprogramms, das sich mit unterschiedlichen Herausforderungen der Digitalisierung von Forschung auseinandersetzt, und steht in engem Kontakt mit Helmholtz Open Science. Darüber hinaus sind die Aktivitäten von HMC in den nationalen und internationalen Kontext (z. B. RDA, EOSC, NFDI) und entlang der wissenschaftlichen Disziplinen sowie der Informations- und Datenwissenschaft eingebettet, um die Kompatibilität mit der größeren Wissenschaftsgemeinschaft zu gewährleisten.
Ziel ist neben der Gestaltung einer internen Helmholtz-Plattform, die Etablierung eines öffentlichen, offenen und langfristig verfügbaren Gemeinschaftsdienstes für den Umgang mit Metadaten in der Wissenschaft.

Ein Datensatz gilt als vollständig, wenn neben den reinen Daten (z. B. Messwerte) auch weiterführende Informationen, wie Entstehung und Nutzungslizenz, vorliegen. Dies erfordert neben der vollständigen Erfassung der Daten und Metadaten auch Hilfestelllungen bzw. Instruktionen für die Erfassung und Nutzung sowie einer Infrastruktur zur Speicherung, Publikation und eindeutigen Identifikation. Eine solche "Wertschöpfungskette" setzt sich aus verschiedenartigen Prozessen zusammen, die von Personen in definierten Rollen bearbeitet werden sollten. Auch gilt es, eine Infrastruktur bereitzustellen, die zum einen eine präzise Eingabemaske für den konkreten Fall des Anwenders generiert, aber zum anderen allgemeine Suchanfragen zielgerichtet auf die richtigen Datensätze lenken muss. Und natürlich ist dieses gesamte Konstrukt nicht ohne Regeln und Dokumentation beherrschbar und muss mit einem angepassten Schulungsangebot und einer intuitiven Benutzeroberfläche ausgestattet sein. Das Schulungsangebot richtet sich auch an Personen mit Rollen bzw. zugewiesenen Aufgaben im Datenmanagementsystem um sicherzustellen, dass die Rollen durch die Definition von notwendigen Qualifikationen mit der notwendigen Qualität ausgeführt werden. Eine Plausibilitätsprüfung, die die erwartete Flexibilität des Systems berücksichtigt, garantiert die Konsistenz der Datensätze. In einer der höchsten Ausbaustufen folgt der Plausibilitätsprüfung eine Art Selbstheilungsmechanismus, der dem Anwender einen Datensatz gemäß den Vorgaben vorschlägt oder dessen erneutes Eingreifen gänzlich obsolet macht.
In diesem Beitrag soll der Fokus auf den Rollen und auf der Interaktion mit dem Datenmanagementsystem liegen. Alle notwendigen Qualifikationen und Aufgabenfelder werden dabei den Rollen zugeordnet. Der Vorteil der Unterteilung in Rollen ist es, dass offenbleibt, ob die zusätzlichen Aufgaben durch bestehendes oder neues Personal abgedeckt werden oder ob nicht eine Person mehrere Rollen innehat. Damit kann der konkrete Personalansatz an die eigenen Bedürfnisse angepasst werden.

This article presents a few selected developments and future ideas related to the measurement of (n,γ) data of astrophysical interest at CERN n_TOF. The MC-aided analysis methodology for the use of low-efficiency radiation detectors in time-of-flight neutron-capture measurements is discussed, with particular emphasis on the systematic accuracy. Several recent instrumental advances are also presented, such as the development of total-energy detectors with γ-ray imaging capability for background suppression, and the development of an array of small-volume organic scintillators aimed at exploiting the high instantaneous neutron-flux of EAR2. Finally, astrophysics prospects related to the intermediate i neutron-capture process of nucleosynthesis are discussed in the context of the new NEAR activation area.

Carbides are known for high hardness and corrosion resistance and therefore applicable as protective coatings. C/Si and C/W multilayers (the individual layer thicknesses were between 10 and 20 nm) have been irradiated at room temperature by argon and xenon ions. The energies varied between 40 and 120 keV while the fluences were in the range of 0.07 - 6 × 10¹⁶ ions/cm². The SRIM simulation was applied to have the proper ion energy. The irradiation induced intermixing and carbide (SiC and WC) formation at the interfaces already for the lowest irradiation fluence. The component in-depth distribution has been determined by AES depth profiling which showed that it varied greatly as a function of the irradiation conditions and layer structure. In both material pair the thickness of the produced carbide increased with square root of fluence but the mixing mechanism were different: local spike for C/W and ballistic for C/Si. The mixing efficiency was lower for the C/Si than for the C/ W.

Ziel/Aim:

Targeted Alpha Therapy is a research field of highest interest in specialized radionuclide therapy. In particular the radionuclide actinium-225 provides all necessary physical and chemical properties for a successful clinical application. Although the macropa chelator has shown beneficial properties regarding labeling and stability in vivo as compared with DOTA, the former lacks an imaging counterpart to actinium-225. On the other hand, lanthanum is a perfect surrogate for actinium. The imaging properties of the β+-emitter lanthanum-133 makes it an attractive candidate as a theranostic matched pair to actinium-225. This project aims at the cyclotron-based production of lanthanum-133 with high radionuclidic purity for theranostic purposes.
Methodik/Methods:
Silver discs were filled with [Ba-134]BaCO3 and capped with a platinum foil. One-hour proton irradiations (18.6 MeV, 15 µA) were performed with the HZDR TR-FLEX (ACSI) cyclotron. The powder target was then opened and the dry solid dissolved in HNO3. Separation was carried out with branched DGA cartridge, although other anion-exchange resins are also under investigation. The fractions containing Ba were collected for recovery. Test radiolabeling of macropa-derived PSMA inhibitors previously published by our group was performed in the MBq/nmol range.
Ergebnisse/Results:
Activity yields of 1.8 GBq lanthanum-133 (decay-corrected to EOB) were achieved, with corresponding lanthanum-135 impurities below 0.4 % and no other La radionuclides detected. The product was collected in diluted HCl, with ca. 80 % activity eluted in the second mL. Quantitative radiolabeling was achieved with ligand concentrations down to the µM range.
Schlussfolgerungen/Conclusions:
Lanthanum-133 with high radionuclidic purity was produced for the first time. Considering future medical demands, the scale up to radioactivity amounts that are needed for clinical application purposes could be achieved by increasing the target mass, beam current and irradiation time.

Oscillating oxic/anoxic conditions induces processes at mineral-Kuid
interfaces aeecting the speciation and fate of redox active elements. Such
Kuctuations occur in natural environments (at watershed and delta water
table or in lake water chemocline) and in engineered systems (in oil reDnery
drainage water peatbogs or nuclear waste repository). In presence of aqueous
sulDde or ferrous iron ions, Se, Sb, Pu and Re undergo heterogeneous
reductive precipitation. At the nanosecond scale, selenate adsorption onto
the net pyrite surface is shown by ab-initio computations to proceed via the
formation of a chemical bond between the oxyanion oxygen atom and a
surface Fe atom, weakening the other Se-O bonds and reducing Se atom
oxydation state. At hour-to-day scale, mobile Se(VI), Se(IV), Sb(V), Pu(V) and
Re(VII) oxyanions are shown by strictly anoxic wet chemistry experiments,
XAFS and Mossbauer spectroscopy [1] to be reduced, in presence of
nanosized particles (iron sulDdes (mackinawite or pyrite) [2], oxides
(magnetite) [3] [4] [5] or clays [6]) and aqueous iron (II) or S(-II), to solids (Se(0),
Sb O , PuO , Re0 , ReS or Re(0)) or to highly speciDc Sb(III) [7] and Pu(III) [8]
sorption complexes. STEM-HAADF microscopy demonstrates the formation of
Se(0) trigonal gray selenium nanowires after co-adsorption of selenate and
ferrous iron ions on 10 nm nanomagnetite [4], a reaction which results from a
complex, kinetically controlled interplay of intermediate reduced surface
complexes and transport of these reduced species to the tip of the nanowires.
These processes in far-from-equilibrium conditions are of prime importance
in the safety assessment of petroleum industry and geological repositories, as
well as in the bioavailability to crop or human beings.
[1] Charlet et al., 2022, J. Mat. Res. DOI: 10.1557/s43578-022-00823-8 [2] Son et
al., 2022, Geochim. Cosmochim. Acta 338 : 220–228. [3] Goberna-Feron et al.,
2021, Env. Sci. & Tech. 55, 3021−3031. [4] Poulain et al., 2022, Env. Sci. & Tech 56
: 14817-14827 [5] Wang et al., 2022, Environ. Sci. Technol. 2022, 56, 9. [6]
Charlet et al., Geochim. Cosmochim. Acta 71: 5731-49. [7] Kirsch et al., 2008,
Mineral Mag, 72, 185-189. [8] Kirsch et al, 2011, Environ. Sci. Technol. 45 :
7267–7274

The actinides (An) are located at the bottom of the periodic table. These elements are exclusively radioactive, highly chemo-toxic, and play an important role in chemical engineering and environmental science related to the nuclear industry or nuclear waste repositories. In contrast to the strongly shielded 4f electrons of the lanthanides, 5f electrons of particularly the early An are found to participate in bonding, e.g. to organic ligands. Another characteristic of the An is their huge variety of possible oxidation states, typically ranging from +II to +VII for early actinides, making their chemistry complex but interesting. A suitable approach to explore fundamental physico-chemical properties of the actinides is to study series
of isostructural An compounds in which the An is in the same oxidation state. Observed changes in e.g. the binding situation or magnetic effects among the An series may deliver insight into their unique electronic properties mainly originating from the f-electrons. A question still remaining in the field of An chemistry is the degree of “covalency” in compounds across the actinide series, which may be addressed by systematic studies on series of An compounds, including transuranium (TRU) elements.
We investigate the coordination chemistry of low-valent actinides using organic N-, O-, or S-donor ligands. Information on covalency trends as well as mutual ligand influences can be obtained by the analysis of solid-state structures derived by SC-XRD in combination with quantum chemical calculations (QCC) and high-energy-resolution fluorescence detection X-ray absorption near edge spectroscopy (HERFD-XANES). In solution, NMR spectroscopy permits to draw conclusions about the complex speciation in solution, the intrinsic magnetic properties of the actinides, or subtle changes in covalency in the ligand-actinide-bonding.

99Tc is a fission product with a long half-life of 2.14 × 105 years. Its migration and bioavailability strongly depend on its oxidation state and speciation in aqueous solution. Under oxidizing conditions, Tc mainly exists as pertechnetate, TcVIIO4, a highly water-soluble anion with s negligible sorption to most minerals. Under reducing conditions, TcIV prevails, whose main species, TcO2 xH2O, is a polymer of low solubility. As the presence of reductants like Fe2+ in the near-field of a nuclear waste repository is expected due to canister corrosion, several studies consider 99TcVII reductive immobilization by minerals containing reductant moieties, such as magnetite (FeIIFe2IIIO4) or mackinawite (FeS) [1]

Pyrite (cubic FeS2) is a redox sensitive sulfide mineral that has been identified as a good sorbent for TcVII from soil and groundwater [2]. Under repository conditions, both pyrite and marcasite (orthorhombic FeS2) are expected to form by corrosion processes and microbial interaction [3]. Moreover, both iron sulfides are also accessory minerals in granitic and argillaceous rocks. Therefore, reliable data on 99TcVII retention by both minerals and their mixtures is relevant for the safe disposal of nuclear waste.

We have studied the Tc retention by pure pyrite and by a mixture of marcasite and pyrite (60:40) using a combination of batch experiments and spectroscopy (Raman microscopy, X-ray photoelectron spectroscopy and X-ray absorption spectroscopy) at pH 6 and 10. [4, 5]. We confirm the 99TcVII reduction and subsequent 99TcIV retention on the mineral surfaces and shed new light on different retention mechanisms for pyrite and marcasite at pH 10.

We acknowledge funding from the German Federal Ministry of Economic Affairs and Energy (BMWi) for VESPA II project (02E11607B), and from the German Federal Ministry of Education and Research (BMBF) for the NukSiFutur TecRad young investigator group (02NUK072).

[1] Yalçıntaş E, et al. 2016 Dalton Trans. 45 17874
[2] Huo L, et al. 2017 Chemosphere 174 456
[3] Roberts W M B, et al. 1969 Mineralium Deposita 4 18
[4] Rodríguez D M, et al. 2020 Environ. Sci. Technol. 54 2678
[5] Rodríguez D M, et al. 2021 Chemosphere 281 130904

Purpose: In magnetic resonance imaging-integrated proton therapy (MRiPT), the magnetic field-dependent change in the dosage of ionization chambers is considered by the correction factor k ⃗ B,M,Q, which needs to be determined experimentally or computed via Monte Carlo (MC) simulations. In this study, k ⃗B,M,Q was both measured and simulated with high accuracy for a plane-parallel ionization chamber at different clinical relevant proton energies andmagnetic field strengths.

Material&Methods: The dose-response of the Advanced Markus chamber (TM34045, PTW, Freiburg, Germany) irradiated with homogeneous 10×10 cm2 mono-energetic fields, using 103.3, 128.4, 153.1, 223.1, and 252.7 MeV proton beams was measured in a water phantom placed in the magnetic field (MF) of an electromagnet with MF strengths of 0.32, 0.5, and 1 T. The detector was positioned at a depth of 2 g/cm2, with chamber electrodes
parallel to the MF lines and perpendicular to the proton beam incidence direction. The measurements were compared with TOPAS MC simulations utilizing COMSOL-calculated 0.32, 0.5, and 1 T MF maps of the electromagnet. k ⃗B,M,Q was calculated for the measurements for all energies and MF strengths based on the equation: k ⃗B,M,Q = MQ/M ⃗ BQ , where MQ and M ⃗ BQ were the temperature and air-pressure corrected detector readings with and without the MF, respectively. MC-based correction factors were determined as k ⃗B,M,Q = Ddet/D ⃗ Bdet , where Ddet and D ⃗ Bdet were the doses deposited in the air cavity of the ionization chamber model without and
with the MF, respectively.

Results: The detector showed a reduced dose-response for all measured energies and MF strengths, resulting in experimentally determined k ⃗B,M,Q values larger than unity. k ⃗B,M,Q increased with proton energy and MF strength, except for 0.5 T and 252.7 MeV. Overall, k ⃗B,M,Q ranged between 1.0065 and 1.0205 for all energies and MF strengths examined and the strongest dependence on energy was observed at 1 T. The MC simulated k ⃗B,M,Q values for all MF strengths showed a good agreement with the experimentally determined correction factors with a maximum deviation of 0.6% and trends within their standard deviations.

Conclusion: For the first time, measurements and simulations were compared for an Advanced Markus chamber for proton dosimetry within MFs. For all MF strengths, there was a good agreement of k ⃗B,M,Q between experimentally determined and MC calculated values in this study. By benchmarking the MC code for the calculation of k ⃗B,M,Q it can be used to calculate k ⃗B,M,Q for various ionization chamber models, MF strengths and proton energies to generate the data needed for a dosimetry protocol for MRiPT.

Inverse gas chromatography (IGC) has become a popular technique for the analysis of particulate materials. By injecting certain probe molecules through a column containing the sample as the stationary phase and measuring the retention time of said probe molecules, information on a range of different physicochemical properties, such as surface energy or Hansen-solubility parameters can be obtained. A proper understanding of these physicochemical properties is significant for many industrial processes (e.g. formulation, miscibility of polymer blends, agglomeration), as said processes are often driven by surface properties.
Though, IGC analysis has many benefits and is widely used nowadays, the comparability of results that are reported and measured by different operators using different IGC devices has not been investigated yet. Therefore, a round robin test was conducted, where eight organisations analysed two standard materials, silica and lactose, according to a jointly defined protocol using IGC devices that either have a valve-based or a syringe-based dosing system. The results are evaluated based on standard IGC theories and the same mathematical operations are applied to all datasets in order to obtain the specific retention volume and the dispersive surface energy component for the two materials. The resulting values of the calculated parameters vary quite significantly, which is a rather unexpected and a very unpleasant finding for this highly sensitive analytical device. Measurements that are conducted individually by the same operator on the same IGC device report similar results, whereas results obtained by different operators with different types of IGC devices are significantly different. Potential factors for the differences, such as the injected quantity of the probe molecules, are presented and discussed.
This round robin test therefore raises some questions on the reproducibility of results obtained via inverse gas chromatography. Furthermore, it demonstrates the need for a standard powder and protocol in order to have a common ground for an objective judgment of results.

⁷⁹Se with a half-life of 3.27 × 10⁵ y [1] is presently considered as a key mobile radionuclide for the disposal of spent fuel and high-level waste [2]. The solubility of selenium (Se) is largely controlled by its oxidation state, and hence depends on the redox conditions present in soils, sediments, bedrock and aquifers. The −II, −I, and 0 oxidation states are commonly predominant in “reducing” anoxic environments, while the +IV and +VI states predominate in more “oxidizing” environments [2]. The interactions with Fe(II) and S(–II)-bearing redox active solids- mediate the oxido-reduction kinetics of Se oxyanions, playing an important role in the control of Se speciation [3]. Regarding Se(VI), it was found to be metastable (far from thermodynamic equilibrium) and potentially selenium could coexist in different oxidation states in the Callovo-Oxfordian pore waters [4]. The reduction of Se(VI) by magnetite, much slower than for Se(IV), include different steps (adsorption, reduction to Se(IV), and further reduction to less soluble Se phases: Se⁰(s), FeSe₂(s), FeSe(s)), each of them imposing a kinetic barrier for the whole reduction process. At present it is not clear whether the Se(VI) initial adsorption or its reduction to Se(IV) are concomitant or not, and extra work needs to be done in this direction to establish the reduction pathway. Furthermore, little is known about the potential competition with ubiquitous ions in porewater such as carbonate or sulfate and especially about their capability to limit the contact of selenate molecules with the Fe(II)-bearing solids, and thus to inhibit the electron transfer.
The redox reactions Se(VI) with magnetite and pyrite under neutral pH conditions will be deciphered at both macroscopic and molecular levels by combining batch sorption studies and advanced spectroscopic techniques (XAS, XPS). In addition, the influence of sulfate ions will be investigated.

[1] Jörg, G. et al., Appl. Radiat. Isot. (2010), 68 (12), 2339−2351.
[2] Fernandez-Martinez, A. and Charlet, L., Rev. Environ. Sci. Biotechnol. (2009), 8, 81–110.
[3] Scheinost, A. C. et al., J Contam Hydrol (2008), 102, 228-45.
[4] Savoye, S. et al., Appl. Geochemistry (2021), 128, 104932.

A good understanding of interlayer coupling is crucial to designing novel van der Waals heterostructures. The present study examines two types of multilayer heterostructures based on 2D transition-metal dichalcogenides (TMDCs). ABC or ABBC stackings consist of three layers (A - MoS2, B - MoSe2, C - WSe2). By doing so, MoSe2 spatially separates the electron layer (MoS2) from the hole layer (WSe2). TMDCs are stacked in one of three ways in the second type: ABA, ABBA, or AABAA. Depending on stoichiometry, the electrons or holes are localized in the middle part of the heterostructure or delocalized to the outer layers. The majority of the materials studied here are direct gap semiconductors with transitions at K. A type II band alignment is found in all of them. We predict that indirect excitons will be evident in all materials.

Magnetite is arguably the most relevant corrosion product when steel canisters corrode anaerobically in future deep geological radioactive waste repositories. 99Tc is of great concern for the safety assessment of these repositories, due to its long half-life (t1/2 = 2.1∙105 years). Under oxidative conditions Tc forms an anionic species, pertechnetate (TcVIIO4−), which is highly mobile due to its high solubility and weak sorption on most minerals. Under anaerobic conditions, TcVII can be reduced to TcIV, which strongly interacts with minerals by sorption, structural incorporation and formation of insoluble oxides like TcO2. FeII-minerals, and among them magnetite, have shown to effectively reduce pertechnetate and play thereby a critical role.[1]
Previous studies by Yalcintas et al.[2] suggested that TcVII 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. In contrast at pH 6-7, the reduction resulted in a partial incorporation of TcIV in octahedral Fe-sites of magnetite.[3] Our initial working hypothesis was that the incorporation is linked to magnetite solubility. To test this, we investigated Tc reaction with magnetite nanoparticles in a wide range of pH (3 - 13), reaction time (1 - 210 days) and varied initial Tc concentration (μM - mM).
To characterize the oxidation state of Tc and its molecular structure, we employed a range of methods including Tc K-edge (21 044 eV) X-ray absorption spectroscopy (XAS) at the Rossendorf Beamline at the ESRF in Grenoble. XANES analysis revealed the predominance of TcIV at all evaluated pH values, supporting that reductive Tc immobilization is the main retention mechanism. EXAFS analysis suggests that two species are formed. At pH 5 and short equilibration times, Tc is retained by forming TcO2∙xH2O polymers, showing the recently reported “zig-zag-chain” structure[4]. In contrast, TcIV substituted magnetite forms within a few hours at pH 7 and 10. At pH 5, it forms only after a few days with the proportion of the Tc-magnetite phase growing at the expense of the TcO2∙xH2O polymers. Therefore, across the pH range 5 to 10, Tc-magnetite seems to be the thermodynamically preferred phase. The initial formation of TcO2∙xH2O polymers at low pH seems to be linked to the release of Fe2+ from magnetite (reductive maghemitization)[5], which leads to substantial Fe2+ concentrations in solution due to the lacking re-adsorption at this pH. The mechanism behind the fast incorporation of TcIV in magnetite, now observed for the first time within days across a wide pH range, remains unsolved. The structural stability of cubic spinel magnetite and the absence of strong evidence for structural uptake of other elements with similar coordination number and ionic
Fig. 1: Schematic process of the interaction of pertechnetate (TcVIIO4−) with magnetite radius like Co, Ni and other 3d metals, point to a complex coupled sorption/redox/incorporation mechanism.
In order to better understand the Tc incorporation into by magnetite, we also conducted density functional theory (DFT) calculations using the PBE[6] functional implemented in AMS/BAND 2022[7], with full optimization of atomic coordinates and lattice parameters. For the finite structures, solvent effects were included with the COSMO[8]. Three charge compensation mechanisms were considered. The calculated incorporation energies and comparison of the Tc coordination structure with experimental EXAFS data indicate that Tc incorporation is most likely to occur either by substitution of two octahedral FeIII sites with a TcIV/FeII pair (Fig. 2, left), or by substitution of two FeII sites with a single TcIV, thus forming a vacancy (Fig. 2, right). The last mechanism, where three TcIV replace four octahedral FeIII (Fig. 2, center), could be excluded.

Uranium (U) mining and milling activities, as well as mineral processing plants, raise environmental concerns due to the possible release of radioactive and other potentially toxic elements. To understand their fate in the environment and evaluate their potential impact, the main scientific challenge calls for identifying their solubility, mobility and bioavailability in the environment. Around former U mining and processing plants, wetlands prove to be specific zones with significant amounts of U. This is partly explained by the reduction of the mobile U(VI) into U(IV) due to strongly reducing conditions related to the microbial activity and/or by complexation with the organic matter occurring with high concentrations in wetlands.
At the center of the ancient mining district of Lachaux in France (45.994°N, 3.596°E), the site of Rophin (within the ZATU: Uranium Working Zone = Long Term Socio-Ecological Research Tool of CNRS, Fig.1.a) is characterized by a wetland area with large U concentrations up to 16 g.kg-1 of dry mass of soil [1]. Several cross-analyses indicate that U was transported in particulate forms into the wetland during the exploitation of U(VI) phosphate minerals [1]. The Rophin site therefore provides the opportunity to study the stability of these U minerals over almost 70 years in a non-manipulated wetland since the closure of the mine. In this context, the main challenge is to describe the behavior of U (and decay products of interest) in the wetland using a predictive model that combines transport and chemical speciation. The overall adopted scientific approach is to propose a mechanistic description of the mobility of these elements, from the molecular scale (speciation) to in natura behavior (lability), by coupling field investigations and laboratory experiments.
A simplified three-layer model describes the soil profile of the Rophin wetland, with variable U concentrations and specific physico-chemical soil properties (Fig.1.b). Analyses carried out by X-absorption spectroscopy on in natura soil samples mainly indicate the presence of an adsorbed form of U(IV) in the highly contaminated layer, while both U(IV) and U(VI) are identified in the organically rich part at the surface. Additional SEM-EDX and μ-XRF mapping measurements also indicate that U minerals transported into the wetland were partially dissolved and re-adsorbed in soils.
The objective was to determine which fraction is finally labile, i.e. the fraction that is adsorbed and whose resupply in solution is rapid. This was assessed by desorption experiments under representative site conditions with two complementary approaches [2,3]. Overall, the available fraction is very low (3 to 10 % for the highly contaminated layer and less than 1% for the surface layer) and is characterized by distribution coefficient (Kd) values of the order of 102 L.kg-1. These results were then compared with field data using DGT/DET techniques coupling (Diffusive Gradient in Thin-films/ Diffusive Equilibrium in Thin-Films) [4]. We found an available fraction in the whitish zone, which is rapidly eliminated with time, whereas a labile U fraction is almost undetectable in the surface layer. Combined with time-dependent deployment DGT/DET coupling, results highlighted the predominance of a kinetic parameter and thus, the expected key role of the organic matter in the U mobile behavior in the surface soil.
This study provides access to the input data (labile quantity and (Kd) values) for the establishment of a reactive transport model at the scale of the Rophin mining-affected wetland, but also allows to determine significant information on U interactions in soils. As such, this multi-scale and interdisciplinary study contributes to the improvement of the global understanding of U migration and fate in wetland soils.

The EU-funded H2020 project FineFuture successfully tackled the recovery of fine particles for an increased resource efficiency, and an improved pneumatic flotation technology was one of the key outcomes with the very realistic option of bringing it to industry. Though being potentially suitable for secondary material as well, the focus was on primary ores such as manganese, magnesite or iron. Nevertheless, feeding the pneumatic flotation cell with tailings material was also conducted in some experiments, and resulted in satisfactory recovery rates of the target elements.
However, due to resource depletion and the paradigm of climate-neutrality economy needs to be transformed into a more circular one, making use of sustainable value chains and keeping resources longer in the loop. Therefore, the research goes further with the project FINEST, and tackles finest particulate matter of anthropogenic origin such as shredder waste from WEEE or cars, fine ashes, etc. The target elements considered from these waste materials are microplastics, mineral additives and disperse metals. The idea is to combine different waste streams by blending them in order to stimulate improved process behavior, and an increase of the recovery rate of valuable elements such as copper, iron etc. Most of the waste streams considered in FINEST are currently not utilized, resulting in a great benefit for circularity and simultaneously reducing environmental harm through the reduction of the amount of material that needs to be disposed of. The unavoidable residuals are treated in a way that all compounds are inert, and allow for a safe disposal.
The project is largely oriented towards transdisciplinarity, and the FINEST Research School is additionally embedded into the research project. The school aims to train postgraduate students in a structured way to allow them to become transfer experts in resource management. While offering training at industry during the PhD phase, the school follows the concept of “transfer via brains“, which means to aim for an excellent education of the PhD’s, who will enter industry afterwards with the goal to manage a transformation from inside into more circular thinking.

One of the biggest threats to humankind and the planet is the climate change that is propelled by excessive carbon dioxide emissions mainly being generated through combustion of fossil fuels in industry, transportation, building, etc. In order to keep the increase of the global temperature below 2K compared to pre-industrialization level, climate-neutrality becomes more and more important for nations, societies, regions, cities and companies in response to this development. In addition, a sustainable circular economy that keeps material streams in the loop as far as possible contributes to this goal. However, the transformation of the society and economy towards more sustainability requires a vast amount of resources in itself. Though resource depletion may actually not really be a challenge for many elements, in particular those elements that are required for high technology applications such as batteries for electro mobility, wind turbines, etc. are scarce, and might become even scarcer in view of the pursued expansion of sustainable and climate-neutral technologies. This is the case for example for lithium as an important raw material for batteries, but also for rare earth elements like neodymium that are required for magnets in wind turbines.
In addition, the extraction of primary ores becomes also more and more difficult due to decreasing concentrations of valuable minerals in the ore bodies in turn leading to even larger amounts of mining waste compared to the recovery of the target element. Often, a considerable part of the minerals cannot be recovered as the particles are too fine for the conventional processing technologies currently in place. In order to tackle this challenge, the Horizon 2020 project FineFuture was conducted in which experts from all over Europe collaborated to find ways to unlock the fine-grained mineral and critical raw materials resources through innovative technologies and concepts for fine particle flotation. Beside advancements in the fundamental understanding of the underlying processes in the interphases as well as the modelling of the particle flows, the pneumatic flotation technology was improved through a new design and more suitable selection of frothers and collectors resulting in higher recovery rates for certain minerals such as manganese and magnesite.
Current research going on is intended to utilize and manage finest particulate matters of anthropogenic origin. The types of finest materials considered in the FINEST project jointly conducted by HZB, HZDR, KIT, UFZ, TUBAF and UG are microplastics, mineral additives and disperse metals, which are found in waste streams such as plastics waste, external thermal insulation composite systems, light-weight shredder fractions (e.g. from electronic scrap and/or automotive recycling), etc.
The sub-project FINEST Microplastics deals with biotechnological solutions for the utilization of the microplastics fraction. Biocatalysts are to convert the plastics fraction to yield specific mono-/oligomers for product synthesis, microbial biomass amenable to further microbial fermentation and inert residues for a safe deposition.
The sub-project FINEST Mineral Additives is dedicated to finest minerals with the aim to recover mineral additives like fillers, flame retardants, pigments or heat stabilizers during chemical recycling processes. By means of pyrolysis, part of the mineral additives from external thermal insulation composite systems shall be recovered while non-separable additives shall be safely stored in recycling cement and low-grade plastics may be utilized by feeding them back into the plastics fraction.
The sub-project FINEST Disperse Metals targets at a blending and agglomeration of complex residues composing of finest particles. The pellets produced from the blended waste shall be further processed through thermal treatment in a furnace aiming at the recovery of the metallic content. The remaining residues shall be disposed of in an inert form.
These innovative approaches need to be assessed in terms of their technological, ecological, economic, and social impact in comparison to the conventional processing, but also in comparison to a mere storage, which is regularly the case for the finest particle waste up-to-date.
Finally, the transdisciplinary approach of the project shall enable a transformation of industry through “transfer via brains” in order to contribute to a circular economy and enable more sustainable value chains.

PhD Thesis:

Experimental characterization of four-magnon scattering processes in ferromagnetic
conduits

Dendritic cells (DCs) play a key role in the orchestration of antitumor immunity. Activated DCs efficiently enhance antitumor effects mediated by natural killer cells and T lymphocytes. Conversely, tolerogenic DCs essentially contribute to an immunosuppressive tumor microenvironment. Thus, DCs can profoundly influence tumor progression and clinical outcome of tumor patients. To gain novel insights into the role of human DCs in pancreatic ductal adenocarcinoma (PDAC), we explored the frequency, spatial organization, and clinical significance of conventional DCs type 1 (cDC1s) and type 2 (cDC2s) and plasmacytoid DCs (pDCs) in primary PDAC tissues. A higher density of whole tumor area (WTA)- and tumor stroma (TS)-infiltrating cDC1s was significantly associated with better disease-free survival (DFS). In addition, an increased frequency of intraepithelial tumor-infiltrating cDC2s was linked to better DFS and overall survival (OS). Furthermore, an increased density of WTA- and TS-infiltrating pDCs tended to improve DFS. Moreover, a higher frequency of WTA- and TS-infiltrating cDC1s and pDCs emerged as an independent prognostic factor for better DFS and OS. These findings indicate that tumor-infiltrating DCs can significantly influence the clinical outcome of PDAC patients and may contribute to the design of novel treatment options that target PDAC-infiltrating DCs.

The field of autonomous motile micro/nanomotors that can propel in the liquid environment strongly benefits from the use of magnetic materials, winning in the long-time deterministic locomotion and controllability of such microscopic objects. This chapter reviews the applications of curved magnetic micro/nanostructures to be employed for biomedical and environmental applications. In this respect, after introducing the basic principle and examples of the self-propelled micro-objects, we further focus here on the locomotion of the magnetically decorated microscopic objects and the influence of their shape on the character and pattern of the motion. Namely, we consider the properties of magnetically capped spherical Janus particles, rod-like, tubular, and other asymmetric objects, e.g., microhelices, with magnetic functionalization. Finally, we describe the applications of such magnetic objects in environmental remediation, biosensing and drug delivery, etc.

Sorption of hazardous metals on clay minerals is a key process contributing to the safety of repository sys-tems. The existence of high- and low-affinity adsorption sites on smectites edge surfaces, responsible for met-als uptake has been revealed in previous studies [1,2]. The exact molecular nature of these adsorption sites has not been fully resolved.
Similar to the adsorption of Ni2+ on montmorillonite [1], Ni2+ on saponite shows a non-linear adsorption be-havior, which, by analogy, suggests the existence of strong and weak sorption sites (Fig.1). Based on the sorp-tion isotherms obtained on saponite, self-oriented clay films were prepared, with Ni loadings corresponding to adsorption dominated by strong and weak sites, and then polarized Ni K-edge EXAFS spectra were recorded.
For samples with low Ni2+ loadings (below 4 mmol/kg), P-EXAFS results confirmed the existence of strong sorption sites. An increase of Ni loading (up to 40 mmol/kg) leads to decreasing in Ni-Mg bond length and an increase in Ni-Si coordination number, indicating the formation of a secondary phase. The exact structure of the new phase is still under evaluation, but this solid phase will certainly mask Ni sorbed to weak sites.
The molecular structure of cations adsorbed on the water-edge interfaces for the most stable surfaces was modeled using ab initio MD, which enable us to obtain a theoretical estimation of the free energies of Zn-Ni cation exchange reactions between weak and strong sites on (100) and (130) edges of saponite. Theoretical values obtained for Zn-Ni exchange are equal to 13.5±0.4 and 5.50±0.03 kJ/mol for (100) and (130) surfaces, respectively. These results are in a good agreement with experimental results for montmorillonite (9.1 kJ/mol) – a trustworthy proxy and suggest a stronger affinity of Zn to strong sites than Ni.

The geochemical behavior of antimony (Sb), a priority pollutant of increasing concern, is closely linked to the redox cycling of iron (Fe). Microbial reduction of Fe(III) oxides and production of soluble Fe(II) under anoxic conditions has been shown to release co-associated Sb (occurring as Sb(V) and/or Sb(III)). In redox-dynamic environments, Fe(II) can be re-oxidized and precipitate as Fe(III) oxides. The extent to which these processes affect Sb mobility, however, is still poorly understood and likely depends on an array of factors such as pH, Sb species and the nature of the newly formed Fe(III) oxides.

Here, we investigated the effect of Fe(II) oxidation on Sb sequestration and on the mineralogy of the resulting Fe(III) precipitates in a pH range typical of Sb-contaminated systems (i.e. pH 6, 6.5, and 7). To initiate the oxidation reaction, 0.5 mmol L-1 Fe(II) was added to an oxygen-saturated electrolyte solution containing 0 – 50 µmol L-1 Sb(V) or Sb(III). Changes in aqueous Sb and Fe(II) were tracked during the experiments, and solid phase samples were collected at the end of the oxidation reaction for characterization by diffractometric, spectroscopic, and microscopic techniques.

Iron(II) oxidation kinetics and Sb sequestration were a function of pH and Sb species, with Sb(III) retarding the oxidation reaction. In the absence of Sb, Fe K-edge extended X-ray absorption fine structure (EXAFS) analysis revealed lepidocrocite as the only solid-phase product. In presence of Sb, feroxyhyte and goethite formed instead of lepidocrocite. The shift in Fe oxide assemblage was more pronounced when Sb was present as Sb(V) and at a lower pH. Antimony EXAFS analyses showed an almost complete oxidation of Sb(III) to Sb(V) followed by the incorporation of Sb(V) into the structure of the Fe oxides precipitates.

Our results allow for a better understanding of Sb geochemistry in redox-dynamic environments as they demonstrate that Sb itself can influence the pathways of secondary Fe oxide formation. Our study also provides important information for the development of adequate remediation practices of Sb-contaminated soils and sediments that are subject to changes in redox conditions as induced by flooding or waterlogging.

Post-irradiation annealing of neutron-irradiated reactor pressure vessel steels is a matter of both technical and scientific interest. Small-angle neutron scattering (SANS), while being sensitive to nm-sized irradiation-induced solute-atom clusters, provides macroscopically representative and statistically reliable measures of cluster volume fraction, number density and size. In the present study, SANS was applied to uncover the size distribution of clusters in as-irradiated samples of a VVER-1000 weld and their gradual dissolution as function of the post-irradiation annealing temperature. The same samples were used to measure Vickers hardness. The results are consistent with Mn-Ni-Si-rich clusters of less than 2 nm radius to be the dominant source of both scattering and hardening. Annealing gave rise to small but significant partial recovery at 350 °C and almost complete recovery at 475 °C. The dispersed-barrier hardening model was applied to bridge the gap between the characteristics of nano-features and macro-hardness.

We report the manifestation of field-induced Berezinskii-Kosterlitz-Thouless (BKT) correlations in the weakly coupled spin-1/2 Heisenberg layers of the molecular-based bulk material [Cu(pz)₂(2-HOpy]₂)(PF₆)₂. At zero field, a transition to long-range order occurs at 1.38 K, caused by a weak intrinsic easy-plane anisotropy and an interlayer exchange of J´/k_B ≈ 1 mK. Because of the moderate intralayer exchange coupling of J/k_B = 6.8 K, the application of laboratory magnetic fields induces a substantial XY anisotropy of the spin correlations. Crucially, this provides a significant BKT regime, as the tiny interlayer exchange J0 only induces 3D correlations upon close approach to the BKT transition with its exponential growth in the spin-correlation length. We employ nuclear magnetic resonance measurements to probe the spin correlations that determine the critical temperatures of the BKT transition as well as that of the onset of long-range order. Further, we perform stochastic series expansion quantum Monte Carlo simulations based on the experimentally determined model parameters. Finite-size scaling of the in-plane spin stiffness yields excellent agreement of critical temperatures between theory and experiment, providing clear evidence that the nonmonotonic magnetic phase diagram of [Cu(pz)₂(2-HOpy]₂)(PF₆)₂ is determined by the field-tuned XY anisotropy and the concomitant BKT physics.

The microbial reduction of U(VI) to U(IV) can decrease the mobility of U contaminants in the environment and may have a significant impact on the safety of a nuclear waste repository, as well as, the potential to serve as a component in bioremediation strategies for U-contaminated environments. In this study, we show significant differences in the reduction mechanisms for iron- and sulfate-reducing bacteria, highlighting the importance of investigating microbe-uranium interaction of different bacterial genera. Moreover, we introduce the use of artificial bio-constructs to study U reduction by microbial communities to gain insights into the complex interactions in a multi-species environment. To gain molecular process understanding regarding microbial U reduction Desulfosporosinus and Desulfitobacterium spp. were chosen as important representatives of sulfate- and iron-reducing bacteria in anaerobic environments. Furthermore, their U reduction capabilities were investigated using artificial bio-constructs with different other microbial species.
Time-dependent experiments of pure cultures in bicarbonate buffer (30 mM, 100 µM U(VI), 10 mM lactate) showed a decrease of U concentrations in the supernatant of Desulfitobacterium sp. G1-2, whereas no changes occurred for Desulfosporosinus hippei DSM 8344T. In contrast, in artificial Opalinus Clay pore water (100 µM U(VI), pH 5.5, 10 mM lactate) up to 80% of the radionuclide got removed by both microorganisms. UV/Vis studies verified the reduction of U(VI) to U(IV) in the cell pellets. STEM-EDXX revealed the presence of two different U-containing aggregates inside the cells of Desulfitobacterium sp. G1-2, while cells of Desulfosporosinus hippei DSM 8344T showed almost no U uptake but U-aggregates on the cell surface.
First experiments with artificial bio-constructs that were formed from different bacterial genera using polyelectrolyte-controlled aggregation showed a promising U reduction capacity. Such artificial biostructures, in the form of aggregates or artificial biofilms, have a potential in investigating the complex interactions in multi-species environments and to utilize beneficial microbes in remediation strategies, even if they do not form biofilms themselves.

Understanding and quantifying the chemistry of actinides with strong complexing ligands found in the environment is of key importance for predicting their mobility in the subsurface, especially with respect to the safety of high-level nuclear waste disposal. Phosphate ligands are present in the environment as they originate from the natural decomposition or microbially mediated solubilization processes of phosphate containing rocks and minerals. They can also be produced by anthropogenic activities such as fertilizers spread on the fields or phosphate-based detergents. Furthermore, phosphates are constituents of glasses and ceramics that may be used to immobilize high-level wastes.

Current thermodynamic databases contain very little data on actinide-phosphate complexes [1]. For the trivalent actinide curium, a recent study combining luminescence spectroscopy, thermodynamics, and quantum chemical (QC) calculations could unambiguously establish the formation of 1:1 and 1:2 phosphate complexes with the H₂PO₄⁻ ligand [2]. Complexation constants for both species were derived and extrapolated to standard conditions using the specific ion interaction theory. By combining the data obtained in the luminescence spectroscopic investigations, such as the crystal-field splitting of the emitting excited states and the luminescence lifetimes, with quantum chemical calculations, the coordination number of the complexes could be determined. At room temperature, both the 1:1 and 1:2 complexes are coordinated by 9 ligands. At elevated temperature, only the 1:1 complex retains a coordination number of 9, while one water molecule is released from the 1:2 complex, thereby reducing its coordination number to 8.

In this study, a similar combined experimental and computational approach will be applied to bridge the gaps in the databases for neptunium(V)-phosphate complexes. The complexation reaction will be studied with UV-vis and infrared (IR) spectroscopies at varying ionic strengths and temperatures under acidic pH conditions. Thereby, complexation constants and thermodynamic parameters for Np(V) aqua ion with phosphate can be derived for the formed Np(V)-H₂PO₄⁻ complex(es) (Figure 1). However, the experimental data alone, do neither hold information on the coordination of phosphate to the NpO₂⁺ cation (mono or bidentate binding), nor on the overall coordination number. This calls for relativistic QC calculations that will help characterizing the stoichiometry and geometries of the complexes. Indeed, QC methods can quantify the relative stability of these structures as well as the complexation strengths with aqueous phosphate through potential change of the coordination number with increasing temperature. The calculated vibrational frequency supports the assignment of bands within the measured IR spectra. In addition, the electronic structures at fundamental and excited states will be computed in order to predict the absorption bands of Np(V) – phosphate complexes in acidic solution. Ultimately, by using the quantum theory of atoms in molecules (QTAIM), the topology of the neptunyl-ligand bonds can be scrutinized to i) discuss the evolution of its character as additional phosphate ligands bind neptunyl and ii) to complement the evolution of the complexation constants determined experimentally.

[1] Grenthe, I. Gaona, X. Plyasunov, A. Rao, L. Runde, W.H. Grambow, B. Konings, R.J.M. Smith, A.L. Moore, E.E. (2020). Second Update on the Chemical Thermodynamics of Uranium, Neptunium, Plutonium, Americium and Technetium. Chemical Thermodynamics Volume 14, OECD Publications, Paris.
[2] Huittinen, N., Jessat, I., Réal, F., Vallet, V., Starke, S., Eibl, M., and Jordan, N. (2021). Revisiting the complexation of Cm(III) with aqueous phosphates: new insights from luminescence spectroscopy and ab initio simulations. Inorg. Chem. 60:10656−10673.

Preface
Selected publications
Statistics (Publications and patents, Concluded scientific degrees; Appointments and honors; Invited conference contributions, colloquia, lectures and talks; Conferences, workshops, colloquia and seminars; Exchange of researchers; Projects)
Doctoral training programme
Experimental equipment
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Organization chart and personnel

The experimental investigation of matter under extreme densities and temperatures, as in astrophysical objects and nuclear fusion applications, constitutes one of the most active frontiers at the interface of material science, plasma physics, and engineering. The central obstacle is given by the rigorous interpretation of the experimental results, as even the diagnosis of basic parameters like the temperature T is rendered difficult at these extreme conditions. Here, we present a simple, approximation-free method [1,2] to extract the temperature of arbitrarily complex materials in thermal equilibrium from X-ray Thomson scattering experiments, without the need for any simulations or an explicit deconvolution. Our paradigm can be readily implemented at modern facilities and corresponding experiments will have a profound impact on our understanding of warm dense matter and beyond, and open up a variety of appealing possibilities in the context of thermonuclear fusion, laboratory astrophysics, and related disciplines.

[1] T. Dornheim, M. Böhme, D. Kraus, T. Döppner, Th. Preston, Zh. Moldabekov, and J. Vorberger, Accurate temperature diagnostics for matter under extreme conditions, Nature Comm. 13, 7911 (2022)
[2] T. Dornheim, M. Böhme, D. Chapman, D. Kraus, T. Döppner, Th. Preston, Zh. Moldabekov, and J. Vorberger, Temperature analysis of X-ray Thomson scattering data, arXiv:2212.10510

Studying the toxicity of chemical compounds using isothermal microcalorimetry (IMC), which monitors the metabolic heat from living microorganisms, is a rapidly expanding field. The unprecedented sensitivity of IMC is particularly attractive for studies at low levels of stressors, where lethality-based data are inadequate. We have revealed via IMC the effect of low dose rates from radioactive β−-decay on bacterial metabolism. The low dose rate regime (<400 µGyh−1) is typical of radioactively contaminated environmental sites, where chemical toxicity and radioactivity-mediated effects coexist without a predominance or specific characteristic of either of them. We found that IMC allows distinguishing the two sources of metabolic interference on the basis of “isotope-editing” and advanced thermogram analyses. The stable and radioactive europium isotopes 153Eu and 152Eu, respectively, were employed in monitoring Lactococcus lactis cultures via IMC. β−-emission (electrons) was found to increase initial culture growth by increased nutrient uptake efficiency, which compensates for a reduced maximal cell division rate. Direct adsorption of the radionuclide to the biomass, revealed by mass spectrometry, is critical for both the initial stress response and the “dilution” of radioactivity-mediated damage at later culture stages, which are dominated by the chemical toxicity of Eu.

Recent studies of laser plasma acceleration processes feature increasing requirements to the
technical equipment and time consumption in both numerical and experimental research.
This rising demand on statistical and mathematical methods for inversion of the system
state, comprehension of measurement data and quantification of data stability can only be
met by a comprehensive machine learning based surrogate model for Laser-driven Plasma
Accelerators (LPA). This surrogate potentially accelerates theoretical comprehension of the
system, novel means for design space exploration and promises reliable in-situ analysis of
experimental data which leads to novel guidance mechanisms for future LPA experiments.
The main aim of our work is to elaborate a surrogate model for electron acceleration
processes by virtue of that one could unveil beam dynamics on the scope of collected
diagnostic. Recently achieved results on laser-wakefield electron acceleration, demonstrate
the capability to learn an approximation of the data-dependent posterior distribution by
conditional inventible neural networks. The further derived model is able to describe an
electron bunch transformation in the simulated beam transport in terms of phase space
particle distribution based on its initial parameters: divergence and size. This step opens a
perspective to a potential elaborated model that could use obtained diagnostics for
reconstructions at any point in the electron beamline consisting of conventional magnetic
elements.

Sources of soft X-rays are highly appealing in research as they allow to image atomic- and
molecule- scaled structures, however high requirements to technical equipment complicate
application of such systems. Free electron laser is one of famous sources of ultra-intense
coherent X-ray beams. Convenient kilometer-scale electron accelerators make these
facilities expensive and difficult to maintain, while laser-driven electron accelerators might
significantly reduce size of free-electron lasers. In order to control such a source of X-rays
there are required time consuming numerical and experimental research. A rising demand
on statistical and mathematical methods for inversion of the system state, comprehension of
measurement data and quantification of data stability can only be met by a comprehensive
machine learning based digital twin for Free Electron Laser. The digital twin potentially
accelerates theoretical comprehension of the system, novel means for design space
exploration and promises reliable in-situ analysis of experimental diagnostics and
parameters which leads to democratization of laser-driven FELs accelerating fundamental
science in research field MATTER by collaborative efforts in Matter and Technologies. Digital
twin is comprising of multiple surrogate models for electron acceleration processes by virtue
of that one could unveil beam dynamics on the scope of collected diagnostic. This
formulation allows us to derive observables within the beamline promising physics-informed
inversion of the beamline meaning that we are able to explain observations guided by our
theoretical understanding.

The Institute of Resource Ecology (IRE) is one of the ten institutes of the Helmholtz-Zentrum Dresden – Rossendorf (HZDR). Our research activities are mainly integrated into the program “Nuclear Waste Management, Safety and Ra-diation Research (NUSAFE)” of the Helmholtz Association (HGF) and focus on the topics “Safety of Nuclear Waste Disposal” and “Safety Research for Nuclear Reactors”. The program NUSAFE, and therefore all work which is done at IRE, belong to the research field “Energy” of the HGF.

Radio broadcast, coloRadio

Scanning coherent X-ray microscopy (ptychography) has gained considerable interest during the last decade since the performance of this indirect imaging technique does not necessarily rely on the quality of the X-ray optics and, in principle, can achieve highest spatial resolution in X-ray imaging. The method can be easily extended to 3D by adding standard tomographic reconstruction schemes. However, the tomographic reconstruction is often applied in a subsequent step using a sequence of aligned ptychographic 2D projections. In this contribution, we outline current developments of a GPU-accelerated framework for direct 3D ptychography, coupling 2D ptychography and tomography. The program utilizes a custom GPU-accelerated framework for ptychography that offers three distinct ptychographic reconstruction algorithms. The tomographic reconstruction runs simultaneously and uses numerical routines of the ASTRA Toolbox. This parallel-computing approach results in a high performance increase considerably reducing the reconstruction time of 3D ptychographic datasets.

Grazing-Incidence Small-Angle X-ray Scattering (GISAXS) is a modern imaging technique used in material research to study nanoscale materials. Reconstruction of the parameters of an imaged object imposes an ill-posed inverse problem that is further complicated when only an in-plane GISAXS signal is available. Traditionally used inference algorithms such as Approximate Bayesian Computation (ABC) rely on computationally expensive scattering simulation software, rendering analysis highly time-consuming. We propose a simulation-based framework that combines variational auto-encoders and normalizing flows to estimate the posterior distribution of object parameters given its GISAXS data. We apply the inference pipeline to experimental data and demonstrate that our method reduces the inference cost by orders of magnitude while producing consistent results with ABC.

The environmental fate of radionuclides (RNs) such as actinides and fission products disposed in underground nuclear waste repositories is of major concern. Long-term safety assessments of these disposal sites rely on the ability of geochemical models and thermodynamic databases (TDB) to forecast the mobility of RNs over very long time periods. One example where large data gaps in TDB still exist is related to the complexation of trivalent actinides and lanthanides with aqueous phosphates. Indeed, solid phosphate monazites are one of the candidates for the immobilization of specific high-level waste streams for safe storage in deep underground repositories in the future, which could locally increase the occurrence of phosphate in the repository.
Recent works [1-3] have been carried out to partially close these gaps in order to provide reliable complexation constants at 298K and at elevated temperature. However, obtaining this information is challenging and requires the identification of the formed complexes by means of spectroscopic techniques, such as UV-Vis or TRLFS (Time-Resolved Laser Fluorescence Spectroscopy). Depending on the phosphate concentration, mono or bi-dendate phosphate complexes can be formed with various coordination numbers (8, 9). However, it is often a challenge to obtain further information about the complex structures from the spectroscopic data alone.
In this context, relativistic quantum chemical (QC) methods can be seen as an additional tool to complement the experimental observations. In this study, structural properties, electronic structures and thermodynamics of the 1:1 and 1:2 phosphate complexes of Cm(III) and Eu(III) (see below) have been extracted by state-of-the-art QC calculations. In particular, QC methods allowed i) studying the complexation strengths of Cm(III) and Eu(III) with aqueous phosphates, ii) suggesting a potential change of the coordination number with increasing temperature and iii) probing the character (ionic/covalent) of the Cm/Eu-water and Cm/Eu-phosphate bonds.

Combining the information obtained from the quantum chemical calculations with the observed spectral changes, facilitates a conclusive assignment of the phosphate complex structures and their overall coordination [2,3].

[1] Jordan, N., Demnitz, M., Lösch, H., Starke, S., Brendler, V., and Huittinen, N. (2018). Complexation of trivalent lanthanides (Eu) and actinides (Cm) with aqueous phosphates at elevated temperatures. Inorg. Chem. 57:7015−7024.
[2] Huittinen, N., Jessat, I., Réal, F., Vallet, V., Starke, S., Eibl, M., and Jordan, N. (2021). Revisiting the complexation of Cm(III) with aqueous phosphates: new insights from luminescence spectroscopy and ab initio simulations. Inorg. Chem. 60:10656−10673.
[3] Jessat, I., Jordan, N., Kretzschmar, J., Réal, F., Vallet, V., Stumpf, T., and Huittinen, N. (2023). Impact of temperature on the complexation of Eu(III) with phosphate ions: a spectroscopic and ab initio study. Inorg. Chem. (in preparation).

Cancer presents as a highly heterogeneous disease with partly overlapping and partly distinct
(epi)genetic characteristics. These characteristics determine inherent and acquired resistance,
which need to be overcome for improving patient survival. In line with the global efforts in
identifying druggable resistance factors, extensive preclinical research of the Cordes lab and others
designated the cancer adhesome as a critical and general therapy resistance mechanism with
multiple druggable cancer targets. In our study, we addressed pancancer cell adhesion mechanisms
by connecting the preclinical datasets generated in the Cordes lab with publicly available
transcriptomic and patient survival data. We identified similarly changed differentially expressed
genes (scDEGs) in nine cancers and their corresponding cell models relative to normal tissues.
Those scDEGs interconnected with 212 molecular targets from Cordes lab datasets generated
during two decades of research on adhesome and radiobiology. Intriguingly, integrative analysis
of adhesion associated scDEGs, TCGA patient survival and protein-protein network
reconstruction revealed a set of overexpressed genes adversely affecting overall cancer patient
survival and specifically the survival in radiotherapy-treated cohorts. This pancancer gene set
includes key integrins (e.g. ITGA6, ITGB1, ITGB4) and their interconnectors (e.g. SPP1, TGFBI),
affirming their critical role in the cancer adhesion resistome. In summary, this meta-analysis
demonstrates the importance of the adhesome in general, and integrins together with their
interconnectors in particular, as potentially conserved determinants and therapeutic targets in
cancer.

Electroencephalography produces high-dimensional, stochastic data from which it might be challenging to extract high-level knowledge about the phenomena of interest. We address this challenge by applying the framework of variational auto-encoders to 1) classify multiple pathologies and 2) recover the neurological mechanisms of those pathologies in a data-driven manner. Our framework learns generative factors of data related to pathologies. We provide an algorithm to decode those factors further and discover how different pathologies affect observed data. We illustrate the applicability of the proposed approach to identifying schizophrenia, either followed or not by auditory verbal hallucinations. We further demonstrate the ability of the framework to learn disease-related mechanisms consistent with current domain knowledge. We also compare the proposed framework with several benchmark approaches and indicate its classification performance and interpretability advantages.

Background and purpose: There is no consensus about an ideal robust optimization (RO) strategy for proton therapy of targets with large intra-fractional motion. We investigated the plan robustness of different RO strategies regarding setup/range errors, interplay effects and interfractional anatomical changes.
Materials and methods: For eight non-small cell lung cancer patients with primary and/or nodal clinical target volume (CTVp/CTVn) with motion >5mm, different RO approaches were investigated: 3DRO considering the average CT (AvgCT) with a target density override, 4DRO considering three/all 4DCT phases, and 4DRO considering the AvgCT and three/all 4DCT phases. Realistic interplay scenarios were reconstructed based on patient breathing and machine logfile data for deliveries with/without layered rescanning. Robustness against setup/range errors, interplay effects and interfractional anatomical changes were analyzed for target coverage and OAR sparing.
Results: All nominal plans fulfilled the clinical requirements, while 4DRO without AvgCT generated the most conformal dose distributions. Robustness against setup/range errors was best for 4DRO with AvgCT. No RO strategy was sufficient in countervailing fraction-wise dose distortions caused by interplay effects. Irrespective of rescanning, target coverage was restored in all cases when accumulating four interplay scenarios. 4DRO with AvgCT showed higher CTVp robustness against interfractional changes, but plan adaptations are necessary for all RO strategies in case of relevant anatomical changes.
Conclusion: All RO strategies are clinically acceptable but exhibit equally low robustness against interplay effects. To ensure fraction-wise target coverage, additional motion mitigation is required for CTVs with large motion amplitudes and interfractional changes need to be monitored.

In order to clarify the migration mechanism and wake behavior of a single bubble rising near a vertical wall, three-dimensional direct numerical simulations are implemented based on the open-source software Basilisk and various types of migration paths like linear, zigzag and spiral are investigated. The volume of fluid (VOF) method is used to capture the bubble interface at a small scale, while the gas-liquid interface and high-velocity-gradient regions in the flow field are encrypted with the adaptive mesh refinement technology. The results show that the vertical wall has an obstructive effect on the diffusion of the vortex boundary layer on the surface of the bubble migrating in a straight line, and the resulting reaction force tends to push the bubbles away from the wall surface. For the zigzag or spiral movement of a bubble in the x-y plane, the perpendicular wall is an unstable factor, but on the contrary, the motion in
the z-y plane is stabilized.

Deep Neural Networks are widely applied for solving Computer Vision tasks for Unmanned Aerial Vehicles (UAVs). For some applications, the predictions of the neural networks (NNs) directly influence the motion planning or control of the UAVs. However, the neural networks are highly prone to adversarial attacks, which has a severe negative impact on the drone’s safe operation. With this work, we are planning to perform a physically realizable attack on a neural network analyzing camera images. The control of the UAV is directly influenced by the predictions of this NN. The generated adversarial attacks will be printed and attached as adversarial patches to an attacker UAV. By choosing which patch to present given the current relative poses of victim and attacker, the attacker will achieve full control over the victim UAV.

The p-center problem is finding the location of p facilities among a set of n demand points such that the maximum distance between any demand point and its nearest facility is minimized. In this paper, we study this problem in the context of uncertainty, that is, the location of the demand points may change in a region like a disk or a segment, or belong to a finite set of points. We introduce Max-p-center and Min-p-center problems which are the worst and the best possible solutions for the p-center problem under such locational uncertainty. We propose approximation and parameterized algorithms to solve these problems under the Euclidean metric. Further, we study the MinMax Regret 1-center problem under uncertainty and propose a linear-time algorithm to solve it under the Manhattan metric as well as an O(n4) time algorithm under the Euclidean metric.

Modelling the temperature of Electric Vehicle (EV) batteries is a fundamental task of EV manufacturing. Extreme temperatures in the battery packs can affect their longevity and power output. Although theoretical models exist for describing heat transfer in battery packs, they are computationally expensive to simulate. Furthermore, it is difficult to acquire data measurements from within the battery cell. In this work, we propose a data-driven surrogate model (LiFe-net) that uses readily accessible driving diagnostics for battery temperature estimation to overcome these limitations. This model incorporates Neural Operators with a traditional numerical integration scheme to estimate the temperature evolution. Moreover, we propose two further variations of the baseline model: LiFe-net trained with a regulariser and LiFe-net trained with time stability loss. We compared these models in terms of generalization error on test data. The results showed that LiFe-net trained with time stability loss outperforms the other two models and can estimate the temperature evolution on unseen data with a relative error of 2.77 % on average.

stochastic-based modelling, promising that the inherent uncertainty in quantum computing will prove to be a significant advantage, driving quantum and neuromorphic computing research
to new heights. Spiking Neural Networks (SNNs) are gaining popularity due to their inherent ability to process spatial and temporal data. However, it is a daunting task to train
the network weights of classical SNN due to the stochastic behaviour of neuron signals and the inherent non-differentiable spike events. This paper introduces a supervised Deep Spiking
Quantum Neural Network (DSQ-Net) using a hybrid classicalquantum framework having the merits of amplitude encoding in a dressed quantum layer. A novel attempt has been made
to obviate the challenges in training a classical SNN, assisted by a Variational Quantum Circuit (VQC) in the proposed hybrid classical-quantum framework. The proposed DSQ-Net
is rigorously validated and benchmarked on the ideal PennyLane Quantum Simulator with limited quantum hardware. The experiments have been conducted on unseen test images with imposed noise from the FashionMNIST, MNIST, KMNIST and CIFAR-10 datasets. Classification accuracy is reported to be 95.6% for the proposed DSQ-Net model and
it outperforms the classical counterpart (Deep Spiking Neural Networks), shallow Random Quantum Neural Networks (RQNN), ResNet-18 and AlexNet. The PyTorch implementation
of DSQ-Net is made available on Github0:https://anonymous.4open.science/r/DSQ-Net-037E.

The understanding of laser-solid interactions is important to the development of future laser-driven particle and photon sources, e.g., for tumor therapy, astrophysics or fusion. Currently, these interactions can only be modeled by simulations which need verification in the real world. Consequently, in 2016, a
pump-probe experiment was conducted by Thomas Kluge to examine the laser-plasma interaction that occurs when an ultrahigh-intensity laser hits a solid density target. To handle the nanometer spatial and femtosecond temporal resolution of the laser-plasma interactions, Small-Angle X-Ray Scattering (SAXS) was used as a diagnostic to reconstruct the laser-driven target. However, the reconstruction of the target from the SAXS diffraction pattern is an inverse problem which are often ambiguous, due to the phase problem, and has no closed-form solution. We aim to simplify the process of reconstructing the target from SAXS images by employing Neural Networks, due to their speed and generalization capabilities. To be more specific, we use a conditional Invertible Neural Network (cINN), a type ofNormalizing Flows, to resolve the ambiguities of the target with a probability density distribution. The
target in this case is modelled by a simple grating function with three parameters. We chose this analytically well-defined and relatively simple target as a trial run for Neural Networks in this field to pave the way for more sophisticated targets and methods. Unfortunately, we don’t have enough and reliable experimental data that could be used as training. So, in consequence, the network is trained only on simulated diffraction patterns and their respective ground truth parameters. The cINN is able to accurately reconstruct simulated- as well as preshot data. The performance on main-shot data remains unclear due to the fact that the simulation might not be able to explain the governing processes.

The understanding of laser-solid interactions is important to the development of future laser-driven particle and photon sources, e.g., for tumor therapy, astrophysics or fusion. Currently, these interactions can only be modeled by simulations which need verification in the real world. Consequently, in 2016, a pump-probe experiment was conducted by Thomas Kluge to examine the laser-plasma interaction that occurs when an ultrahigh-intensity laser hits a solid density target. To handle the nanometer spatial and femtosecond temporal resolution of the laser-plasma interactions, Small-Angle X-Ray Scattering
(SAXS) was used as a diagnostic to reconstruct the laser-driven target. However, the reconstruction of the target from the SAXS diffraction pattern is an inverse problem which are often ambiguous, due to the phase problem, and has no closed-form solution. We aim to simplify the process of reconstructing the target from SAXS images by employing Neural Networks, due to their speed and generalization capabilities. To be more specific, we use a conditional Invertible Neural Network (cINN), a type of Normalizing Flows, to resolve the ambiguities of the target with a probability density distribution. The target in this case is modelled by a simple grating function with three parameters. We chose this analytically well-defined and relatively simple target as a trial run for Neural Networks in this field to pave the way for more sophisticated targets and methods. Unfortunately, we don’t have enough and reliable experimental data that could be used as training. So, in consequence, the network is trained only on simulated diffraction patterns and their respective ground truth parameters. The cINN is able to accurately reconstruct simulated- as well as preshot data. The performance on main-shot data remains unclear due to the fact that the simulation might not be able to explain the governing processes.

The understanding of laser-solid interactions is important to the development of future laser-driven particle and photon sources, e.g., for tumor therapy, astrophysics or fusion. Currently, these interactions can only be modeled by simulations which need verification in the real world. Consequently, in 2016, a pump-probe experiment was conducted by Thomas Kluge to examine the laser-plasma interaction that occurs when an ultrahigh-intensity laser hits a solid density target. To handle the nanometer spatial and femtosecond temporal resolution of the laser-plasma interactions, Small-Angle X-Ray Scattering (SAXS) was used as a diagnostic to reconstruct the laser-driven target. However, the reconstruction of the target from the SAXS diffraction pattern is an inverse problem which are often ambiguous and has no closed-form solution. We aim to simplify the process of reconstructing the target from SAXS images by employing Neural Networks due to their speed and generalization capabilities. To be more specific, we use a conditional Invertible Neural Network (cINN) to resolve the ambiguities with a probability density distribution. In consequence, the cINN is trained on simulated diffraction patterns and their respective
ground truth parameters. The cINN is able to accurately reconstruct simulated- as well as preshot data.
The performance on main-shot data remains unclear due to the fact that the simulation might not be able
to explain the governing processes.

The structure and properties of iron hydrides under pressure have been of interest to geoscientists. At ambient conditions, there are no stable solid iron hydrides. Previous theoretical and experimental studies suggest that the double hcp phase of FeH is stable at low pressures with phase transitions to the hcp and fcc phases up to 80 and 140 GPa, respectively. Here, we present a theoretical investigation of the potential energy surfaces of FeH at high pressure. We construct a highly transferable machine-learned interatomic potential with a hierarchical approach using the PyFLAME code. Then, using this fast and accurate neural network potential, we systematically explore the potential energy surfaces of bulk structures of FeH by global sampling using the minima hopping method, to predict stable and metastable iron hydrides up to 200 GPa. We have carried out density functional theory calculations to refine the predicted structures and to evaluate the dynamical stability of selected structures as well. In an automated and systematic approach, we are going to show how a transferable machine-learned interatomic potential can be trained and validated using global optimization and analyze the phase diagram of the stoichiometric Fe-H system under pressure.

Equation-of-state (EoS) data — relating the pressure and internal energy to material density and temperature — is a key quantity in the warm dense matter regime, for example as input to hydrodynamics codes used to guide inertial confinement fusion experiments. The first-principles methods, density-functional theory and path-integral Monte–Carlo, are considered state-of-the-art approaches to calculate EoS data. However, both methods are computationally expensive, which motivates the development of low-cost approaches such as average-atom models. In the first part of this talk, we benchmark EoS results from an average-atom model against the extensive first-principles dataset from Militzer et al. (Phys. Rev. E 103, 013203). In the second part, we develop a neural-network surrogate model as a numerically feasible alternative to calculating EoS data. We train two neural networks to interpolate this dataset, with one being trained using average-atom outputs and the other without. We also compare the accuracy of the machine-learned and average-atom models using out-of-distribution data from other sources.

In recent years, the reactor core simulator DYN3D has become a frequently used tool for neutronic analyses of Sodium cooled Fast Reactors (SFRs) by the Reactor Safety Group of the Helmholtz-Zentrum Dresden-Rossendorf. The capabilities of the code are constantly expanding with new models, such as the various thermal expansion models relevant for SFR neutronic behavior. This study presents the extension of the radial expansion module for the modeling of non-uniform core expansions, i.e. core flowerings. Since DYN3D uses regular numerical meshes for its neutronic solvers, the implementation of the coordinate transformation method (CTM) was performed to cope with non-uniform core deformations. First, the implementation of the CTM was tested on a realistic SFR core for lifelike core flowering scenarios. The DYN3D results were compared against the Monte Carlo reference solutions. Second, DYN3D was validated against the core flowering experiment performed in the Phenix reactor. The measured reactivity effects of the static deformations were used to assess the DYN3D performance. At both stages, the obtained results show an acceptable agreement with the references, thus demonstrating the applicabilty of DYN3D for modeling various core flowering scenarios.

The new multi-purpose 1-MV AMS facility HAMSTER (Helmholtz
Accelerator Mass Spectrometer for Tracing Environmental Radionuclides)
is built within the HZDR research campus in Dresden-
Rossendorf starting in 2022. The new machine is especially dedicated
to the analysis of ultra-trace levels of actinides in environmental
samples. Therefore, eventual contamination of the site where the
new accelerator building is being constructed should be avoided and
clarified. Hence, several soil samples close to the construction site of
the new accelerator building have been analyzed to assess the content
and isotopic ratios of the actinides U, Np and Pu. The samples
have been processed in the existing chemistry labs of HZDR’s 6-MV
DREAMS facility showing low background levels. Overall, the samples
show expected signatures of global fallout in Pu concentrations
and APu/239Pu ratios. However, in some samples increased 236U
concentrations and relatively low 233U/236U atomic ratios have been
detected pointing to an additional source of 236U. Additional analysis
is currently ongoing.

Usually, quantum electrodynamics is the prime example, when it comes to a well-understood and outstandingly precise description of elementary particle processes. However, modern laser facilities provide highly intense light with a non-trivial temporal structure, where an arbitrary number of ‘photons’ from the light source may interact with the colliding particles. In this case, the standard perturbative treatment, e.g. known from quantum electrodynamics, becomes very cumbersome and impractical. Accordingly, there are, among others, wide theoretical investigations w.r.t. scattering processes of particles impinging these extreme light sources. This has been done by applying strong-field quantum electrodynamics, which is a theory of electromagnetic interactions within coherent highly intense light treated as a classical background field. Here, the distinction between a classical background field and a quantised photon field revealed a vast amount of novel non-linear structures and non-perturbative phenomena. In this seminar, we introduce the basic concepts of strong-field QED and derive the Feynman rules for the theory. Then we apply those rules to the Breit-Wheeler process, i.e. the electron-positron pair production in the collision of a laser field and a highly energetic photon

Some studies of applying a 50 keV XFEL for strong-field physics, modelled by the interaction with an electron beam, were presented. The process of electron-positron pair production in strong fields deviates from the well-known perturbative result in weak field backgrounds. In a strong field background, an electron can directly emit a photon, generating a pair via the trident process. Using 50 keV photons, only about 5 MeV kinetic electron energy is required to reach the trident threshold, which is available by electron guns or laser acceleration (in solids, or wakefield). The trident process can also be used to test models for dark matter candidates. Using the proposed massive “dark photon”, the assumed mass and coupling to ordinary could be determined more precisely than with hadron experiments. Certain exclusion regions can be scanned, but the trident experiment could also be used to detect dark matter (instead of excluding certain mass/coupling ranges) because there is full control over the QED background. A second scheme is the interaction of hard x-rays with electrons in the presence of an intense, infrared few-cycle laser light field. It allows to study of laser-assisted Compton scattering, Breit Wheeler pair production and trident, where during the peaks of the few-cycle IR laser field, spectral features are introduced. A (quasi-) continuous X-ray beam (as in a synchrotron) is not sufficient for strong-field studies as high intensity is required. A user community, similar to established synchrotron or XFEL users, may not exist yet. Many colleagues work on theoretical models, but more experimentalists will emerge with upcoming experimental capabilities at XFELs. The LUXE experiment at DESY, and the detection of QED vacuum birefringence at HED/HIBEF, EuXFEL, are examples of such developments.

We present a novel approach for an event generator inherently using exact QED descriptions to predict the results of high-energy electron-photon scattering experiments that can be performed at modern X-ray free-electron laser facilities. Future experiments taking place at HIBEF, LCLS, and other facilities targeting this regime, will encounter processes in x-ray scattering from (laser-driven) relativistic plasmas, where the effects of the energy spectrum of the laser field as well as multi-photon interactions can not be neglected anymore. In contrast to the application window of existing QED-PIC codes, our event generator makes use of the fact, that the classical nonlinearity parameter barely approaches unity in high-frequency regimes, which allows taking the finite bandwidth of the x-ray laser into account in the description of the QED-like multi-photon interaction. Consequently, we exploit these effects in Compton scattering, Breit-Wheeler pair-production and trident pair-production in x-ray laser fields as one of the driving forces of electromagnetic cascades and plasma formation.

An estimation for the potential reduction of clinical margins when using prompt gamma imaging for online treatment verification in proton therapy of prostate cancer is provided. For two adaptive scenarios a potential reduction relative to the clinical practice was evaluated. Using the current trolley-mounted PGI system for online treatment verification to trigger an adaptation, the current range uncertainty margins used at our institute could be reduced by 57%. Additional volumetric imaging at isocenter before irradiation could also reduce the setup uncertainty margins by 66%. A case example illustrates the corresponding dose sparing.

The objective of this paper is to quantify the coupling effect on the power distribution of sodium-cooled
fast reactors (SFRs), specifically the European SFR. Calculations are performed with several state-of-the-art
reactor physics and Multiphysics codes (TRACE/PARCS, DYN3D, WIMS, COUNTHER and GeN-Foam) to build
confidence in the methodologies and validity of results. Standalone neutronics calculations were generally
in excellent agreement with a reference Monte Carlo-calculated power distribution (from Serpent). Next,
the impact of coolant density and fuel temperature Doppler feedback was calculated. Reactivity
coefficients for perturbations in the inlet temperature, coolant heat up and core power were shown to be
negative with values of around -0.5 pcm/°C, -0.3 pcm/°C and -3.5 pcm/% respectively. Fuel temperature
and coolant density feedback was found to introduce a roughly -1%/+1% in/out power tilt across the core.
Calculations were then extended to axial expansion for cases where fuel is linked and unlinked to the clad.
Core calculations are in good agreement with each other. The impact of differential fuel expansion is found
to be larger for fuel both linked and unlinked to the clad, with the in/out power tilt increasing to around -
4%/+2%. Thus, while broadly confirming the known result that standalone physics calculations give good
results, the expansion coupling effect is perhaps more than anticipated a priori. These results provide a
useful benchmark for the further development of Multiphysics codes and methodologies in support of
advanced reactor calculations.

Within the European SFR – Safety Measures Assessment and Research Tools (ESFR-SMART) project, steady-state coupled simulation of the ESFR core has been performed using several core analysis packages, with the objective of quantifying the coupling effect. Focus is on the fuel Doppler effect and coolant expansion effect. Standalone neutronics calculations in TRACE/PARCS (PSI), DYN3D (HZDR) and WIMS (Jacobs) showed superb agreement with the reference Serpent power distribution (root mean square (rms) discrepancies of 1.3%, 1.5% and 0.7% respectively). Results for COUNTHER (CIEMAT) were also in reasonable agreement, but with a somewhat higher discrepancy of 3.7%. Temperature distributions from thermal-hydraulic calculations were also compared and are found to be in good agreement. The effect of Doppler and coolant density feedback on core power distribution was predicted by TRACE/PARCS, DYN3D and WIMS to be between 0.4% and 0.8% rms difference in assembly powers. Reactivity coefficients for perturbations in the inlet temperature, flow rate and core power were shown to be negative for these three codes, with values of roughly -0.5 pcm/°C, -0.3 pcm/°C and -3.5 pcm/% respectively. A preliminary investigation of differential thermal expansion effects indicates that this may have a significant effect on core power distribution of a few %, greater than anticipated a priori and may warrant inclusion in coupled core analysis to ensure the accurate calculation of power distributions.

Presentation for the deRSE23 conference, outlining which steps were taken by the HIFIS incubator platform to establish their workshop portfolio, with details on challenges encountered and current state as of February 2023.

In the development of software - for products, projects and platforms - different approaches are pursued. For the life cycle of the software, it is important to determine the appropriate approach as early as possible in order to set the framework conditions for software engineering.

Increasingly, scientific software applications are developing into services that are embedded in and used via community platforms. The goal in developing and operating a software platform is to create a sustainable and scalable set of services for a defined target group. Added value compared to local software solutions arises, among other things, from the fact that data storage, computing capacities and communication options are offered in addition to core functions such as modeling, data analysis, project management or software development. The need for continuous operation and development as well as flexible scalability requires special software development methods such as DevOps and CI/CD. The sustainability approach also requires the embedding into scientific communities as well as continuous funding or a viable business model.

Specifics and experiences of this approach will be discussed on the basis of applications from the Helmholtz platform hifis.net.

HIFIS, the Helmholtz Federated IT Services, is a Helmholtz-wide platform that supports scientific projects with IT resources, services, consulting and expertise from the collection, storage, linking and analysis of research data to the publication of the results. In addition to offering federated cloud and backbone services, a particular focus is on research software engineering. In recent years, extensive support services have been developed around this topic. The areas of consulting, education, community and technology offerings are covered and help scientists across all of Helmholtz to boost their software engineering practice. The poster will take a look at those offerings, outline the extensive reuse opportunities, and will provide a way to see how such offerings could be transferred to other institutions.

Software tools for simulating electrochemical processes (e.g. COMSOL Multi-physics, ELSYCA) are mostly of commercial type. Besides, three-dimensional simulations in complex cell geometries are known to become resource-expensive, as typically thin concentration boundary layers need to be resolved. The present work presents a simulation framework for electrochemical processes based on the open source platform OpenFOAM. The finite volume method used and combined with domain decomposition is able to efficiently benefit from multicore computer architectures. Our framework takes into account electrolyte flow, which is well known to affect mass transfer, and allows to consider multi-species electrolytes and forcing of the electrolyte. The stability and fast convergence of the method presented is found to rely on the linearization of the Butler-Volmer condi-
tion in the iterative solver. The framework is validated against an analytical solution valid for simplified conditions and an electrodeposition process at a conically shaped electrode in an external magnetic field. The latter exhibits transient departure of the concentration boundary layer from the cathode, and excellent agreement with COMSOL simulation results is found.

Set of Python scripts used to produce paper results

Context
Pheochromocytomas/paragangliomas (PPGLs) with pathogenic mutations in the succinate dehydrogenase subunit B (SDHB) are associated with a high metastatic risk. Somatostatin receptor 2 (SSTR2)-dependent imaging is the most sensitive imaging modality for SDHB-related PPGLs, suggesting that SSTR2 expression is a significant cell surface therapeutic biomarker of such tumors.
Objective
Exploration of the relationship between SSTR2 immunoreactivity and SDHB immunoreactivity, mutational status, and clinical behavior of PPGLs. Evaluation of SSTR-based therapies in metastatic PPGLs.
Design
Retrospective analysis of a multicenter cohort of PPGLs.
Setting
Six specialized Endocrine Tumor Centers in Germany, the Netherlands and Switzerland.
Patients
Patients with PPGLs participating in the ENSAT registry.
Methods
Clinical data were extracted from medical records and immunohistochemistry (IHC) for SDHB and SSTR2 was performed in patients with available tumor tissue. Immunoreactivity of SSTR2 was investigated using Volante scores.
Main outcome measure
Association of SSTR2 IHC positivity with genetic and clinic-pathological features of PPGLs.
Results
Of 202 patients with PPGLs, 50% were SSTR2 positive. SSTR2 positivity was significantly associated with SDHB- and SDHx-related PPGLs, with the strongest SSTR2 staining intensity in SDHB-related PPGLs (p=0.01). Moreover, SSTR2 expression was significantly associated with metastatic disease independent of SDHB/SDHx mutation status (p<0.001).
In metastatic PPGLs, the disease control rate with first-line SSTR-based radionuclide therapy was 67% (n=22, n=11 SDHx), and with first-line “cold” somatostatin analogs 100% (n=6, n=3 SDHx).
Conclusions
SSTR2 expression was independently associated with SDHB/SDHx mutations and metastatic disease. We confirm a high disease control rate of somatostatin receptor-based therapies in metastatic PPGLs.

We present a new methodology for the linear-response time-dependent density functional theory (LR-TDDFT) calculation of the dynamic density response function of warm dense matter in an adiabatic approximation that can be used with any available exchange-correlation (XC) functional across Jacob's Ladder and across temperature regimes. The main novelty of the presented approach is that it can go beyond the adiabatic local density approximation (ALDA) and generalized LDA (AGGA) while preserving the self-consistence between the Kohn-Sham (KS) response function and adiabatic XC kernel for extended systems. The key ingredient for the presented method is the combination of the adiabatic XC kernel from the direct perturbation approach with the macroscopic dynamic KS response from the standard LR-TDDFT method using KS orbitals. We demonstrate the application of the method for the example of warm dense hydrogen, for which we perform a detailed analysis of the KS density response function, the RPA result, the total density response function and of the adiabatic XC kernel. The analysis is performed using LDA, GGA, and meta-GGA level approximations for the XC effects. The presented method is directly applicable to disordered systems such as liquid metals, warm dense matter, and dense plasmas.

In most cases, redox activity of a UO22+ complex is regarded as metal-centered phenomena, because uranium has small energy gaps amongst 5f/6d/7s subshells thereby exhibiting a wide range of oxidation states commonly from +III to +VI or in some instances even +I or +II. While a wide variety of redox-active ligands are known for transition metal complexes including multi-electron reduction that could facilitate inert bond or small molecule activation, only few such examples are known for UO22+. In this study, three UO22+ complexes bearing alpha-diimine-, o-quinonediimine- and 2,6-diiminopyridinebased
ligands were synthesized which exhibited two redox couples in the range from −0.79 V to −2.02 V vs. Fc+/0 to stepwise afford singly- and doubly-reduced complexes. Unique electronic transitions of UO22+ complexes with a manifold of low-lying excited states helped us to complementarily combine spectroelectrochemistry and time-dependent density functional theory (TD-DFT) calculations to assign the redox-active site in these UO22+ complexes, i.e., whether or not a ligand of interest becomes redox-active. During the whole redox processes observed here, the ligands employed are found to be exclusively redox-active, i.e., non-innocent, while the centered UO22+ is just spectating and remains unchanged, i.e., innocent. Whereas double reduction of UO22+ complexes usually involves breakening of strong U≡O bonds, this is not required in the present examples and therefore may find the basis for the synthesis of new types of uranium molecular catalysts and magnetic materials.

In this talk, I will present progress in the research on the use of fragment molecular orbital calculations to the system containing lanthanide and actinide.

Plant interactions, understood as the net effect of an individual on the fitness of a neighbor, vary in strength and can shift from negative interference to positive facilitation as the environmental conditions change in time and space. However, the biophysical mechanisms underlying these changes are not well understood. Additionally, evolutionary theory questions the stability of antagonistic facilitation. Using a mechanistic model for belowground resource competition between individual plants, we find that, under stress conditions, antagonistic facilitation is evolutionarily stable even when both interacting plants compete for resources. This supports the theory of ecosystem engineers in primary succession and nurse plants in the stress gradient hypothesis. Furthermore, we find that the proportion of the limiting resource that spontaneously becomes available to any plant is the key environmental parameter determining the evolutionary stability of facilitation. This represents a challenge and a potential confusion factor for empirical studies.

Higher order correlations influence the physics of the system on many levels. They may be summarized by local field corrections or appear explicitly as non-linear contributions in the density response or in other properties like the stopping power. We present the latest results for nonlinear properties of the electron gas as they have been obtained using real time Green's functions, path integral Monte Carlo, and density functional theory. We show how nonlinear properties can be extracted from simulations with and without external perturbations.

Marine plankton play a crucial role in carbon storage, oxygen production, global climate, and ecosystem function. Planktonic ecosystems are embedded in a Lagrangian patches of water that are continuously moving, stretching, and diluting. These processes drive inhomegeneities on a range of scales, with implications for the integrated ecosystem properties, but are hard to characterize. We present a theoretical framework which accounts for all these aspects; tracking the water patch hosting a drifting ecosystem along with its physical, environmental, and biochemical features. The model resolves patch dilution and internal physical mixing as a function of oceanic strain and diffusion. Ecological dynamics are parameterized by an idealized nutrient and phytoplankton population and we specifically capture the propagation of the biochemical spatial variances to represent within-patch heterogeneity. We find that, depending only on the physical processes to which the water patch is subjected, the plankton biomass response to a resource perturbation can vary several fold. This work indicates that we must account for these processes when interpreting and modeling marine ecosystems and provides a framework with which to do so.

Experiments creating extreme states of matter almost invariably create non-equilibrium states.
These are very interesting in their own right but need to be understood even if the ultimate goal
is to probe high pressure or high temperature equilibrium properties like the equation of state.
Here, we report on the capabilities of the newly developed imaginary time correlation function
(ITCF) technique [1] to detect and quantify non-equilibrium in pump-probe experiments fielding
time resolved x-ray scattering diagnostics. We find a high sensitivity of the ITCF even to a small
fraction of non-equilibrium electrons in the Wigner distribution. The behavior of the ITCF technique is such that modern lasers and detectors should be able to trace the non-equilibrium relaxation from tens of femto-seconds to several 10s of picoseconds without the need for a model.

Background: The Editorial Board of EJNMMI Radiopharmacy and Chemistry releases a biannual highlight commentary to update the readership on trends in the field of radiopharmaceutical development.
Main Body: This selection of highlights provides commentary on 21 different topics selected by each coauthoring Editorial Board member addressing a variety of aspects ranging from novel radiochemistry to first-in-human application of novel radiopharmaceuticals.
Conclusion: Trends in radiochemistry and radiopharmacy are highlighted. Hot topics cover the entire scope of EJNMMI Radiopharmacy and Chemistry, demonstrating the progress in the research field, and include new PET-labelling methods for 11C and 18F, the importance of choosing the proper chelator for a given radioactive metal ion, implications of total body PET on use of radiopharmaceuticals, legislation issues and radionuclide therapy including the emerging role of 161Tb.

Large-scale energy storage plants based on power-to-gas-to-power (PtG-GtP) technologies incorporating high temperature electrolysis, catalytic methanation for the provision of synthetic natural gas (SNG) and novel, highly efficient SNG-fired Allam reconversion cycles allow for a confined and circular use of CO2/CH4 and thus an emission-free storage of intermittent renewable energy. This study features a thorough technology assessment for large-scale PtG-GtP storage plants based on highly efficient sCO2 power cycles combined with subsurface CO2 storage. The Allam cycle employs supercritical CO2 as working fluid as well as an oxy-combustion process to reach high efficiencies of up to 66 %. The entire PtG-GtP process chain assessed in this study is expected to reach maximum roundtrip efficiencies of 54.2 % (with dedicated and sufficient O2 storage) or 49.0 % (with a dedicated air separation unit). The implementation of said energy storage systems into existing national energy grids will pose a major challenge, since they will require far-reaching infrastructural changes to the respective systems itself, such as extensive installations of renewable generation and electrolysis capacities as well as sufficient subsurface storage capacities for both CO2 and CH4. Therefore, this study incorporates an assessment of the present subsurface storage potential for CO2 and CH4 in Germany. Furthermore, a basic forecast study for the German energy system with an assumed mass deployment of the proposed SNG-based PtG-GtP energy storage system for the year 2050 is conducted. In case of a fully circular use of CO2/CH4, when electricity is solely generated by renewable energy sources, 736 GW of renewables, 234 GW of electrolysis and 62 GW of gas-to-power capacities are required in the best case scenario in 2050. The total storage volume on the national scale of Germany for both CO2 and CH4 was determined to be 7.8 billion Nm3, respectively, leading to a CH4 storage capacity of 54.5 TWh. The presented investigations illustrate the feasibility of large-scale energy storage systems for renewable electricity based on high temperature electrolysis, catalytic methanation and Allam power cycles paired with large subsurface storages for CO2 and CH4.

Spin-orbit coupling (SOC) is crucially important for the correct description of the electronic structure and transport properties of inorganic semiconductors, and for assessing topological properties as in topological insulators. We present a consistent set of SOC parameters for the density-functional based tight-binding (DFTB) method covering the elements throughout the periodic table. The parameters are based on atomic SOC data calculated at the level of density-functional theory (DFT). We tested these parameters for representative systems with significant SOC, including transition metal dichalcogenide two-dimensional crystals, III-V bulk semiconductors, and topological insulators. Our parameterization opens the door for DFTB-based electronic structure and transport calculations of very large systems, such as twisted van der Waals heterostructures.

Aminopolycarboxylates (APCs) show great complexation potential towards (lanthanide and actinide) metal ions. As such they are often used as decontamination or decorporation agents. Especially trivalent actinides are of great interest, due to their prevalence in spent nuclear fuel. Accurate thermodynamic data on this complexation behavior is key for safety assessments of nuclear waste repositories. In a worst-case scenario – a groundwater intrusion into the repository a (re-)mobilization of radionuclides (RNs) is to be avoided. Low molecular weight organic ligands may however alter the retention potential of the repository relevant solid phases towards the RNs. A ligand of interest is nitrilotriacetic acid (NTA), which is a typical representative of the APCs. It has been previously shown that it forms complexes with trivalent RNs such as Eu(III)[1] and Am(III)[2] and is used as a decontaminating agent. This work focuses on Eu(III) as a nonradioactive analog to some trivalent actinides with outstanding luminescence properties which make it a great probe for time-resolved laser-induced fluorescence spectroscopy (TRLFS) study.
This work utilizes a multi-method approach with nuclear magnetic resonance (NMR) spectroscopy, TRLFS and isothermal titration calorimetry (ITC) to gain accurate and reliable thermodynamic and spectroscopic data on the Eu(III)-NTA system. NMR spectroscopic experiments showed three distinct complexes, which could be attributed to a 1:1, a 1:2 and a 2:2 Eu(III)-NTA complex, the latter of which existing only at increased concentrations. This observation could be confirmed by TRLFS[3]. Complex formation constants were determined from pH and concentration series applying TRLFS. TRLFS data were evaluated using parallel factor analysis as described elsewhere[4]. Verification of those log β values as well as information about the reaction enthalpy ΔH, the reaction entropy ΔS and the Gibbs free energy ΔG were obtained via ITC measurements.
To confirm the proposed similarities in thermodynamic data for complex formation, similar experiments have been conducted with Cm(III). The formation of the 1:1 and the 1:2 complex could be confirmed with log β values similar to Eu(III).
The retention of Eu(III) on calcium aluminum silicate hydrate (C-A-S-H) phases was observed using batch experiments. Preliminary results have shown little to no impact of NTA on the Eu(III) retention. This may be explained by the high concentration of Al(III) and Ca(II) ions in the supernatants of the samples, as NTA readily complexes these ions as well.
Acknowledgement: The German Federal Ministry for Economic Affairs and Energy (BMWi) is thanked for financial support within the GRaZ II project, no. 02E11860B.

[1] Choppin, G. R. et al. (1977). The complexation of lanthanides by aminopolycarboxylate ligands - II. J. Inorg. Nucl. Chem. 39: 2025-2030
[2] Akram, N. and Bourbon, X. (1995). Analyse critique de donnees thermodynamiques: pouvoir complexant de l'EDTA, du NTA, du citrate et de l'oxalate vis a vis de cations metalliques. Etudes Experimentations Calculs. Andra.
[3] Sieber, C. et al. (2023). Eu(III) and Cm(III) complexation of NTA, EDTA, and EGTA studied by means of NMR, TRLFS, and ITC – an improved approach to more robust thermodynamics. in preparation
[4] Drobot, B. et al. (2015). Combining luminescence spectroscopy, parallel factor analysis and quantum chemistry to reveal metal speciation–a case study of uranyl (VI) hydrolysis. Chem. Sci. 6: 964-972

A common problem across scientific domains concerns metadata: Important information about experiments can only be found in file names and directory structures scattered around the filesystem. Fully manual or semi-automated naming of the files, or retrospective changes in the templated structure can worsen the situation by introducing inconsistencies and ambiguities. Not only can this impede scientists in their daily work, but it also prevents reuse or automated post-processing of the data. This talk will present an approach to (i) extracting the metadata from a large collection of real-world datasets suffering from these issues and (ii) improving their (machine-)actionability by ingesting the results into a dedicated metadata catalog.

The energy transition in Germany is one of the greatest challenges for the coming decades. An important part of this is the phase-out of nuclear power generation and the safe long-term storage of highly radioactive waste in a future deep geological repository. When considering safety aspects of a potential repository, the influence of biological processes on the integrity of a potential repository is increasingly taken into account in addition to the necessary (physical-) chemical data basis. The effects of the bio-factor are manifold. Our research shows that the interaction of radionuclides with whole (micro)organisms or organic substances produced by them form complexes that alter the migration behavior of radionuclides. In addition, the mineral phases of the host rock are altered by bio-degradation and biomineralization processes. Another important aspect is that microbial induced electron transfer processes cause corrosion that reduces the integrity of potential containers. Last but not least, metabolic processes, especially under anaerobic conditions, lead to gas production that directly alters physical parameters such as pressure. However, the knowledge gained will not only be incorporated into state-of-the-art algorithms for modeling hydrogeological and ecological systems, but will also be important far beyond repository research.
Studying the interaction of radionuclides with bacteria, for example, has provided new insights that have led to the development of an innovative process for plastic electroplating. The novel process allows the coating of highly complex polymer parts with functional metal surfaces while at the same time substituting highly toxic chemicals and saving resources. The investigation and comparison of different mine waters from former uranium ore mining has also led to the development of a new concept for the cost-effective, biotechnological purification of contaminated mine waters. The process and the potential of the procedure are currently being investigated in more detail as part of a project. In addition, thermodynamic studies of biopolymers identified as cellular radionuclide binding sites have demonstrated their potential for separation processes. Due to the chemical similarity of actinides and lanthanides, these findings are being applied to the field of circular economy, rare earth extraction and recycling.
The examples mentioned clearly show how repository and radioecological research can also make an important contribution to a sustainable and successful energy transition beyond the actual research topic.

We investigate the synchronization transition of the Shinomoto-Kuramoto model Q21
on networks of the fruit-fly and two large human connectomes. This model
contains a force term, thus is capable of describing critical behavior in the
presence of external excitation. By numerical solution we determine the
crackling noise durations with and without thermal noise and show extended
non-universal scaling tails characterized by 2 < τ_t < 2.8, in contrast with the Hopf
transition of the Kuramoto model, without the force τ_t = 3.1 (1). Comparing the
phase and frequency order parameters we find different transition points and
fluctuations peaks as in case of the Kuramoto model. Using the local order
parameter values we also determine the Hurst (phase) and β (frequency)
exponents and compare them with recent experimental results obtained by
fMRI. We show that these exponents, characterizing the auto-correlations are
smaller in the excited system than in the resting state and exhibit module
dependence.

Technetium (Tc) is an element of concern for the environment and living organisms. In particular, 99Tc a beta emitter with a long half-life (t1/2 = 2∙105 years) is the most abundant isotope of Tc. Besides its generation by medical applications, it is a fission product in nuclear reactors during energy production and must be considered in the safety assessment of nuclear waste repositories. Tc is known to be very mobile in water fluxes under aerobic condition, when mainly TcVII is present. TcVII barely interacts with minerals or microorganisms that could restrict its migration. Thus, the strategy to immobilize TcVII employs the reduction of TcVII to TcIV, since the main species of TcIV is a low soluble oxide (TcIVO2), limiting Tc migration through aquifers. The change in redox state is triggered by reducing agents, such as Fe2+, sulfide or by microbiological redox cascades. Thus, it is necessary to evaluate the interaction of Tc with different materials present in engineered or natural environments also under more complex experimental conditions. We use a broad variety of advanced techniques along a value chain that starts with determination of thermodynamic data (i.e. complex formation constants, solubility constants of minerals, redox potentials and Tc distribution coefficients) it is followed by structural verification by micro-spectroscopy approaches up to establishment in thermodynamic databases. Our particular interest is the in situ monitoring of molecular sorption and redox processes at biogeochemical interfaces and in solutions. As a result, a deep chemical understanding of environmental behavior of technetium will allow the development of sound risk assessments and remediation strategies. This is only feasible by a multidisciplinary approach, including chemistry, geosciences and microbiology.
Some of the work presented here is part of the BMBF funded young investigator group TecRad (Ref 02NUK072, further details can be found at https://www.hzdr.de/db/Cms?pNid=1375).

Studies of charged-particle reactions for low-energy nuclear astrophysics require high sensitivity, which can be achieved by means of detection setups with high efficiency and low backgrounds, to obtain precise measurements in the energy region of interest for stellar scenarios. High-efficiency total absorption spectroscopy is an established and powerful tool for studying radiative capture reactions, particularly if combined with the cosmic background reduction by several orders of magnitude obtained at the Laboratory for Underground Nuclear Astrophysics (LUNA). We present recent improvements in the detection setup with the Bismuth Germanium Oxide (BGO) detector at LUNA, aiming to reduce high-energy backgrounds and to increase the summing detection efficiency. The new design results in enhanced sensitivity of the BGO setup, as we demonstrate and discuss in the context of the first direct measurement of the 65 keV resonance (Ex = 5672 keV) of the 17O(p,gamma)18F reaction. Moreover, we show two applications of the BGO detector, which exploit its segmentation. In case of complex gamma-ray cascades, e.g. the de-excitation of Ex = 5672 keV in 18F, the BGO segmentation allows to identify and suppress the beam-induced background signals that mimic the sum peak of interest. We demonstrate another new application for such a detector in form of in-site activation measurements of a reaction with beta+ unstable product nuclei, e.g., the 14N(p,gamma)15O reaction.

Ligand K-edge XANES is an effective mean to probe the electronic structure of actinides in molecular complexes and solid-state compounds. The hybridization of actinide 5f and 6d states with ligand p-orbitals makes the metal contribution visible in the K-edge XANES, offering a different point of view to observe the electronic structure of the system.

In this contribution, we will report our recent analysis of the O K-edge XANES of ThO2 and compare it with that of CeO2 [1]. We found that despite the similarity of the spectra, the interpretation of the main spectral features is different and reflects the different roles of f- and d- orbitals in shaping the electronic structure of the two compounds.
The stronger localization of Ce 4f over Th 5f emerges from the sharpness of the corresponding spectral features. The splitting of the 5d/6d orbitals in two bands, i.e., eg and t2g, is observed and reproduced by DFT-bases calculations. The Ce 4f orbitals are found below the 5d bands, while for ThO2 the 5f band is between the 6d-eg and 6d-t2g bands. Figure 1 summarizes these findings.

The necessity of energy independency, political and climatic concerns is driving the global attention towards sustainable energy sources. The European commission targets carbon-neutrality with net zero greenhouse gas emission by 2050 [1], which results in a decarbonization of the energy sector by renewable energy sources. Nevertheless, a significant challenge arises from the fluctuating power infeed of wind and solar based plants, which may result in grid instability, overstrain and mismatch in supply-demand. Thus, energy storage systems (ESS) are required to decouple electricity generation from the demand and to enhance the reliability of the energy system. Furthermore, a successful implementation of such a storage technology on a large scale requires cost-effective cycles for energy storage and reconversion.
Therefore, a Power-to-Heat-to-Power system is proposed, based on electrical charged high temperature ceramics and a supercritical CO2 (sCO2) power cycle for discharge. The high temperature sensible thermal energy storage is manufactured from waste material of the aluminum production, which is a low-cost storage solution. As a result, such a thermal storage combines an important contribution to the circular economy with an economic solution for large scale, location-independent energy storage. CO2 becomes supercritical when temperature and pressure are higher than 31 °C and 74 bar. In this phase the viscosity is low and the density as well as the heat capacity are high. Hence, the installed components, in particular the turbomachinery of the sCO2 power cycle are highly compact, which results in low investment costs and low thermal losses. Furthermore, high temperatures up to 600 °C can be utilized to generate electricity at high thermal efficiency.
An inhouse code was used to study various heat transfer fluids, materials and designs for the thermal storage vessel during the charge and discharge cycle. Furthermore, the heat exchanger transferring the heat from the thermal storage cycle to the sCO2 power cycle was numerically investigated, to optimize compactness and thermal efficiency. Finally, the experimental facility CARBOSOLA was designed in cooperation with the Siemens Energy AG, the TU Dresden and the DLR, to investigate the involved components of the power cycle as well as the cycle performance. Various questions will be addressed, such as material resistance at temperatures up to 650 °C, optimal heat exchanger designs, part load operation of the facility, cost effective volume flow measurement, compression and expansion processes and the favorable integration of the thermal storage cycle. Furthermore, the mentioned partners perform techno-economical-analysis of the described systems and the facility will be used to validate these models.
References
[1] G. Subbaraman et al., “ZEPS TM Plant Model: A High Efficiency Power Cycle with Pressurized Fluidized Bed Combustion Process,” 2nd Oxyfuel Combust. Conf., pp. 2–5, 2011.

A sustainable future requires products to be recyclable. An important process in recycling is shredding where materials joined in multi-material structures are liberated or detached. Until now, no physics-based models exist to describe shredding processes adequately. The proposed approach uses finite element simulations to model the shredding of a multi-material structure (steel and fiber-reinforced polymers with an adhesion joint) in a rotary shredder based on previous experimental investigations. Simulations successfully replicate the shredding phenomena, but the stochastic nature of the process results in different load cases making a strict quantitative comparison between simulations and experiments challenging. Comparing similar load cases of two experiments and the corresponding simulations, the estimated liberation degree ranges from 56 % to 100 % (63 % to 99 % in experiments). The estimated energy consumption varies from 1.4 kWh/t to 1.7 kWh/t (1.0 kWh/t to 1.4 kWh/t in experiments), marking a significant step in achieving a reasonable physics-based estimation of required energy. However, the number of fiber-reinforced polymer fragments is underestimated, ranging from 22 to 50 fragments (50 to 78 in experiments). The presented method is a novel contribution to recyclability assessment and recycling-oriented design.

In this talk, I will present our recent advancements in utilizing Artificial Intelligence (AI) to significantly enhance the efficiency of electronic structure calculations [1]. In particular, I will focus on our efforts to accelerate Kohn-Sham density functional theory calculations atfinite temperatures by incorporating deep neural networks within the Materials Learning Algorithms framework [2,3]. Our results demonstrate substantial gains in calculation speed for metals across their melting point. Furthermore, our implementation of automated machine learning hasresulted in significant savings in computational resources when identifying optimal neural network architectures, thereby laying the foundation forlarge-scale AI-driven investigations [4]. I will also showcase our most recent breakthrough, which enables neural-network-driven electronic structure calculations for systems containing over 100,000 atoms [5]. Finally, I will provide an outlook on the potential of physics-informed neural networks for solving time-dependent Kohn-Sham equations, which describe electron dynamics in response to incident electromagnetic waves [6]. [1] L. Fiedler, K. Shah, M. Bussmann, A. Cangi, Phys. Rev. Materials 6, 040301, (2022). [2] A. Cangi, J. A. Ellis, L. Fiedler, D. Kotik, N. A. Modine, V. Oles, G. A. Popoola, S. Rajamanickam, S. Schmerler, J. A. Stephens, A. P. Thompson, MALA, https://doi.org/10.5281/zenodo.5557254 (2021). [3] J. A. Ellis, L. Fiedler, G. A. Popoola, N. A. Modine, J. A. Stephens, A. P. Thompson, A. Cangi, Phys. Rev. B 104, 035120 (2021). [4] L. Fiedler, N. Hoffmann, P. Mohammed, G. A. Popoola, T. Yovell, V. Oles, J. A. Ellis, S. Rajamanickam, A. Cangi, Mach. Learn.: Sci. Technol. 3 045008 (2022). [5] L. Fiedler, N. A. Modine, S. Schmerler, D. J. Vogel, G. A. Popoola, A. P. Thompson, S. Rajamanickam, A. Cangi, arXiv:2210.11343 (2022). [6] K. Shah, P. Stiller, N. Hoffmann, A. Cangi, Physics-Informed Neural Networks as Solvers for the Time-Dependent Schrödinger Equation, NeurIPS Machine Learning and the Physical Sciences, arXiv:2210.12522 (2022).

Artificial intelligence (AI) has great potential for accelerating electronic structure calculations to hitherto unattainable scales [1]. I will present our recent efforts accomplishing speeding up Kohn-Sham density functional theory calculations at finite temperatures with deep neural networks in terms of our Materials Learning Algorithms framework [2,3] by illustrating results for metals across their melting point. Furthermore, our results towards automated machine learning save orders of magnitude in computational efforts for finding suitable neural networks and set the stage for large-scale AI-driven investigations [4]. Finally, I will conclude with a preview of our most recent result that enables neural-network-driven electronic structure calculations for systems containing more than 100,000 atoms.
[1] L. Fiedler, K. Shah, M. Bussmann, A. Cangi, Phys. Rev. Materials 6, 040301, (2022).
[2] A. Cangi, J. A. Ellis, L. Fiedler, D. Kotik, N. A. Modine, V. Oles, G. A. Popoola, S. Rajamanickam, S. Schmerler, J. A. Stephens, A. P. Thompson, MALA, https://doi.org/10.5281/zenodo.5557254 (2021).
[3] J. A. Ellis, L. Fiedler, G. A. Popoola, N. A. Modine, J. A. Stephens, A. P. Thompson, A. Cangi, Phys. Rev. B 104, 035120 (2021).
[4] L. Fiedler, N. Hoffmann, P. Mohammed, G. A. Popoola, T. Yovell, V. Oles, J. A. Ellis, S. Rajamanickam, A. Cangi, Mach. Learn.: Sci. Technol. 3 045008 (2022).

Two-dimensional conjugated metal-organic frameworks (2D c-MOFs) are emerging as a unique class of electronic materials. However, 2D c-MOFs with band gaps in the Vis-NIR and high charge carrier mobility are rare. Most of the reported semiconducting 2D c-MOFs are metallic (i.e. gapless), which largely limits their use in logic devices. Herein, we design a phenanthrotriphenylene-based, D2h-symmetric π-extended ligand (OHPTP), and synthesize the first rhombic 2D c-MOF single crystals (Cu2(OHPTP)). The continuous rotation electron diffraction (cRED) analysis unveils the orthorhombic crystal structure at the atomic level with a unique AB layer stacking. The Cu2(OHPTP) is a p-type semiconductor with an indirect band gap of ~0.50 eV and exhibits high electrical conductivity of 0.10 S cm-1 and high charge carrier mobility of ~10.0 cm2 V-1 s-1. Theoretical calculations underline the predominant role of the out-of-plane charge transport in this semiquinone-based 2D c-MOF.

Purpose

To assess the relation of the previously reported classification of molecular subtypes to the outcome of patients with HNSCC treated with postoperative radio(chemo)therapy (PORT-C), and to assess the association of these subtypes with gene expressions reflecting known mechanisms of radioresistance.
Material and methods

Gene expression analyses were performed using the GeneChip Human Transcriptome Array 2.0 on a multicentre retrospective patient cohort (N = 128) of the German Cancer Consortium Radiation Oncology Group (DKTK-ROG) with locally advanced HNSCC treated with PORT-C. Tumours were assigned to four molecular subtypes, and correlation analyses between subtypes and clinical risk factors were performed. In addition, the classifications of eight genes or gene signatures related to mechanisms of radioresistance, which have previously shown an association with outcome of patients with HNSCC, were compared between the molecular subtypes. The endpoints loco-regional control (LRC) and overall survival (OS) were evaluated by log-rank tests and Cox regression.
Results

Tumours were classified into the four subtypes basal (19.5%), mesenchymal (18.8%), atypical (15.6%) and classical (14.1%). The remaining tumours could not be classified (32.0%). Tumours of the mesenchymal subtype showed a lower LRC compared to the other subtypes (p = 0.012). These tumours were associated with increased epithelial-mesenchymal transition (EMT) and overexpression of a gene signature enriched in DNA repair genes. The majority of the eight considered gene classifiers were significantly associated to LRC or OS in the whole cohort.
Conclusion

Molecular subtypes, previously identified on HNSCC patients treated with primary radio(chemo)therapy or surgery, were related to LRC for patients treated with PORT-C, where mesenchymal tumours presented with worse prognosis. After prospective validation, subtype-based patient stratification, potentially in combination with other molecular classifiers, may be considered in future interventional studies in the context of personalised radiotherapy and may guide the development of combined treatment approaches.

Anewapproach to target development for laboratory astrophysics experiments at high power laser facilities is presented. With the dawnofhighpowerlasers, laboratory astrophysics emerged as a field, bringing insight into physical processes in astrophysical objects, such as formation of stars. An important factor for success on these experiments is targetry. To date, targets have mainly relied on expensive and challenging microfabrication methods. The design presented incorporates replaceable machined parts which assemble into a structure that defines the experimental geometry. This can make targets cheaper and faster to manufacture, while maintaining robustness and reproducibility. The platform is intended for experiments on plasma flows, but it is flexible and may be adapted to the constraints of other experimental setups. Examples of targets used in experimental campaigns are shown, including a design for insertion in a high magnetic field coil. Experimental results are included demonstrating the performance of the targets.

Renewable Electricity production will strongly vary over time in the
Energy System of 2045. Simultaneously the raw materials industry
needs to have its own transition towards a more local circular economy
and from fossil carbon based energy sources to renewables. As a major
and increasingly important energy consumer, this industry might need
to adapt energy consumption to current energy availability.

In this contribution we discuss four major technical possibilities on
different time scales (Inner Energy variation, throughput variation,
scheduled production pauses, and dual power options) for power
flexibility in this sector, their characteristics with regard to grid
service and power market, and with respect to economic and
environmental impacts generated by providing and by using these
flexibility options. The contribution provides generic formulas to
compute such impacts from LCA and LCC results for stationary operation
conditions plus direct impacts of certain actions, and shows how they
depend on market conditions. It also discusses the need for energy
system models to provide predictions of flexibility requirements early
on, to allow the industry to take the right investment decisions with
respect to flexibility.

The contribution shows that while technically major flexibility
potentials exist, considerable investment is required to make them
practically available for the future energy system. It also shows that
Germany needs a considerable local hydrogen infrastructure
(production, distribution and storage) in order to sustain such
industry.

In the post-covid era, touchless interaction between human beings and environments is attracting more and more attentions. Sensors based on giant magnetoresistance (GMR) effect are widely considered as a workhorse to address this demand. However, the fabrication of GMR
multi-layer elements face many limitations (e.g., inappropriate to substrates with curved and/or rough surfaces) due to the layer thickness
dependence of performance. Here, we propose a transfer technique to overcome the aforementioned limitations. With the assistance of two
sacrificial layers, a large scale and wrinkle-free coverage is realized on
various substrates (of different materials, roughness, and curvatures) with little loss of GMR performance. Notably, such technique is easy
processing, without the need of any substrate deformation, temporary carriers or high-temperature processing. The transferred sensors are
integrated into skin-mountable electronics, successfully functioning as a human-machine interface.

Soft actuators are mechanically active functional systems. Magnetic polymeric composites have been used as grippers, rollers, and walkers responding to applied magnetic fields. Flexible, light and conformal sensory systems are still under research to have on-board control of actuation of soft systems. We show electronic skins with magnetic field sensors that provides awareness of the folding state to origami-like magnetic foils.
[1] M. Ha, et al. Adv. Mater. 33, 2008751 (2021)

The development of functional inks allows to create novel printed electronics with unconventional form factors. Here, we show the fabrication of printed magnetic field sensors based on bismuth microparticles. Sensors showed non-saturating large magnetoresistance (146%, 5T, at room temperature), and resilience to mechanical bending (2000 cycles). We demonstrated large area magnetically sensitive interfaces as smart lock and interactive wallpapers.[1]
[1] E.S. Oliveros-Mata, C. Voigt, et al. Adv. Mater. Technol.2200227 (2022)

A typical feature of nuclear safety facilities are multiphase flows with coexisting morphologies, i.e. with phases which occur both in a continuous form (such as in a stratified flow) and in a disperse form (bubbles or droplets). Established simulation methods are usually suitable for either resolved structures (e.g., Volume-of-Fluid) or dispersed structures (e.g., Euler-Euler). We propose a morphology adaptive multifield two-fluid model, which is able to handle both disperse and resolved interfacial structures coexisting in a common computational domain, covered by a unified set of equations. This requires (A) a careful selection of closure models. On the continuous side, the interfacial drag formulation of Štrubelj and Tiselj (Int J Numer Methods Eng, 2011, 85, 575-590) is used to describe large interfacial structures in a volume-of-fluid-like manner. For the dispersed structures, the HZDR baseline model is applied. Meller et al. (Int J for Numer Method Fluid, 2021, 93, 748-773) and Tekavčič et al. (Nucl Eng Des, 379, 111223) presented several test cases to prove that the numerical consistent coexistence of different morphologies is ensured. The interaction of the morphologies is only controlled by the aforementioned closure models without being disturbed by numerical effects. A second requirement is (B) a reliable transition between continuous and disperse states, depending on the size of the structures and the degree of spatial resolution. This is subject of the current work. A prerequisite for reliable transitions is the stable coverage of intermediate situations, where bubbles are either over- or under-resolved for Euler-Euler or Volume-of-Fluid (Fig. 1). An adaptive interfacial drag model and a filtering technique are applied for stable and robust handling of the transition regions. Two morphology transfer models are established, allowing large resolved structures to disintegrate into small unresolved fluid particles and, vice versa, the accumulation of disperse fluid particles to continuous large-scale structures. This is applied to generic verification and validation test cases, representing typical sub-problems relevant in safety facilities. The model is applied to a cyclic separator (Fig. 2), which can only be simulated with methods allowing the transition from a disperse to a continuous morphology. This is particularly challenging because the gas core must exhibit a stable behavior in the highly rotating flow while gas and liquid are moving in opposite directions along the rotational axis.

Für die Lösung von komplexen Problemen können neben Algorithmen auch künstliche neuronale Netzwerke verwendet werden. Mit maschinellem Lernen werden diese Netzwerke standardmäßig auf CPU und GPU erstellt und ausgeführt. Zur Verwendung von trainierten Netzwerken auf FPGAs gibt es jedoch keine direkte Umsetzung innerhalb der bekannten Machine Learning Frameworks. Um dieses Problem zu beheben wurde für Xilinx und Intel FPGA die Portierungs-Software hls4ml entwickelt. Diese Open-Source Software ermöglicht eine Übersetzung von trainierten Netzwerken die mit etablierten Machine Learning Frameworks erstellt wurden in eine High-Level Synthese Sprache.

Innerhalb dieses Projekts erfolgt die Implementierung eines neuronalen Netzwerks für die MNIST-Datensatz Klassifikation, welches anschließend mit hls4ml für die Xilinx Alveo U200 Data Center Accelerator Card portiert wird. Die Portierung erfolgt mit verschiedenen Konfigurationen, um unterschiedlich optimierte Implementierungen zu generieren. Der gesamte Prozess vom Erstellen des Netzwerks bis zur Ausführung der Implementierung und Auswertung der Ergebnisse wird mithilfe von Continous Integration automatisiert.

Die Evaluation zeigt, dass eine Portierung des Netzwerks auf die Xilinx Alveo U200 Data Center Accelerator Card möglich ist. Es sollte jedoch dabei beachtet werden das nicht mit allen Konfigurationen eine ausführbare Implementierung erstellt werden kann.