Publications Repository - Helmholtz-Zentrum Dresden-Rossendorf

Twin monomers [Mg(2-OCH₂-^cC₆H₄O)][L]_0.8 (2, L=diglyme) and [Mg(2-OCH₂-^cC₆H₄O)][L]_0.66 (3, L=tmeda) form by their thermal polymerization interpenetrating organic-inorganic hybrid materials in a straightforward manner. Carbonization (Ar) followed by calcination gave porous MgO (2: surface area 200 m²g^-1, 3: 400 m²g^-1), which showed in catalytic studies towards Meerwein-Ponndorf-Verley reductions excellent yields and complete conversions for cyclohexanone and benzaldehyde. However, with crotonaldehyde a mixture of C₄–C₈ compounds was obtained. When MgO was exposed to air then primarily crotyl alcohol was formed. The range of applications could be easily extended by twin polymerization of 3 in presence of [Cu-(O₂CCH₂O(CH₂CH₂O)₂Me)₂] (4) or [Ag(O₂CCH₂-^cC₄H₃S)(PPh₃)] (5), resulting in the formation of nanoparticle-decorated porous CuO@MgO or Ag@MgO materials, which showed high catalytic reactivity towards the reduction of methylene blue.

Die Kombination von Materialien wie Metallen und Kunststoffen in Verbundstrukturen ermöglicht funktionsintegrative Designs. Im Recycling müssen die unterschiedlichen Materialien jedoch wieder aufgeschlossen werden, um materialspezifisch hohe Recyclingraten zu erzielen. Typischerweise erfolgt der Aufschluss durch mechanische Zerkleinerungsprozesse. Derzeit gibt es keine adäquate Beschreibung dieser Prozesse, die zu einer recyclingorientierten Produktgestaltung beitragen könnte. Im Beitrag wird ein Ansatz zu physikalisch basierten numerischen Simulationen mit der Finite-Elemente-Methode (FEM) vorgestellt.

Due to its balance between accuracy and computational cost, Density Functional Theory (DFT) is one of the most important computational methods within materials science and chemistry. However, current research efforts such as the modeling of matter under extreme conditions demand the application of DFT to larger length scales as well as higher temperatures. Such investigations are currently prohibited due to the computational scaling of DFT.

We have recently introduced a machine-learning workflow that replaces modern DFT calculations [1,2,3]. This workflow uses neural networks to predict the electronic structure locally. We show that by employing such an approach, models can be trained to predict the electronic structure of matter across temperature ranges. This paves the way for large-scale simulations of thermodynamically sampled observables relevant to modeling technologically important phenomena such as radiation damage in fusion reactor walls.

The Mu2e experiment is currently being constructed at Fermilab to search for the direct conversion of muons into electrons in the field of a nucleus without the emission of neutrinos. The experiment aims at a sensitivity of four orders of magnitude higher than previous related experiments, which implies highly demanding accuracy requirements both in the design and during the operation. Hence, it is essential to estimate precisely the backgrounds that could mimic the monoenergetic conversion electron signal and the particle yields relevant to the experiment sensitivity. In that regard, Monte Carlo simulations were performed to investigate key yields and beam-related and cosmic rays-related backgrounds. The investigation includes: (I) an evaluation of the antiproton and charged pion yields from an 8 GeV proton pencil beam impinging on a tungsten cylindrical target, (II) an evaluation of the transmission of cosmic neutrons and neutral kaons in a block of concrete. The simulations were performed using the FLUKA2021, MCNP6, GEANT4, PHITS, and MARS15 codes. The presentation will show the simulation results with a focus on the prediction obtained from each code and their impact on the experiment.

The Mu2e experiment, currently under construction at the Fermi National Accelerator Laboratory near Chicago, will search for the neutrinoless direct conversion of a muon to an electron in the field of an aluminum nucleus, aiming for a sensitivity four orders of magnitude better than previous experiments. The observation of a clear signal would imply Charged Lepton Flavor Violation, and hint at physics beyond the Standard Model.

The normalization of the signal events will be done by monitoring the rate of muons stopping on aluminum target discs. This will be accomplished with a detector system made of an HPGe detector and a Lanthanum Bromide detector, which detect the characteristic X- and γ-rays of energies up to 1809 keV produced when the muons are stopped or captured on the aluminum.

At the Helmholtz-Zentrum Dresden-Rossendorf, we have used a pulsed Bremsstrahlung photon beam at the ELBE radiation facility to study the performance of the detectors under conditions very similar to the ones expected at Mu2e.

In the presentation, a short overview of design and status of the Mu2e experiment and its detectors will be given, and results of the ELBE beamtime campaigns will be presented.

By the middle of 2023, all German nuclear power plants (NPPs) will have been shut down. The final shutdown is followed by a post-operational phase in which measures can be carried out to prepare for the NPPs dismantling and decommissioning. One of the essential tasks in planning and preparing an NPP for decommissioning is to obtain precise knowledge of the activation levels in its reactor pressure vessel (RPV), the biological shielding, and other internal components. In that regard, a novel method based on the combined use of two Monte Carlo codes, MCNP6 and FLUKA2021, was developed to serve as a non-destructive tool for evaluating the activation in an NPP. The presentation will give an overview of the methodology and demonstrate its application through the activation calculations of selected components of a German pressurized water reactor (PWR), which is the most common NPP type in Germany.

We investigate the fluid flow field in a fractured granite core sample. Sequential imaging with Positron-Emission-Tomography (PET) allows direct reconstruction of flow streamlines, thus providing a unique insight into the fluid dynamics of complex fractured crystalline materials. Pulse migration experiments using the positron-emitting radionuclide 18F- as tracer were conducted on a fractured granitic drill core, originating from a depth of 1958 m of the Enhanced Geothermal System (EGS) reference site at Soultz-sous-Forêts, France. The flow field was analyzed as a function of in- and outlet positions across the fracture, as well as applied flow rates. Different flow path
characteristics were identified. Both the fracture aperture variation and the topography of the fracture surface affect the flow field with consequences on flow channeling and preferential flow paths. Furthermore, pulse migration experiments were also numerically simulated with a 2.5D model using COMSOL Multiphysics®.
While the higher flow rate experiments show wider and higher dispersion of the flow path, lower velocity results in more localized flow and channeling behavior. This type of study thus yields enhanced experimental insights into the hydrodynamics of fracture
flow and its relation to the rough structure of natural single fractures, compared to input‑output experiments. It can help to validate model simulations and experimentally determine hydrodynamic parameters needed for reactive transport modeling that are otherwise estimated with a high degree of uncertainty.

To promote FAIR principles and to improve the value and knowledge from data innovation, HIFIS – a Helmholtz IT platform, provides a wide variety of services. This talk focuses on the lessons learned and the impact of integrating a variety of RSE offers, including educational resources and consulting on the research community in Helmholtz. We discuss the structure of the HIFIS consulting service and the resources needed to provide a good and fruitful environment for improving our clients’ software projects.

The metal-rich phosphide TaCrP forms from the elements by step-wise solid state reaction in an alumina crucible (maximum annealing temperature 1180 K). TaCrP is trimorphic. The structural data of the hexagonal ZrNiAl high-temperature phase (space group P¯62m) was deduced from a Rietveld refinement. At room temperature TaCrP crystallizes with the TiNiSi type (Pnma, a = 623.86(5), b = 349.12(3), c = 736.78(6) pm, wR = 0.0419, 401 F2 values, 20 variables) and shows a Peierls type transition below ca. 280 K to the monoclinic low-temperature modification (P121/c1, a = 630.09(3), b = 740.3(4), c = 928.94(4) pm, β = 132.589(5)°, wR = 0.0580, 1378 F2 values, 57 variables). The latter phase transition is driven by pairwise Cr–Cr bond formation out of an equidistant chain in o-TaCrP. The phase transition was monitored via different analytical tools: differential scanning calorimetry, powder synchrotron X-ray diffraction, magnetic susceptibility measurements and 31P solid state NMR spectroscopy.

The interlayer interaction in Pt-dichalcogenides strongly affects their electronic structures. The modulations of the interlayer atom-coordination in vertical heterostructures based on these materials are expected to laterally modify these interlayer interactions and thus provide an opportunity to texture the electronic structure. To determine the effects of local variation of the interlayer atom coordination on the electronic structure of PtSe₂, van der Waals heterostructures of PtSe₂ and PtTe₂ have been synthesized by molecular beam epitaxy. The heterostructure forms a coincidence lattice with 13-unit cells of PtSe₂ matching 12-unit cells of PtTe₂, forming a moiré superstructure. The interaction with PtTe₂ reduces the band gap of PtSe₂ monolayers from 1.8 to 0.5 eV. While the band gap is uniform across the moiré unit cell, STS and dI/dV mapping identify gap states that are localized within certain regions of the moiré unit cell. Deep states associated with chalcogen pz-orbitals at binding energies of ~-2 eV also exhibit lateral variation within the moiré unit cell, indicative of varying interlayer chalcogen interactions. Density functional theory calculations indicate that local variations in atom coordination in the moiré unit cell causes variations in the charge transfer from PtTe2 to PtSe2 thus affecting the value of the interface dipole. Experimentally this is confirmed by measuring the local work function by field emission resonance spectroscopy, which reveals a large work function modulation of ~0.5 eV within the moiré structure. These results show that the local coordination variation of the chalcogen atoms in the PtSe2/PtTe2 van der Waals heterostructure induces a nanoscale electronic structure texture in PtSe₂.

The inventors of the Julia programming language proclaim, that one can use high-level syntax to solve demanding numerical tasks. In order to evaluate this claim, we present possible applications of Julia by using it for the implementation of our Monte-Carlo event generator for laser-matter interaction. Especially the possible deployment of modern GPUs for demanding computing tasks during several stages of the event generation is discussed. In order to elaborate on these GPU capabilities, we show benchmarks of Julia's main programming interface for NVIDIA CUDA GPUs, namely `CUDA.jl`, and compare them with native CUDA-C++ implementations. Finally, Julia's capabilities for high-level abstraction for computations on heterogenous architectures are discussed and compared to low-level solutions like the `alpaka` library for C++.

Auf der ACHEMA 2022 waren in Frankfurt 25 Anbieter von Klassierer-, Sortier-, Recycling- oder Aufbereitungsanlagen im engeren Sinne vertreten. Der vorliegende Bericht fasst kurz zusammen, welche Aussteller ihr Portfolio im Bereich der Mechanischen Prozesse vorstellten und was an Neuerungen gezeigt wurde. Schwerpunkte stellten u. a. Plan- und Taumelsiebmaschinen sowie Technologien für schnelle Siebbelagswechsel und zum Entfernen von Körnern außerhalb der Produktspezifikation dar.

Auf der ACHEMA 2022 waren in Frankfurt 38 Anbieter von Zerkleinerungstechnik vertreten. Der vorliegende Bericht fasst kurz zusammen, welche Aussteller vertreten waren und was – vor allem an Neuerungen – gezeigt wurde. Schwerpunkte waren einerseits Maschinen zum Dispergieren verklumpter bzw. sehr feinkörniger Pulver zur besseren Verarbeitbarkeit oder zum Einmischen in Flüssigkeiten sowie andererseits Mahlkörpermühlen zur Fein- und Feinstmahlung.

Variable resolution fluctuation electron microscopy experiments were performed on self-ion implanted amorphous silicon and amorphous germanium to analyze the medium-range order. The results highlight that the commonly used pair-persistence analysis is influenced by the experimental conditions. Precisely, the structural correlation length Λ, a metric for the medium-range order length scale in the material, obtained from this particular evaluation varies depending on whether energy filtering is used to acquire the data. In addition, Λ depends on the sample thickness. Both observations can be explained by the fact that the pair-persistence analysis utilizes the experimentally susceptible absolute value of the normalized variance obtained from fluctuation electron microscopy data. Instead, plotting the normalized variance peak magnitude over the electron beam size offers more robust results. This evaluation yields medium-range order with an extent of approximately (1.50± 0.50)nm for the analyzed amorphous germanium and around (1.10±0.20)nm for amorphous silicon

The generally accepted view is that CSCs hijack the signaling pathways attributed to normal stem cells that regulate the self-renewal and differentiation processes. Therefore, the development of selective targeting strategies for CSC, although clinically meaningful, is associated with significant challenges because CSC and normal stem cells share many important signaling mechanisms for their maintenance and survival. Furthermore, the efficacy of this therapy is opposed by tumor heterogeneity and CSC plasticity. While there have been considerable efforts to target CSC populations by the chemical inhibition of the developmental pathways such as Notch, Hedgehog (Hh), and Wnt/β-catenin, noticeably fewer attempts were focused on the stimulation of the immune response by CSC-specific antigens, including cell-surface targets. Cancer immunotherapies are based on triggering the anti-tumor immune response by specific activation and targeted redirecting of immune cells toward tumor cells. This review is focused on CSC-directed immunotherapeutic approaches such as bispecific antibodies and antibody-drug candidates, CSC-targeted cellular immunotherapies, and immune-based vaccines. We discuss the strategies to improve the safety and efficacy of the different immunotherapeutic approaches and describe the current state of their clinical development.

In exploring terminal nickel-oxo complexes, postulated to be the active oxidant in natural and non-natural oxidation reactions, we report the synthesis of the pseudo-trigonal bipyramidal Ni(II) complexes (K)[Ni(II)(LPh)(DMF)] (1[DMF]) and (NMe₄)₂[Ni(II)(LPh)(OAc)] (1[OAc]) (LPh = 2,2’,2’’-nitrilo-tris-(N-phenylacetamide); DMF = N,N-dimethylformamide; OAc = acetate). Both complexes were characterized using NMR, FTIR, ESI-MS, and X-ray crystallography, showing the LPh ligand to bind in a tetradentate fashion, together with an ancillary donor. The reaction of 1[OAc] with peroxyphenyl acetic acid (PPAA) resulted in the formation of [(LPh)Ni(III)-O-H···OAc]²-, 2, that displays many of the characteristics of a terminal Ni=O species. 2 was characterized by UV-Vis, EPR, and XAS spectroscopies and ESI-MS. 2 decayed to yield a Ni(II)-phenolate complex 3 (through aromatic electrophilic substitution) that was characterized by NMR, FTIR, ESI-MS, and X-ray crystallography. 2 was capable of hydroxylation of hydrocarbons and epoxidation of olefins, as well as oxygen atom transfer oxidation of phosphines at exceptional rates. While the oxo-wall remains standing, this complex represents an excellent example of a masked metal-oxide that displays all of the properties expected of the ever elusive terminal M=O beyond the oxo-wall.

Bacteria primarily live in structured environments, such as colonies and biofilms, attached to surfaces or growing within soft tissues. They are engaged in local competitive and cooperative interactions impacting our health and well-being, for example, by affecting population-level drug resistance. Our knowledge of bacterial competition and cooperation within soft matrices is in-complete, partly because we lack high-throughput tools to quantitatively study their interactions. Here, we introduce a method to generate a large amount of agarose microbeads that mimic the natural culture conditions experienced by bacteria to co-encapsulate two strains of fluores-cence-labeled Escherichia coli. Focusing specifically on low bacterial inoculum (1–100 cells/capsule), we demonstrate a study on the formation of colonies of both strains within these 3D scaffolds and follow their growth kinetics and interaction using fluorescence microscopy in highly replicated experiments. We confirmed that the average final colony size is inversely proportional to the inoculum size in this semi-solid environment as a result of limited available resources. Further-more, the colony shape and fluorescence intensity per colony are distinctly different in mono-culture and co-culture. The experimental observations in mono- and co-culture are compared with predictions from a simple growth model. We suggest that our high throughput and small foot-print microbead system is an excellent platform for future investigation of competitive and co-operative interactions in bacterial communities under diverse conditions, including antibiotics stress.

This article provides a comprehensive overview of the STRUMAT-LTO project. Embrittlement of the reactor pressure vessel (RPV) due to neutron irradiation and high temperature conditions impose critical challenges for long-term operation (LTO) of pressurized water reactors (PWRs). Significant amount of past research conducted on RPV ageing phenomena has helped to enhance the understanding of the flux effect and the impact of chemical/microstructural heterogeneities on RPV embrittlement. Nonetheless, several unresolved questions regarding RPV embrittlement persist, such as the conflicting viewpoints on the underlying mechanisms that lead to accelerated embrittlement at high fluence conditions in certain low-copper (Cu) RPV steels and the synergistic
effect between nickel, manganese, and silicon (Ni-Mn-Si). Also, the accuracy of embrittlement trend curves (ETCs) for LTO beyond 60 years and the applicability of the master curve approach at high fluences for small/sub-sized specimens require further study. The aim of the STRUMAT-LTO is to address the above-mentioned scientific gaps in RPV embrittlement by employing a unique set of RPV steel specimens constituting systematic variations in Ni, Mn, and Si content, which are irradiated to high fluences resembling reactor operation beyond 60 years within the LYRA-10 experiment at high flux reactor (HFR) in Petten. The STRUMAT-LTO project has received funding from the Euratom research and training programme 2019–2020 under grant agreement
n◦945272. The project has a duration of 48 months.

Chiral effects originate from the lack of inversion symmetry within the lattice unit cell or sample’s shape. Being mapped onto magnetic ordering, chirality enables topologically non-trivial textures with a given handedness. Here, we demonstrate the existence of a static 3D texture characterized by two magnetochiral parameters being magnetic helicity of the vortex and geometrical chirality of the core string itself in geometrically curved asymmetric permalloy cap with a size of 80 nm and a vortex ground state. We experimentally validate the nonlocal chiral symmetry breaking effect in this object, which leads to the geometric deformation of the vortex string into a helix with curvature 3 μm−1 and torsion 11 μm−1. The geometric chirality of the vortex string is determined by the magnetic helicity of the vortex texture, constituting coupling of two chiral parameters within the same texture. Beyond the vortex state, we anticipate that complex curvilinear objects hosting 3D magnetic textures like curved skyrmion tubes and hopfions can be characterized by multiple coupled magnetochiral parameters, that influence their statics and field- or current-driven dynamics for spin-orbitronics and magnonics.

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.

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.

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.

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.

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.

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

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

Machine Learning is becoming ubiquitous in many scientific domains. However, practitioners struggle to apply every new addition to the Machine Learning market on their data with comparable effects than published. In this talk, I'd like to present recent observations on reproducibility of Machine Learning results and how the community strives to tackle related challenges.

Detection of antigens and antibodies (Abs) is of great importance in determining the infection and immunity status of the population, as they are key parameters guiding the handling of pandemics. Current point-of-care (POC) devices are a convenient option for rapid screening; however, their sensitivity requires further improvement. We present an interdigitated gold nanowire-based impedance nanobiosensor to detect COVID-19-associated antigens (receptor-binding domain of S1 protein of the SARS-CoV-2 virus) and respective Abs appearing during and after infection. The electrochemical impedance spectroscopy technique was used to assess the changes in measured impedance resulting from the binding of respective analytes to the surface of the chip. After 20 min of incubation, the sensor devices demonstrate a high sensitivity of about 57 pS·sn per concentration decade and a limit of detection (LOD) of 0.99 pg/mL for anti-SARS-CoV-2 Abs and a sensitivity of around 21 pS·sn per concentration decade and an LOD of 0.14 pg/mL for the virus antigen detection. Finally, the analysis of clinical plasma samples demonstrates the applicability of the developed platform to assist clinicians and authorities in determining the infection or immunity status of the patients.

The PyTorch implementation of SQNN is available on Github at https://github.com/darthsimpus/ASOC

Deep Convolutional Neural Network (CNN)-based image classification systems are often susceptible to noise interruption, i.e., minor image noise may significantly impact the outcome. On the contrary, classical Spiking Neural Network (SNN) is known for handling noisy data due to the stochastic and temporal behaviour of the spiking neuron signals. However, it is not always feasible to train the weights of the classical SNN due to stochastic and non-differentiable spiking signals. Recent applications of quantum machine learning to stochastic modelling have predicted that quantum computing would prove to be a significant advantage, hence catapulting the study of quantum and neuromorphic computing to a new level of development. Motivated by these observations, this paper introduces a shallow hybrid classical-quantum spiking feedforward neural network referred to as Spiking Quantum Neural Network (SQNN) for dealing with a robust image classification task in the presence of noise and adversarial attacks. The proposed SQNN offers the inherent capabilities of processing unforeseen noisy test images due to its spatial and temporal information. An efficient variational quantum circuit training with the help of a standard back-propagation algorithm obviates the classical Spiking Time-Dependent Plasticity (STDP) and Spike-Prop algorithms, which are often found inefficient in training the feedforward SNN. The proposed SQNN is extensively tested and benchmarked on the PennyLane Quantum Simulator. Experimental results show that the proposed SQNN model supersedes the feedforward SNN (SFNN), Random Quantum Neural Networks (RQNN), AlexNet and ResNet-18 on unseen test images with added noise from the FashionMNIST, MNIST, KMNIST, CIFAR10, and ImageNet datasets.

Mineral dissolution is a dynamic process in which kinetics depend on the reactive surface area, orientation, and geometry of the dissolving mineral grain. Dissolution rate is, thus, not represented by a single value, but rather, by a spectrum that is affected by the reactivity of different types of surface features. Such dissolution rate spectra are usually obtained by very detailed studies of perfectly cleaved surfaces by atomic force microscopy or in situ studies, such as flow-through experiments. This study visualizes dissolution progress by repeated X-ray computed tomography scans of a single particle. This allows studying the influence of larger particle features, such as corners and edges, at the interception of macroscopic faces of particles, as well as the influence of those macroscopic features on the dissolution rate spectra. As a suitable case study, the dissolution of a monomineralic galena (PbS) particle in ethaline is studied. The observed changes in particle geometry are evaluated using a newly developed empirical model in order to break down the rate spectra as a function of the particle geometry. Results illustrate that dissolution rates are exponentially correlated with the distance to crystal corners and edges. The reactivity map generated from these exponential relations shows a linear trendline with the dissolution rates over the entire surface of the studied galena particle. The empirical reactivity map developed here opens the possibility of predicting the dissolution rate of particulate materials based on computed tomography and the optimal geometrical properties of the particles that maximize the dissolution, e.g., size and shape.

Technical Meeting

New Horizons in Imaging and Therapy

Young DGN Fortbildung

This work discusses the influence of different cleaning procedures on p-GaN grown on sap-phire by metal-organic chemical vapor deposition. The cleaned p-GaN surface was trans-ferred into an ultra-high vacuum chamber and studied by an X-ray photoelectron spectrome-ter, revealing that a cleaning with a so-called „piranha“ procedure results in low carbon and oxygen concentrations on the p-GaN surface. Contrary, a cleaning that solely uses ethanol represents a simple cleaning, but leads to an increase of carbon and oxygen contaminations on the surface. Afterward, the cleaned p-GaN samples underwent a subsequential vacuum thermal cleaning at various temperatures to achieve an atomically clean surface. XPS meas-urements revealed residual oxygen and carbon on the p-GaN surface. Thus, a thermal treat-ment under a vacuum did not entirely remove these organic contaminations, although the thermal cleaning reduced their peak intensities. The complete removal of carbon and oxygen contaminants was only achieved by argon ion sputtering, which is accompanied by a strong depletion of the nitrogen on the p-GaN surface. The treatments cause a large number of sur-face defects preventing the formation of a negative electron surface when the p-GaN is acti-vated with a thin layer of cesium.

Stochastic simulations of complex systems from domains including physics, biology, ecology or economics often require large system sizes, long time scales, and numerous replications
to fully explore model behavior. The simple rules defining many models can lead researchers
to prefer familiar but inefficient programming techniques, which severely hinder progress
by creating computational bottlenecks. While such studies often benefit from combined
domain-specific, statistical, and programming knowledge, few individual researchers span
the full range of necessary skills. Here, we present a collaboration on the neutral model
of biodiversity in dendritic river networks, where the goal is to analyze biodiversity data
across the world’s major river systems. We show how we achieved large performance gains
by engaging the problem at its foundations and thereby enabled research at a new scale.

Helical polyalanine (PA) molecules gathered a lot of interest as the propagation of electrons along the helical backbone structure comes along with spin polarization. Via liquid and solid scanning tunneling microscopy (STM) we studied the ordering of physisorbed and chemisorbed PA molecules on HOPG and Au surfaces. While enantiopure PA molecules adsorb in a hexagonally close-packed structure, we found heterochiral dimers with a rectangular unit cell for DL-PA. Despite the steric hindrance, the packing density of the DL-PA heterophase is increased by 25% compared to the enantiopure PA structure. Apparently, this is achieved by shifting D- and L-PA along their helical axis. Moreover, the alpha-helix structure of the PA molecules seems to be preserved; thus, electrostatic forces indeed play an important role for the formation and stabilization of the helical structure. In parallel, the interactions between PA homo- and heterochiral pairs were analyzed by van-der-Waals-corrected DFT-based tight binding calculations. Denser packing geometries can be reached by heterochiral PA pairs. Second, coarse-grained classical potentials were derived from the DFTB data, and the different PA phases seen in STM were also successfully obtained from Monte-Carlo simulations.

Complex, hierarchical or random network topolgies can give rise to unique behavior in many physical models. We study dynamical synchronization behavior in Kuramoto models on power grids and brain connectomes with millons of connections and O(100k) nodes. At these scales it is crucial to use the sparsity when computing derivatives, which, due to the random network structure, makes employing modern parallel hardware tricky. Here, we present our approach to numerically solving large systems ordinary differential equations on random directed graphs, where we focus on the computationally expensive task of computing derivatives and leave the common integration step to the boost::odeint library. Our application can utilize both parallel CPUs and GPUs. We also provide an overview of our results on human and fly brain connectomes as well as failure cascades in power grids and provide a measure of the advantage gained from our computational optimization efforts.

The neutral model of biodiversity describes a Markov process of death and replacement of neutral individuals constituting the species occupying an ecosystem. It predicts a number macroscopic ecosystem observables, including local and global abundances, and can serve as advanced null-hypothesis for more complex models. We present a massively parallel approach to simulating the neutral model which both enables simulations on large networks, to, e.g., capture fine details of real river networks, and efficiently produces averages results to enable comparisons with empirical data or other models at high statistical significance or accurately compute correlations or responses.

Metal aerogels assembled from nanoparticles have captured grand attention because they combine the virtues of metals and aerogels and are regarded as ideal materials to address current environmental and energy issues. Among these aerogels, those composed of two metals not only display combinations (superpositions) of the properties of their individual metal components but also feature novel properties distinctly different from those of their monometallic relatives. Therefore, quite some effort has been invested in refining the synthetic methods, compositions, and structures of such bimetallic aerogels as to boost their performance for the envisaged application(s). One such use would be in the field of electrocatalysis, whereby it is also of utmost interest to unravel the element distributions of the (multi)metallic catalysts to achieve a ratio of their bottom-to-up design. Regarding the element distributions in bimetallic aerogels, advanced characterization techniques have identified alloys, core-shells, and structures in which the two metal particles are segregated (i.e., adjacent but without alloy or core-shell structure formation). While an almost infinite number of metal combinations to form bimetallic aerogels can be envisaged, the knowledge of their formation mechanisms and the corresponding element distributions is still in its infancy. The evolution of the observed musters is all but well understood, not to mention the positional changes of the elements observed in operando or in beginning- vs end-of-life comparisons (e.g., in fuel cell applications).
With this motivation, in this Account we summarize the endeavors made in element distribution monitoring in bimetallic aerogels in terms of synthetic methods, expected structures, and their evolution during electrocatalysis. After an introductory chapter, we first describe briefly the two most important characterization techniques used for this, namely, scanning transmission electron microscopy (STEM) combined with element mapping (e.g., energy-dispersive X-ray spectroscopy (EDXS)) and X-ray absorption spectroscopy (XAS). We then explain the universal methods used to prepare bimetallic aerogels with different compositions. Those are divided into one-step methods in which gels formed from mixtures of the respective metal salts are coreduced and two-step approaches in which monometallic nanoparticles are mixed and gelated. Subsequently, we summarize the current state-of-knowledge on the element distributions unraveled using diverse characterization methods. This is extended to investigations of the element distributions being altered during electrochemical cycling or other loads. So far, a theoretical understanding of these processes is sparse, not to mention predictions of element distributions. The Account concludes with a series of remarks on current challenges in the field and an outlook on the gains that the field would earn from a solid understanding of the underlying processes and a predictive theoretical backing.

Biomedical research with laser-driven ion sources

Exploiting the strong electromagnetic fields that can be supported by a plasma, high-power laser driven compact plasma accelerators can generate short, high-intensity pulses of high energy ions with special beam properties. By that they may expand the portfolio of conventional machines in many application areas. The maturating of laser-driven ion accelerators from physics experiments to turn-key sources for these applications will rely on breakthroughs in both, generated beam parameters (kinetic energy, flux), as well as increased reproducibility, robustness and scalability to high repetition rate.
Recent developments at the high-power laser facility DRACO-PW enabled the production of polychromatic proton beams with unprecedented stability [1]. This allowed the first in vivo radiobiological study to be conducted using a laser-driven proton source [2]. Yet, the ability to achieve energies beyond the 100 MeV frontier is matter of ongoing research, mainly addressed by exploring advanced acceleration schemes like the relativistically induced transparency (RIT) regime.
In this talk, we report on experimental proton acceleration studies at the onset of relativistic transparency using pre-expanded plastic foils. Combined hydrodynamic and 3D particle-in-cell (PIC) simulations helped to identify the most promising target parameter range matched to the prevailing laser contrast conditions carefully mapped out in great detail beforehand. A complex suite of particle and optical diagnostics allowed characterization of spatial and spectral proton beam parameters and the stability of the regime of best acceleration performance, yielding cut-off energies larger than 100 MeV in the best shots.
The reported progress for proton acceleration directly feeds into our program on ultra-high dose rate radiobiology. We operate a fully-equipped beamline including beam monitoring and dosimetry adapted to ultra-high dose rate proton pulses at DRACO-PW with the future perspective of a dedicated beamline at our high-power laser facility PENELOPE within the ATHENA project.

References
[1] Ziegler, T. et al. Proton beam quality enhancement by spectral phase control of a PW-class laser system. Sci Rep 11, 7338 (2021)
[2] Kroll, F. et al. Tumour irradiation in mice with a laser-accelerated proton beam. Nat. Phys. 18, 316–322 (2022)

Exploiting the strong electromagnetic fields that can be supported by a plasma, high-power laser driven compact plasma accelerators can generate short, high-intensity pulses of high energy ions with special beam properties. By that they may expand the portfolio of conventional machines in many application areas. The maturating of laser-driven ion accelerators from physics experiments to turn-key sources for these applications will rely on breakthroughs in both, generated beam parameters (kinetic energy, flux), as well as increased reproducibility, robustness and scalability to high repetition rate.
Recent developments at the high-power laser facility DRACO-PW enabled the production of polychromatic proton beams with unprecedented stability [1]. This allowed the first in vivo radiobiological study to be conducted using a laser-driven proton source [2]. Yet, the ability to achieve energies beyond the 100 MeV frontier is matter of ongoing research, mainly addressed by exploring advanced acceleration schemes like the relativistically induced transparency (RIT) regime.
In this talk, we report on experimental proton acceleration studies at the onset of relativistic transparency using pre-expanded plastic foils. Combined hydrodynamic and 3D particle-in-cell (PIC) simulations helped to identify the most promising target parameter range matched to the prevailing laser contrast conditions carefully mapped out in great detail beforehand. A complex suite of particle and optical diagnostics allowed characterization of spatial and spectral proton beam parameters and the stability of the regime of best acceleration performance, yielding cut-off energies larger than 100 MeV in the best shots.
The reported progress for proton acceleration directly feeds into our program on ultra-high dose rate radiobiology. We operate a fully-equipped beamline including beam monitoring and dosimetry adapted to ultra-high dose rate proton pulses at DRACO-PW with the future perspective of a dedicated beamline at our high-power laser facility PENELOPE within the ATHENA project.

References
[1] Ziegler, T. et al. Proton beam quality enhancement by spectral phase control of a PW-class laser system. Sci Rep 11, 7338 (2021)
[2] Kroll, F. et al. Tumour irradiation in mice with a laser-accelerated proton beam. Nat. Phys. 18, 316–322 (2022)

Quasi-two-dimensional (2D) manganese phosphorus trisulfide, MnPS₃, which exhibits antiferromagnetic ordering, is a particularly interesting material in the context of magnetism in a system with reduced dimensionality and its potential technological applications. Here, we present an experimental and theoretical study on modifying the properties of freestanding MnPS₃ by local structural transformations via electron irradiation in a transmission electron microscope and thermal annealing in vacuum. In both cases we find that phases with the net formula MnS₁₋ₓPₓ in the α- or γ-MnS crystal structure can be formed. The phase transformations can be locally and precisely controlled by the total applied electron dose and explored at the atomic scale. For the MnS structures generated in this process, our ab-initio calculations indicate that their electronic and magnetic properties strongly depend on both in-plane crystallite orientation and thickness. Moreover, the electronic properties of the MnS phases can be further tuned by alloying with phosphorus, suggesting a novel route toward the design of lateral heterostructures. Therefore, our results may enable pathways for the controlled growth of new phases with distinct properties embedded in freestanding quasi-2D MnPS₃.

A new ultra low-level counting setup has been installed in the shallow-underground laboratory Felsenkeller in Dresden, Germany. It includes a high-purity germanium detector (HPGe) of 163\% relative efficiency within passive and active shields. The passive shield consists of 45m rock overburden (140 meters water equivalent), 40 cm of low-activity concrete, and a lead and copper castle enclosed by an anti-radon box. The passive shielding alone is found to reduce the background rate to rates comparable to other shallow-underground laboratories. An additional active veto is given by five large plastic scintillation panels surrounding the setup. It further reduces the background rate by more than one order of magnitude down to 116±1 kg−1 d−1 in an energy interval of 40-2700 keV. This low background rate is unprecedented for shallow-underground laboratories and close to deep underground laboratories.

Extending 2D structures into 3D space has become a general trend in multiple disciplines, including electronics, photonics, plasmonics, superconductivity and magnetism [1,2]. This approach provides means to modify conventional or to launch novel functionalities by tailoring curvature and 3D shape of magnetic thin films and nanowires [2,3]. In this talk, we will address fundamentals of curvature-induced effects in magnetism and review current application scenarios. In particular, we will demonstrate that curvature allows tailoring fundamental anisotropic and chiral magnetic interactions [4] and enables fundamentally new non-local chiral symmetry breaking effect [5]. Application potential of geometrically curved magnetic architectures is currently being explored as mechanically reshapeable magnetic field sensors for automotive applications, memory, spin-wave filters, high-speed racetrack memory devices as well as on-skin interactive electronics relying on thin films [6,7] as well as printed magnetic composites [8,9].

[1] P. Gentile et al., Electronic materials with nanoscale curved geometries. Nature Electronics (Review) 5, 551 (2022).
[2] D. Makarov et al., New Dimension in Magnetism and Superconductivity: 3D and Curvilinear Nanoarchitectures. Advanced Materials (Review) 34, 2101758 (2022).
[3] D. Makarov et al., Curvilinear micromagnetism: from fundamentals to applications (Springer, Zurich, 2022).
[4] O. Volkov et al., Experimental observation of exchange-driven chiral effects in curvilinear magnetism. Physical Review Letters 123, 077201 (2019).
[5] D. D. Sheka et al., Nonlocal chiral symmetry breaking in curvilinear magnetic shells. Communications Physics 3, 128 (2020).
[6] J. Ge et al., A bimodal soft electronic skin for tactile and touchless interaction in real time. Nature Communications 10, 4405 (2019).
[7] G. S. Canon Bermudez et al., Electronic-skin compasses for geomagnetic field driven artificial magnetoception and interactive electronics. Nature Electronics 1, 589 (2018).
[8] M. Ha et al., Printable and Stretchable Giant Magnetoresistive Sensors for Highly Compliant and Skin-Conformal Electronics. Advanced Materials 33, 2005521 (2021).
[9] R. Xu et al., Self-healable printed magnetic field sensors using alternating magnetic fields. Nature Communications 13, 6587 (2022).

The talk will be about theoretical description of magnetic soft robots at different scales starting from the macroscopic actuators based on polymer membranes to properties of nanoscaled mechanically soft exchange-coupled systems.

The reaction of (NMe₄)₂[Ni(II)(LPh)(OAc)] (1[OAc], LPh = 2,2’,2’’-nitrilo-tris-(N-phenylacetamide); OAc = acetate) with 3-chloroperoxybenzoic acid (m-CPBA) resulted in the formation of a self-hydroxylated Ni(III)- phenolate complex, 2, where one of the phenyl groups of LPh underwent hydroxylation. 2 was characterised by UV-Vis, EPR, and XAS spectroscopies and ESI-MS. 2 decayed to yield a previously characterised Ni(II)-phenolate complex, 3. We postulate that self-hydroxylation was mediated by a formally Ni(IV)=O oxidant, formed from the reaction of 1[OAc] with m-CPBA, which undergoes electrophilic aromatic substitution to yield 2. This is supported by an analysis of the kinetic and thermodynamic properties of the reaction of 1[OAc] with m-CPBA. Addition of exogenous hydrocarbon substrates intercepted the selfhydroxylation process, producing hydroxylated products, providing further support for the formally Ni(IV)=O entity. This study demonstrates that the reaction between Ni(II) salts and m-CPBA can lead to potent metal-based oxidants, in contrast to recent studies demonstrating carboxyl radical is a radical free-chain reaction initiator in Ni(II)/m-CPBA hydrocarbon oxidation catalysis.

The coherent infrared and THz sources driven by the superconducting electron accelerator ELBE are described. The present status of the facility is summarized and a few scientific highlights are mentioned. Finally plans for a successor facility (Dresden Advanced Light Infrastructure, DALI) are outlined along with the most important scientific and technological challenges.

Due to its importance as an astronomical observable in core-collapse supernovae (CCSNe), the reactions producing and destroying 44Ti must be well constrained. Generally, statistical model calculations such as Hauser-Feshbach are employed when experimental cross sections are not available, but the variation in such adopted rates can be large. Here, data from the literature is compared with statistical model calculations of the 44Ti(α,p)47V reaction cross section and used to constrain the possible reaction rate variation over the temperatures relevant to CCSNe. Suggestions for targeted future measurements are given.

The production of Σ0 hyperons in proton proton collisions at a beam kinetic energy of 3.5 GeV impinging on a liquid hydrogen target was investigated using data collected with the HADES setup. The total production cross section is found to be σ(pK+Σ0)[μb]=17.7±1.7(stat)±1.6(syst). Differential cross section distributions of the exclusive channel pp→pK+Σ0 were analyzed in the center-of-mass, Gottfried-Jackson and helicity reference frames for the first time at the excess energy of 556 MeV. The data support the interplay between pion and kaon exchange mechanisms and clearly demonstrate the contribution of interfering nucleon resonances decaying to K+Σ0. The Bonn-Gatchina partial wave analysis was employed to analyse the data. Due to the limited statistics, it was not possible to obtain an unambiguous determination of the relative contribution of intermediate nucleon resonances to the final state. However nucleon resonances with masses around 1.710 GeV/c2 (N∗(1710)) and 1.900 GeV/c2 (N∗(1900) or Δ∗(1900)) are preferred by the fit.

The double differential production cross sections, d2σ/dΩdE, for hydrogen isotopes and charged pions in the reaction of p + Nb at 3.5 GeV proton beam energy have been measured by the High Acceptance DiElectron Spectrometer (HADES). Thanks to the high acceptance of HADES at forward emission angles and usage of its magnetic field, the measured energy range of hydrogen isotopes could be significantly extended in comparison to the relatively scarce experimental data available in the literature. The data provide information about the development of the intranuclear cascade in the proton-nucleus collisions. They can as well be utilized to study the rate of energy/momentum dissipation in the nuclear systems and the mechanism of elementary and composite particle production in excited nuclear matter at normal density. Data of this type are important also for technological and medical applications. Our results are compared to models developed to describe the processes relevant to nuclear spallation (INCL++) or oriented to probe either the elementary hadronic processes in nuclear matter or the behavior of compressed nuclear matter (GiBUU).

Hadron production (π±, proton, Λ, K0S, K±) in π−+C and π−+W collisions is investigated at an incident pion beam momentum of 1.7 GeV/c. This comprehensive set of data measured with HADES at SIS18/GSI significantly extends the existing world data on hadron production in pion induced reactions and provides a new reference for models that are commonly used for the interpretation of heavy-ion collisions. The measured inclusive differential production cross-sections are compared with state-of-the-art transport model (GiBUU, SMASH) calculations. The (semi-) exclusive channel π−+A→Λ+K0S+X, in which the kinematics of the strange hadrons are correlated, is also investigated and compared to a model calculation. Agreement and remaining tensions between data and the current version of the considered transport models are discussed

We find that the proton separation energy, S(p), of 73Rb is −640(40) keV, deduced from the observation of β-delayed ground-state protons following the decay of 73Sr. This lower-limit determination of the proton separation energy of 73Rb coupled with previous upper limits from nonobservation, provides a full constraint on the mass excess with ΔM(73Rb)=−46.01±0.04 MeV. With this new mass excess and the excitation energy of the Jπ=5/2− isobaric-analog state (T=3/2) in 73Rb, an improved constraint can be put on the mass excess of 73Sr using the isobaric-multiplet mass equation (IMME), and we find ΔM(73Sr)=−31.98±0.37 MeV. These new data were then used to study the composition of ashes on accreting neutron stars following Type I x-ray bursts. Counterintuitively, we find that there should be an enhanced fraction of A>102 nuclei with more negative proton separation energies at the 72Kr rp-process waiting point. Larger impurities of heavier nuclei in the ashes of accreting neutron stars will impact the cooling models for such astrophysical scenarios.

´Objectives:

The emerging significance of the tumor microenvironment (TME) as a new frontier for cancer diagnosis and therapy can be primarily attributed to its unique features, such as the interconnection between stromal and cancer cells.1 Cancer-associated fibroblasts (CAFs) within the TME are identified by biomarkers such as fibroblast activation protein alpha (FAP), which are expressed on their surfaces. Targeting FAP using small molecule 18F-labeled inhibitors (FAPIs) have recently garnered significant attention for noninvasive tumor visualization using PET.2 Currently, the predominant 18F-fluorination method for radiolabeling FAPIs involves chelation-based radiofluorination strategies using aluminum [18F]fluoride ([18F]AlF). Herein, a powerful radiofluorination protocol for the preparation of an 18F-labeled FAPI via the sulfur [18F]fluoride exchange ([18F]SuFEx) reaction is disclosed.3
Methods:

The incorporation of the aryl fluorosulfate motif into the linker of the FAPI core structure (2) via amide bond formation allowed the radiolabeling precursor 3 to be accessed in moderate yield (Scheme 1 A, 46%). The radiosynthesis commenced with [18F]fluoride loading onto a QMA-cartridge which was eluted with a methanolic solution containing Et4NHCO3, followed by evaporation of the solvent under reduced pressure at 70 oC for 5 min (Scheme 1 B). Thereafter, the precursor 3 (100 µg, 145 nmol) in MeCN was added to the reaction vial, and allowed to react by [18F]SuFEx at room temperature for 5 min. The reaction was quenched by water dilution followed by SPE-based purification using a C18 cartridge. [18F]3 was isolated by elution from the cartridge with EtOH and the identity of the product was confirmed by UHPLC.

Results

The optimized radiosynthesis of 18F-labeled FAPI ([18F]3) was obtained with non-decay corrected isolated activity yields (AY) of 54 ± 3% (n = 3) and >99% RCP in 25 min. The automated radiosynthesis afforded [18F]3 in an unoptimized 11% AY, with >95% RCP and molar activity (Am) of 25 GBq/µmol (n = 1) in 30 min. The product was obtained in 2 mL EtOH, which can easily be further diluted with water or saline solution for subsequent biological evaluation.

Cadmium (Cd) is a toxic heavy metal with very low permissible exposure limits and is, thus, a very dangerous pollutant for the environment and public health and is considered by the World Health Organisation as one of the ten chemicals of major public concern. Adsorption onto solid phases and (co)precipitation processes are the most powerful mechanisms to retain pollutants and limit their migration; thus, the understanding of these processes is fundamental for assessing the risks of their presence in the environment. In this study, the immobilisation of Cd by smectite clay has been investigated by batch sorption tests, and the experimental data were interpreted with a thermodynamic model, including cation exchange and surface complexation processes. The model can describe the adsorption of Cd in smectite under a wide range of experimental conditions (pH, ionic strength, and Cd concentration). Under the conditions analysed in this study, the precipitation of otavite (CdCO₃) is shown to have a limited contribution to Cd immobilisation.