Publications Repository - Helmholtz-Zentrum Dresden-Rossendorf

Data-Driven Research for the Discovery of Novel Two-Dimensional and Ionic Material

While two-dimensional (2D) materials are traditionally derived from
bulk layered compounds bonded by weak van der Waals (vdW) forces,
the recent surprising experimental realization of non-vdW 2D compounds
obtained from non-layered crystals [1] foreshadows a new direction
in 2D systems research.
Here, we present several dozens of candidates of this novel materials
class derived from applying data-driven research methodologies
in conjunction with autonomous ab initio calculations [2,3]. We find
that the oxidation state of the surface cations of the 2D sheets is an
enabling descriptor regarding the manufacturing of these systems as
it determines their exfoliation energy: small oxidation states promote
easy peel off [2]. When extending the set from oxides to sulfides and
chlorides, the exfoliation energy becomes ultra low due to strong surface
relaxations [3]. The candidates exhibit a wide range of appealing
electronic, optical and magnetic properties making these systems an
attractive platform for fundamental and applied nanoscience.
[1] A. Puthirath Balan et al., Nat. Nanotechnol. 13, 602 (2018).
[2] R. Friedrich et al., Nano Lett. 22, 989 (2022).
[3] T. Barnowsky et al., submitted (2022).

The formation enthalpy, quantifying the enthalpy of a compound with
respect to its elemental references, is a key parameter for predicting the
thermodynamic stability of materials thus enabling data-driven materials
design. Although for instance zero-point vibrational and thermal
contributions to the formation enthalpy can be quite substantial reaching
absolute values of up to ∼ 50 meV/atom for ionic systems such as
oxides, they are often neglected in ab initio workflows.
Here, we first calculate the thermal and zero-point contributions accurately
from a quasi-harmonic Debye model. At room temperature,
they largely cancel each other due to the different bond stiffness of
compound and references reducing the total vibrational contribution
to maximally ∼ 20 meV/atom [1]. Moreover, the vibrational contributions
can be parametrized within the coordination corrected enthalpies
(CCE) method completely eliminating the need to compute
these terms explicitly. On this basis, using only 0 K ab initio data
as input, a workflow can be designed providing access to formation
enthalpies at different temperatures from the AFLOW-CCE tool [2].
[1] R. Friedrich et al., npj Comput. Mater. 5, 59 (2019).
[2] R. Friedrich et al., Phys. Rev. Mater. 5, 043803 (2021).

While two-dimensional (2D) materials are traditionally associated with bulk layered compounds
bonded by weak van der Waals (vdW) interactions, the recent surprising experimental realization of
non-vdW 2D compounds obtained from non-layered crystals [1,2] opens up a new direction in 2D
systems research. These materials show several distinct differences to traditional 2D sheets as their
surface was revealed to be terminated by cations rather than anions. Here, we outline several
dozens of candidates of this novel materials class derived from employing data-driven research
principles in conjunction with autonomous ab initio calculations [3,4] (Figure 1). The oxidation state
of the surface cations of the 2D sheets turns out to be an enabling descriptor regarding the
manufacturing of these systems as it determines their exfoliation energy: small oxidation states
promote easy peel off [3]. When extending the set from oxides to sulfides and chlorides, the
exfoliation energy becomes ultra low due to strong surface relaxations [4]. The materials also pass
several tests validating their vibrational and dynamic stability. The candidates exhibit a wide range of
appealing electronic, optical and in particular magnetic properties making these systems an
attractive platform for fundamental and applied nanoscience.
References
[1] A. Puthirath Balan et al., Nat. Nanotechnol. 13 (2018) 602.
[2] A. Puthirath Balan et al., Chem. Mater. 30 (2018) 5923.
[3] R. Friedrich et al., Nano Lett. 22 (2022) 989.
[4] T. Barnowsky et al., Adv. Electron. Mater. (2023) 2201112.

In the past decades, automated high-content microscopy demonstrated its ability to deliver large quantities of image-based data powering the versatility of phenotypic drug screening and systems biology applications. However, as the sizes of image-based datasets grew, it became infeasible for humans to control, avoid and overcome the presence of imaging and sample preparation artefacts in the images. While novel techniques like machine learning and deep learning may address these shortcomings through generative image inpainting, when applied to sensitive research data this may come at the cost of undesired image manipulation. Undesired manipulation may be caused by phenomena such as neural hallucinations, to which some artificial neural networks are prone. To address this, here we evaluate the state-of-the-art inpainting methods for image restoration in a high-content fluorescence microscopy dataset of cultured cells with labelled nuclei. We show that architectures like DeepFill V2 and Edge Connect can faithfully restore microscopy images upon fine-tuning with relatively little data. Our results demonstrate that the area of the region to be restored is of higher importance than shape. Furthermore, to control for the quality of restoration, we propose a novel phenotype-preserving metric design strategy. In this strategy, the size and count of the restored biological phenotypes like cell nuclei are quantified to penalise undesirable manipulation. We argue that the design principles of our approach may also generalise to other applications.

D. rerio 3D microscopy and in-focus pixel segmentation.

This study presents a benchmark analysis of an unprotected loss of flow transient in a sodium-cooled fast reactor at the Fast Flux Test Facility (FFTF), carried out as part of an IAEA coordinated research project. Three codes, namely Serpent (Monte Carlo), DYN3D (3D nodal diffusion) and ATHLET (system thermal hydraulics), were employed in the benchmark exercise. Two distinct modeling approaches were utilized: 1) stand-alone ATHLET with point kinetics (PK) and system thermal hydraulics (TH); and 2) coupled DYN3D/ATHLET with spatial kinetics (SK) and system TH. Neutronics data essential for both approaches were generated using Serpent. The study is organized into three parts.

Part I presented a summary of the preparation of neutronics data for PK or coupled SK/TH simulations and included the outcomes of the static neutronics stage of the benchmark. The main focus lay on verifying the cross-section generation method for DYN3D by comparing its results against the reference Monte Carlo solutions obtained with Serpent.

Part II provides a detailed description of the ATHLET TH model of the system. This model is thoroughly evaluated by comparing the results with the ANL benchmark solution and experimental data for the transient. Furthermore, a sensitivity analysis is conducted to explore various modeling options and assess their impact on the simulation results.

Part III will showcase the transient calculation results using the two modeling approaches. Additionally, an adaptive decay heat model for nodal codes will be introduced. The performance of both modeling approaches will be assessed by comparing their results to the available experimental data.

This study presents a benchmark analysis of an unprotected loss of flow transient in a sodium-cooled fast reactor at the Fast Flux Test Facility (FFTF), carried out as part of an IAEA coordinate research project. Three codes, namely Serpent (Monte Carlo), DYN3D (3D nodal diffusion) and ATHLET (system thermal hydraulics), were employed in the benchmark exercise. Two distinct modeling approaches were utilized: 1) stand-alone ATHLET with point kinetics (PK) and system thermal hydraulics (TH); and 2) coupled DYN3D/ATHLET with spatial kinetics (SK) and system TH. Neutronics data essential for both approaches were generated using Serpent. The study is organized into three parts.

Part I presents a summary of the preparation of neutronics data for PK or coupled SK/TH simulations and includes the outcomes of the static neutronics stage of the benchmark. The main focus lies on verifying the cross-section generation method for DYN3D by comparing its results against the reference Monte Carlo solutions obtained with Serpent.

Part II will provide a detailed description of the ATHLET TH model of the system. This model will be thoroughly evaluated by comparing the results with the ANL benchmark solution and experimental data for the transient. Furthermore, a sensitivity analysis will be conducted to explore various modeling options and assess their impact on the simulation results.

Part III will showcase the transient calculation results using the two modeling approaches. Additionally, an adaptive decay heat model for nodal codes will be introduced. The performance of both modeling approaches will be assessed by comparing their results to the available experimental data.

This talk intends to address the challenge of solving Partial Differential Equations (PDEs) with smooth
or non-smooth solutions by formulating variational PDE formulations resulting in a soft-constrained
optimization problem. The flexibility of the variational formulation enables us to use hybrid non-linear
surrogates to approximate discontinuous shocks while solving forward or inverse PDE problems. We
first explore general concepts and tools necessary for solving PDEs under a variational formulation with
general non-linear surrogates and boundary conditions. We then compare the numerical performance of
Physics Informed Neural Networks (PINNs) as surrogates against Polynomial Surrogate Models (PSMs).
Our goal is to open up the discussion regarding the class of problems that genuinely require the use of
Neural Networks. Our findings indicate that PSMs outperform PINNs by several orders of magnitude in
both accuracy and runtime. Furthermore, we introduce a new method for approximating discontinuous
functions using modified global spectral methods. We extend this method to solve PDEs with nonsmooth
solutions, providing an innovative solution to a highly challenging problem.

Copper(II)–nitroxide based Cu(hfac)₂L^R compounds exhibit unusual magnetic behavior that can be induced by various stimuli. In many aspects, the magnetic phenomena observed in Cu(hfac)₂L^R are similar to classical spin-crossover behavior. However, these phenomena originate from polynuclear exchangecoupled spin clusters Cu²⁺–O^•–N< or >N–^•O–Cu²⁺–O^•–N<. Such peculiarities may result in additional multifunctionality of Cu(hfac)₂L^R compounds, making them promising materials for spintronic applications. Herein, we investigate the Cu(hfac)₂L_MeMe material, which demonstrates a three-step temperature-induced magnetostructural transition between high-temperature, low-temperature, and intermediate states, as revealed by magnetometry. Two main steps were resolved using variable-temperature Fourier-transform infrared and Q-band electron paramagnetic resonance (EPR) spectroscopies. The intermediate-temperature states (∼40–90 K) are characterized by the coexistence of two types of copper(II)–nitroxide clusters, corresponding to the low-temperature and high-temperature phases. High-field EPR experiments revealed the effect of partial alignment of Cu(hfac)₂L_MeMe microcrystals in a strong (>20 T) magnetic field. This effect was used to unveil the structural features of the low-temperature phase of Cu(hfac)₂L_MeMe, which were inaccessible using single-crystal X-ray diffraction (XRD) technique. In particular, high-field EPR allowed us to determine the relative direction of the Jahn–Teller axes in CuO₆ and CuO₄N₂ units.

Magnetorotational instability (MRI) is the most likely mechanism for efficient transport of angular momentum in accretion disks. However, despite numerous efforts, the quest for an unambiguous realization of MRI in experiments is still ongoing. To conclusively identify MRI in the laboratory, a large Taylor-Couette experiment with liquid sodium is under construction at the Helmholtz-Zentrum Dresden-Rossendorf within the DRESDYN project. Recently, we have determined the optimal range of parameters for the onset of an axisymmetric mode of the standard MRI (SMRI) with a purely axial background magnetic field and analyzed its nonlinear evolution, saturation and scaling properties in the context of the DRESDYN-MRI experiment. In this sequel paper, we continue SMRI studies and investigate the linear and nonlinear dynamics of non-axisymmetric modes of the instability in a similar magnetized Taylor-Couette setup. For the linear stability analysis, we use $Pm=\nu/\eta \sim 10^{-5}$ typical of liquid sodium used in the experiment. We show that the achievable magnetic Reynolds $Rm\sim 40$ and Lundquist $Lu\sim10$ numbers in this experiment are large enough for the growth of non-axisymmetric $|m|=1$ SMRI modes. For fixed $\mu$, the critical $Rm_c$ for the onset of non-axisymmetric SMRI is about 2-3 time higher than that of axisymmetric SMRI. We follow the evolution of these modes from their exponential growth in the linear regime all over to nonlinear saturation. The structure of the saturated state and its scaling properties with respect to Reynolds number $Re$ are analyzed, which is relevant and important for the DRESDYN-MRI experiment having very high Reynolds numbers ($\sim 10^6$). We show that for $Re \lesssim 10^4$, the magnetic energy of non-axisymmetric SMRI modes does not saturate and eventually decays due to the modification of the radial shear profile of the mean azimuthal velocity by the nonlinear axisymmetric SMRI, that is, the modified shear profile appears to be stable against non-axisymmetric modes. By contrast, for large $Re \gtrsim 10^4$, a sudden rapid growth and saturation of the magnetic energy of non-axisymmetric modes occur, which are radially localized in the turbulent boundary layer near the inner cylinder wall. The saturation amplitude of the non-axisymmetric modes is always a few orders smaller than that of the axisymmetric SMRI mode. We further show that the scaling relations for magnetic energy and torque in the saturated state of SMRI derived for axisymmetric modes in our previous study well carry over to $|m|\geq 1$ non-axisymmetric ones.

Seismology finds that Earth’s solid inner core behaves anisotropically. Interpretation of this requires a knowledge of crystalline elastic anisotropy of its constituents—the major phase being most likely ε-Fe, stable only under high pressure. Here, single crystals of this phase are synthesized, and its full elasticity tensor is measured between 15 and 33 GPa at 300 K. It is calculated under the same conditions, using the combination of density functional theory and dynamical mean field theory, which describes explicitly electronic correlation effects. The predictive power of this scheme is checked by comparison with measurements; it is then used to evaluate the crystalline anisotropy in ε-Fe under higher density. This anisotropy remains of the same amplitude up to densities typical of Earth’s inner core.

Thermal-hydraulic analysis of two-phase flow plays a crucial role in the optimal design of nuclear fuel assemblies and in nuclear safety. This paper presents the state of the art in two-phase flow hydrodynamics and heat transfer in nuclear fuel assemblies. A comprehensive review of experimental and CFD methods used in the last 30 years to analyse the thermal-hydraulic characteristics of sub-channels in rod bundle geometries under different flow conditions (adiabatic and boiling two-phase flow) is presented. The effects of design parameters, e.g. rod-pitch length, mixing vane angle, and flow parameters, e.g. pressure, mass flux and heat flux, on flow hydrodynamics and heat transfer performance are summarized. In addition, the capabilities of CFD modelling of two-phase in rod bundles are discussed. Moreover, based on the existing studies, some recommendations for future studies are given.

Laser plasma-based particle accelerators attract great interest in fields where conventional accelerators reach limits based on size, cost or beam parameters. Despite the fact that particle in cell simulations have predicted several advantageous ion acceleration schemes, laser accelerators have not yet reached their full potential in producing simultaneous high-radiation doses at high particle energies. The most stringent limitation is the lack of a suitable high-repetition rate target that also provides a high degree of control of the plasma conditions required to access these advanced regimes. Here, we demonstrate that the interaction of petawatt-class laser pulses with a pre-formed micrometer-sized cryogenic hydrogen jet plasma overcomes these limitations enabling tailored density scans from the solid to the underdense regime. Our proof-of-concept experiment demonstrates that the near-critical plasma density profile produces proton energies of up to 80 MeV. Based on hydrodynamic and three-dimensional particle in cell simulations, transition between different acceleration schemes are shown, suggesting enhanced proton acceleration at the relativistic transparency front for the optimal case.

Abstract

Semantics, i.e. terms and their meaning, can be shared, agreed upon, and used in data to make such data more FAIR, especially in terms of interoperability and reusability. The currently most often used technology for machine-actionable vocabularies of semantic terms are RDF-based ontologies (RDF = the W3C Resource Description Framework). But while the RDF has been around for about 20 years, there is still no broadly known tooling for using ontology terms during routine data entry and design.

To address this problem, we are implementing a data development framework that builds on semantic vocabularies as one of its core elements. This framework will provide a graphical interface where users can build their data (structures) in the form of knowledge graphs, i.e. nodes and edges that correspond to semantic vocabulary terms plus “raw values” (e.g. strings or numbers). This graph data editor will also support tables and forms as more compact graph elements for entity and attribute lists respectively.

In the editor, users will also get development support much like in IDEs (integrated development environments) for programming languages, e.g. by showing vocabulary term annotations on hover, auto-completing graph elements expected with specific terms, or suggesting existing terms and data structures when users are creating their own.

These support features together with the graph data editor will be embedded in the before mentioned data development framework. Within this framework an organization can choose desired ID services (e.g. ORCID, DOI, or in-house databases), set common vocabularies (e.g. QUDT [1] for units or BFO [2] as a top-level ontology), and have a central knowledge graph that all members can contribute to. (Groups of) users will be able to build their own graph data sets using git+GitLab for provenance and project management together with the organization’s ID services and vocabularies.

Acknowledgements

This work is being done as part of the Helmholtz Metadata Collaborations efforts to improve the metadata management in the German Helmholtz Association of Research Centers.

References

1. FAIRsharing.org: QUDT; Quantities, Units, Dimensions and Types, DOI: 10.25504/FAIRsharing.d3pqw7, Last Edited: Friday, May 6th 2022, 11:03, Last Editor: delphinedauga, accessed: 27 July 2023.
2. Arp, Robert, Barry Smith, and Andrew D. Spear, Building Ontologies With Basic Formal Ontology (Cambridge, MA, 2015; online edn, MIT Press Scholarship Online, 19 May 2016), DOI: 10.7551/mitpress/9780262527811.001.0001 , accessed: 27 July 2023.

The stratabound Mississippi Valley-type (MVT) sulphide deposits of the Gorno
and Piani Resinelli mining districts are hosted in the lower Carnian carbonate
succession, mainly peritidal limestones, of the Lombardian Basin (Southalpine
Domain, Northern Italy). In addition to the formation of the well-known sulphide
deposits, these carbonate sediments experienced a complex diagenetic evolution,
including different stages of dolomitization, silicification, dissolution, brecciation,
calcite cement precipitation. Stratigraphic and petrographic features suggest
that, apart from an early calcite cementation and a first penecontemporaneous
dolomitization affecting the supratidal beds, diagenetic processes and sulphide
precipitation, are intimately and genetically associated. They document the
occurrence of a Carnian hydrothermal system developed shortly after deposition
at shallow burial depth, confirmed by fluid inclusion microthermometry and U-Pb
radiometric datings.

At the electron accelerator for beams with high brilliance and low emittance (ELBE), the second version of a superconducting radio-frequency (SRF) photoinjector was brought into operation in 2014. After a period of commissioning, a gradual transfer to routine operation took place in 2017, so that now more than 1800h of user beam are generated every year. Since the commission, a total of 24 cathodes (2 Cu, 12 Mg, 10 Cs2Te) have been used, without observing serious cavity degradation. The contribution summarizes commissioning and operational experience of the last 8 years of gun operation, with special emphasis on SRF properties but also on specialties such as dark current and multipacting that are directly linked to the integration of a normal conducting cathode into the SRF cavity.

Magnetocaloric hydrogen liquefaction could be a ‘game-changer’ for liquid hydrogen industry. Although heavy rare-earth based magnetocaloric materials show strong magnetocaloric effects in the temperature range required by hydrogen liquefaction (77–20 K), the high resource criticality of the heavy rare-earth elements is a major obstacle for upscaling this emerging liquefaction technology. In contrast, the higher abundances of the light rare-earth elements make their alloys highly appealing for magnetocaloric hydrogen liquefaction. Via a mean-field approach, it is demonstrated that tuning the Curie temperature (T_C) of an idealized light rare-earth based magnetocaloric material towards lower cryogenic temperatures leads to larger maximum magnetic and adiabatic temperature changes (ΔS_T and ΔT_ad). Especially in the vicinity of the condensation point of hydrogen (20 K), ΔS_T and ΔT_ad of the optimized light rare-earth based material are predicted to show significantly large values. Following the mean-field approach and taking the chemical and physical similarities of the light rare-earth elements into consideration, a method of designing light rare-earth intermetallic compounds for hydrogen liquefaction is used: tuning T_C of a rare-earth alloy to approach 20 K by mixing light rare-earth elements with different de Gennes factors. By mixing Nd and Pr in Laves phase (Nd, Pr)Al₂, and Pr and Ce in Laves phase (Pr, Ce)Al₂, a fully light rare-earth intermetallic series with large magnetocaloric effects covering the temperature range required by hydrogen liquefaction is developed, demonstrating a competitive maximum effect compared to the heavy rare-earth compound DyAl.

Thermodynamic and magnetic studies on high-quality single crystals are used to investigate the magnetic phase diagram and magnetostructural coupling in the mixed-spin system Ni_0.25Mn_0.75TiO₃. Clear anomalies in the thermal expansion at the spin ordering and spin reorientation temperatures, T_N and T_R, evidence pronounced magnetoelastic effects. The magnetic entropy is released mainly above T_N implying considerable short range magnetic order up to about 4 × T_N . This is associated with a large regime of negative thermal expansion of the c axis. Both T_N and T_R exhibit the same sign of uniaxial pressure dependence, which is positive (negative) for pressure applied along the b (c) axis. The magnetic phase diagrams are constructed and the uniaxial pressure dependencies of the ordering phenomena are determined. For magnetic fields B II b axis, a sign change and splitting of anomalies implies further magnetic phases. In addition to short-range magnetic order well above T_N, competing anisotropies yield a glasslike behavior as evidenced by a maximum in AC-χ (T_SG ≃ 3.7 K) and quasilinear temperature dependence of c_p. High-field magnetization up to 50 T demonstrates that in addition to antiferromagnetically ordered spins there are also only weakly coupled moments at 2 K with a sizable amount of about 15% of all Mn²⁺ spins present in the material. The observed changes in the pressure dependence and the magnetostrictive effects shed light on the recently observed flop of electric polarization from P II c to P II a [Phys. Rev. B 90, 144429 (2014)], in particular, suggesting that the magnetoelectric effect is not directly related to magnetostriction.

We present an overview of selected copper-based quasi-2D square-lattice spin-1/2 materials with an easy-plane anisotropy, providing the possibility to study emergent Berezinskii-Kosterlitz-Thouless (BKT) correlations. In particular, in those materials with a comparatively small exchange coupling, the effective XY anisotropy of the low-temperature spin correlations can be controlled by an applied magnetic field, yielding a systematic evolution of the BKT correlations. In cases where the residual interlayer correlations are small enough, dynamical BKT correlations in the critical regime may be observed experimentally, whereas the completion of the genuine BKT transition is preempted by the onset of long-range order.

We measured the elastic constants (C₁₁ − C₁₂)/2 and C₄₄ of the non-Kramers system Y_0.63Pr_0.37Ir₂Zn₂₀ (Pr-37% system) by means of ultrasound to check how the single-site quadrupolar Kondo effect is modified by increasing the Pr concentration. The Curie-like softening of (C₁₁ − C₁₂)/2 of the present Pr-37% system on cooling from 5 to 1K can be reproduced by a multipolar susceptibility calculation based on the non-Kramers Γ3 doublet crystalline-electric-field ground state. Further, on cooling below 0.15 K, a temperature dependence proportional to √T was observed in (C₁₁ − C₁₂)/2. This behavior rather corresponds to the theoretical prediction of the quadrupolar Kondo “lattice” model, unlike that of the Pr-3.4% system, which shows a logarithmic temperature dependence based on the “single-site” quadrupolar Kondo theory. In addition, we discuss the possibility to form a vibronic state by the coupling between the low-energy phonons and the electric quadrupoles of the non-Kramers doublet in the Pr-37% system, since we found a low-energy ultrasonic dispersion in the temperature range between 0.15 and 1K.

Na2Ga7 crystallizes with the orthorhombic space group Pnma (no. 62; a = 14.8580(6) Å, b = 8.6766(6) Å, and c = 11.6105(5) Å; Z = 8) and constitutes a filled variant of the Li2B12Si2 structure type. The crystal structure consists of a network of icosahedral Ga12 units with 12 exohedral bonds and four-bonded Ga atoms in which the Na atoms occupy the channels and cavities. The atomic arrangement is consistent with the Zintl [(4b)Ga]− and Wade [(12b)Ga12]2– electron counting approach. The compound forms peritectically from Na7Ga13 and the melt at 501 °C and does not show a homogeneity range. The band structure calculations predict semiconducting behavior consistent with the electron balance [Na+]4[(Ga12)2–][Ga–]2. Magnetic susceptibility measurements show that Na2Ga7 is diamagnetic.

This study introduces a general framework, called Bi-sided facility location, for a wide range of problems in the area of combined facility location and routing problems such as locating test centres and designing the network of supermarkets. It is based on a multi-objective optimisation model to enhance the service quality which the clients received, called client-side, and enhance the interconnection quality and eligibility among the centres, called center-side. Well-known problems such as k-median and k-centre for the client-side and the travelling salesman problem for the centre-side are taken into account in this paper. After discussing the complexity of this kind of combination, we propose a heuristic approximation algorithm to find approximation Pareto-optimal solutions for the problem. The algorithm is an efficient local search utilising geometric objects such as the Voronoi diagram and Delaunay triangulation as well as algorithms for computing approximation travelling salesman tour. In addition to the comprehensive theoretical analysis of the proposed models and algorithm, we apply the algorithm to different instances and benchmarks, and compare it with NSGA-II based on set coverage and spacing metrics. The results confirm the efficiency of the algorithm in terms of running time and providing a diverse set of efficient trade-off solutions.

Under magnetic fields, quantum magnets often undergo exotic phase transitions with various kinds of order. The discovery of a sequence of fractional magnetization plateaus in the Shastry-Sutherland compound SrCu₂(BO₃)₂ has played a central role in the high-field research on quantummaterials, but so far this system could only be probed up to half the saturation value of the magnetization. Here, we report the first experimental and theoretical investigation of this compound up to the saturation magnetic field of 140 T and beyond. Using ultrasound and magnetostriction techniques combined with extensive tensor-network calculations (iPEPS), several spin-supersolid phases are revealed between the 1/2 plateau and saturation (1/1 plateau). Quite remarkably, the sound velocity of the 1/2 plateau exhibits a drastic decrease of -50%, related to the tetragonal-to-orthorhombic instability of the checkerboard-type magnon crystal. The unveiled nature of this paradigmatic quantum system is a new milestone for exploring exotic quantum states of matter emerging in extreme conditions.

Cancer is an extraordinarily diverse disease that affects our society globally; it hits people of all ages and genders. Because of its high mortality rate, it is responsible on average for one in six deaths, it is the second most common cause of death, according to the World Health Organization. In this article, published in 'Krebs im Focus, Die Wissenschaftszeitschrift des NCT/UCC Dresden', the importance of immune cancer phenotyping to make use of the recent advances in cancer immunotherapy, based on immune checkpoint inhibition and cross-linking of immune cells to target cancer cells, is outlined. The research landscape in the last few years has shown encouraging signs for nanoelectronics to be better represented in cancer research in near future. In particular, this approach can open new routes to perform a complex combinatorial analysis using tiny electronic chips and simultaneously screening multiple biochemical species thus facilitating the transition from conventional medicine to precision medicine in clinical oncology.

We report crystal structure and magnetic behavior of the triangular antiferromagnet KYbO₂, the A-site substituted version of the quantum spin liquid candidate NaYbO₂. The replacement of Na by K introduces an anisotropic tensile strain with 1.6% in-plane and 12.1% out-of-plane lattice expansion. Compared to NaYbO₂, both Curie-Weiss temperature and saturation field are reduced by about 20% as the result of the increased Yb-O-Yb angles, whereas the g tensor of Yb³⁺ becomes isotropic with g = 3.08(3). Field-dependent magnetization shows the plateau at 1/2 of the saturated value and suggests the formation of the up-up-up-down field-induced order in KYbO₂ in contrast to the more common 1/3 plateau with the up-up-down order that has been reported in the isostructural Yb³⁺ selenides.

Magnetic refrigeration is a highly active field of research. The recent studies in materials and methods for hydrogen liquefaction and innovative techniques based on multicaloric materials have significantly expanded the scope of the field. For this reason, the proper characterization of materials is now more crucial than ever. This makes it necessary to determine the magnetocaloric and other physical properties under various stimuli such as magnetic fields and mechanical loads. In this work, we present an overview of the characterization techniques established at the Dresden High Magnetic Field Laboratory in recent years, which specializes in using pulsed magnetic fields. The short duration of magnetic-field pulses, lasting only some ten milliseconds, simplifies the process of ensuring adiabatic conditions for the determination of temperature changes, ΔT_ad. The possibility to measure in the temperature range from 10 to 400 K allows us to study magnetocaloric materials for both room-temperature applications and gas liquefaction. With magnetic-field strengths of up to 50 T, almost every first-order material can be transformed completely. The high field-change rates allow us to observe dynamic effects of phase transitions driven by nucleation and growth as well. We discuss the experimental challenges and advantages of the investigation method using pulsed magnetic fields. We summarize examples for some of the most important material classes including Gd, Laves phases, La–Fe–Si, Mn–Fe–P–Si, Heusler alloys and Fe–Rh. Further, we present the recent developments in simultaneous measurements of temperature change, strain, and magnetization, and introduce a technique to characterize multicaloric materials under applied magnetic field and uniaxial load. We conclude by demonstrating how the use of pulsed fields opens the door to new magnetic-refrigeration principles based on multicalorics and the ‘exploiting-hysteresis’ approach.

We combine thermodynamic, electron spin resonance (ESR), and muon spin-relaxation (μSR) measurements with density functional theory (DFT) and classical Monte Carlo calculations toward understanding a disorderdriven behavior of the 3D coupled frustrated cubic lattice Lu₃Sb₃Mn₂O₁₄ with s = 5/2. The classical Monte Carlo calculations based on exchange interactions extracted from DFT predict that Lu₃Sb₃Mn₂O₁₄ undergoes a transition to magnetic ordering. In sharp contrast, our specific heat measurements evince a weak magnetic anomaly at 0.5 K while μSR detects neither long-range magnetic order nor spin freezing down to 0.3 K. For temperatures above 2 K, our ac susceptibility, magnetization, and specific heat data obey temperature-magnetic field scalings, indicative of the formation of 3D random singlets. The development of multiple ESR lines with decreasing temperature below 80 K supports the notion of inhomogeneous magnetism. Our results extend random-singlet physics to 3D frustrated classical magnets with a large spin number s = 5/2.

Multiferroic behavior in the linear-chain spin S = 1/2 compound CuCrO₄ was proposed to appear due to competing nearest- and next-nearest-neighbor exchange interactions along the chain. Here, we report on our study of the long-range magnetic ordering using powder neutron diffraction and muon-spin rotation measurements. Consistently, both methods find incommensurate long-range antiferromagnetic ordering below 8.5(3) K. We determined the magnetic structure from neutron powder diffraction patterns based on the propagation vector τ = (0, 0, 0.546(1)). At 1.9 K, the magnetic moment of Cu²⁺ was refined to 0.48(2) μ_B. The Cu moments form a helicoidal spiral with an easy plane coinciding with the equatorial planes of the Jahn-Teller elongated CuO₆ octahedra. Low-temperature high magnetic field measurements of the magnetization and the dielectric polarization show the multiferroic phase to extend up to ∼25 T, after which a new, yet unknown phase appears. Full saturation of the magnetic moment is expected to occur at fields much beyond 60 T.

Using first-principles calculations we study the energetics of alkali metal (AM) atom intercalation into bulk tetracene crystals. We show that, contrary to the adsorption of Li and Na atoms on isolated tetracene molecules, the intercalation of these and other (K, Rb, Cs) AM atoms into bulk tetracene crystals is energetically favorable (with respect to forming an infinite AM crystal) in a wide range of AM concentrations and that the intercalation en- ergy is noticeably lower than that for intercalation into graphite, a material used today in anodes of AM batteries. In case of Li, there is no swelling of the intercalated crystals, and for Na the increase in crystal volume is less than 10%, which makes crystalline tetracene attractive from the viewpoint of energy storage, as the capacity exceeds the theoretical capacity of graphite. We further assess diffusion barriers of AM atoms, which for Li and Na proved to be below 0.5 eV, indicating a high diffusivity of these atoms already at room temperature. We also study the effects of intercalation on the electronic properties of the system, and show that several bands can be filled upon inter- calation, so that the system exhibits semiconducting-metallic-semiconducting behavior when AM atom concentration increases. Our results shed light on the perspective of using AM atom intercalation into tetracene crystals for energy storage and tuning the electronic properties of this system.

Over the last years, inverse gas chromatography (IGC) proved to be a versatile and sensitive analytical technique for physicochemical properties. However, the comparability of results obtained by different users and devices remains a topic for debate. This is the first time, an interlaboratory study using different types of IGC instruments is reported. Eight organizations with different IGC devices defined a common lab measurement protocol to analyse two standard materials, silica and lactose. All data was collected in a standard result form and has been treated identically with the objective to identify experimentally observed differences and not potentially different data treatments. The calculated values of the dispersive surface energy vary quite significantly (silica: 22 mJ/m2 - 34 mJ/m2, lactose 37 mJ/m2 - 51 mJ/m2) and so do the ISP values and net retention volumes for both materials. This points towards significant and seemingly undiscovered differences in the operation of the instruments and the obtained underlying primary data, even under the premise of standard conditions. Variations are independent of the instrument type and uncertainties in flow rates or the injected quantities of probe molecules may be potential factors for the differences. This interlaboratory study demonstrates that the IGC is a very sensitive analytical tool, which detects minor changes, but it also shows that for a proper comparison, the measurement conditions have to be checked with great care. A publicly available standard protocol and material, for which this study can be seen as a starting point, is still needed to judge on the measurements and the resulting parameters more objectively.

Froth flotation faces increasing challenges in separating particles as those become finer and more complex, thus reducing the efficiency of the separation process. A lab flotation apparatus has been designed with the idea of combining the advantages of agitator-type froth flotation for high turbulences and column flotation with a deep froth zone for a fractionating effect enabling also to study the effect of different particle property vectors. A model system consisting of ultrafine (< 10 μm) glass particles with differing morphology (spheres vs. fragments) and wettability state (hydrophilic vs. moderately hydrophobic vs. strongly hydrophobic) as the floatable and magnetite as the non-floatable fraction was used for flotation to study how the separation process is influenced by the ultrafine property vectors of shape and wettability. Within this newly designed apparatus the froth depth was varied to investigate the fractionating effect and how the different particle fractions are affected by it. Furthermore, to evaluate the new apparatus, flotation tests had been carried out in a benchmark mechanical flotation cell under comparable conditions. Our findings contribute to ultrafine flotation techniques and especially our understanding of the complex effect of particle shape in combination with the other property vectors.

The uptake of Pu(IV) by hardened cement paste (HCP) at degradation stage I was investigated in the absence and presence of gluconate (GLU). Furthermore, the influence of the ionic strength was examined by different background electrolytes. For low ionic strength (I = 0.3 M) artificial cement pore water (ACW, pH = 13) and for high ionic strength (I = 2.5 M) cement pore water based on the diluted caprock solution (ACW-VGL, pH = 12.5) were used. Sorption experiments were performed under Ar atmosphere using HCP in the binary system HCP / GLU ([GLU]0/M = 1×10-1 - 1×10-8) and the ternary system HCP / Pu(IV) / GLU ([239Pu(IV)]0/M = 1×10-8, [GLU]0/M = 1×10-2) with S/L of 0.1 – 50 g L-1 within a contact time of 72 h. GLU sorbs strongly on HCP, a saturation of the sorption sites of HCP with GLU was observed at [GLU] ≥ 1×10-4 M at S/L = 5 g L-1. The effects of the order of addition of the components Pu(IV) and GLU showed a low sorption of Pu(IV) to HCP, indicating strong kinetic effects. In the absence of GLU, quantitative uptake (S% = 99%) of Pu(IV) by HCP was observed. GLU had a significant effect on the sorption of Pu(IV) to HCP in both background electrolytes.
Powder samples from batch experiments were investigated by X-ray absorption spectroscopy to determine the structural parameters of the near-neighbour environment of sorbed Pu ([Pu(III)]0/M = 5×10-6) on HCP (S/L = 2.5 g L-1) in dependence of the ionic strength of the background electrolyte (ACW and ACW-VGL) and in presence of GLU ([GLU]0/M = 1×10 2). Pu LIII-edge X-ray absorption near-edge structure spectra confirm the presence of Pu(IV) as the dominant species on HCP. Plutonium was incorporated mainly into the calcium silicate hydrates phases (C-S-H) of HCP. Also, the ionic strength of the background electrolytes, as well as the presence of GLU do not influence the speciation of Pu on HCP during the degradation state I in cement-based repository.

The synthesis, structure and photophysical properties of two polynuclear zinc complexes, namely Zn6 L2 (μ3 -OH)2 (OAc)8 ] (1) and [Zn4 L4 (μ2 -OH)2 * emission. Other biologically relevant ions, i.e., Na+, K+, Mg2+, Ca2+, Mn2+, Fe2+, Co2+, Ni2+ and Cu2+, did not give rise to a fluorescence enhancement.

Earth is exposed to nearby cosmic events. The solar system moves through the
interstellar medium and collects interstellar dust particles that contain unique
signatures of ongoing nucleosynthesis in nearby supernovae or rare cosmic
explosions. Such particles may accumulate over million years in deep-ocean
archives and in lunar soil, imprinting isotopic fingerprints of specific interstellar
radionuclides in the geological record. The most prominent radionuclides are
60Fe (t1/2 = 2.6 Myr) and 244Pu (81 Myr). Both do not exist naturally on Earth.
They can be measured with high sensitivity via accelerator mass spectrometry
(AMS). Indeed, both nuclides have been found on Earth and 60Fe also on the
Moon.
AMS measurements of 60Fe from terrestrial and lunar archives demonstrate
a clear exposure of Earth to recent (<10 Myr) cosmic explosions, suggesting
close-by supernova activity ∼2–3 and ∼7 million years ago. In addition, recent
detection of interstellar 244Pu, exclusively produced by the rapid neutron capture
(r-)process, allows to link supernovae and r-process. This latter process is far
from being fully understood. Interstellar 244Pu can place constraints on r-process
frequency and production yields over the last few 100 Myr. The measured
244Pu influx was found lower than expected if supernovae dominate r-process
nucleosynthesis, implying contributions from additional sources.
In this chapter, the journey of such radionuclides is followed, after their
production in massive stars or compact objects, from the interstellar medium
to their incorporation in geological archives, resulting finally in the detection of
a few atoms via direct atom counting. These experimental results provide unique
insights into recent and nearby nucleosynthesis events.

Accelerator mass spectrometry (AMS) was born in the late 1970s when it was realized at nuclear physics laboratories that the accelerator systems can be used as a sensitive mass spectrometer to measure ultra-low traces of long-lived radioisotopes. It soon became possible to measure radioisotope-to-stable isotope ratios in the range from 10−12 to 10−16 by counting the radioisotope ions "atom by atom’’ and comparing the count rate with ion currents of stable isotopes (1.6 A = 1x10^13 singly-charged ions/sec). It turned out that electrostatic tandem accelerators are best suited for this, and there are now world-wide about 160 AMS facilities based on this principle. The current review will present the history, technological developments and research areas of AMS through the 45 years since its discovery. Many different fields are touched by AMS measurements, including (alphabetically) archaeology, astrophysics, atmospheric science, biology, climatology, cosmic-ray physics, environmental physics, forensic science, glaciology, geophormology, hydrology, ice core research, meteoritics, nuclear physics, oceanography, particle physics - and more. Since it is virtually impossible to discuss all fields in detail in this review, only some specific fields with recent advances will be highlighted in more detail. For the others, an effort has been made to provide relevant references for in-depth studies of the respective fields.

Earth is exposed to nearby cosmic events. The solar system moves through the interstellar medium and collects interstellar dust particles that contain unique signatures of ongoing nucleosynthesis in nearby supernovae or rare cosmic explosions. Such particles may accumulate over million years in deep-ocean archives and in lunar soil, imprinting isotopic fingerprints of specific interstellar radionuclides in the geological record. The most prominent radionuclides are 60Fe (t1/2=2.6 Myr) and 244Pu (81 Myr). Both do not exist naturally on Earth. They can be measured with high sensitivity via accelerator mass spectrometry (AMS). Indeed, both nuclides have been found on Earth or the Moon.
AMS measurements of 60Fe from terrestrial and lunar archives demonstrate a clear exposure of Earth to recent (<10 Myr) cosmic explosions, suggesting close-by supernova activity ~2–3 and ~6 million years ago. In addition, recent detection of interstellar 244Pu, exclusively produced by the rapid neutron capture (r-)process, allows to link supernovae and r-process. This latter process is far from being fully understood. Interstellar 244Pu can place constraints on r-process frequency and production yields over the last few 100 Myr. The measured 244Pu influx was found lower than expected if supernovae dominate r-process nucleosynthesis, implying contributions from additional sources.
In this chapter we follow the journey of such radionuclides after production in massive stars or compact objects, from the interstellar medium to their incorporation in geological archives, resulting finally in the detection of a few atoms via a direct atom counting. These experimental results provide unique insights into recent and nearby nucleosynthesis events.

Magnonics is a rapidly developing domain of nanomagnetism, with application potential in information processing systems. Realisation of this potential and miniaturisation of magnonic
circuits requires their extension into the third dimension. However, so far magnonic conduits are largely limited to thin films and 2D structures. Here, we introduce 3D magnonic nanoconduits fabricated by the direct write technique of focused electron beam induced deposition (FEBID). We use Brillouin light scattering (BLS) spectroscopy to demonstrate significant qualitative differences in spatially resolved spin-wave resonances of 2D and 3D nanostructures, which originates from the geometrically induced nonuniformity of the internal field. This work demonstrates the capability of FEBID as an additive manufacturing technique to produce magnetic 3D nanoarchitectures and presents the first report of BLS spectroscopy characterisation of FEBID conduits.

Background and purpose: Tumour hypoxia is an established radioresistance factor. A novel hypoxia-activated prodrug CP-506 has been proven to selectively target hypoxic tumour cells and to cause anti-tumour activity. The current study investigates whether CP-506 improves outcome of radiotherapy in vivo.
Materials and methods: Mice bearing FaDu and UT-SCC-5 xenografts were randomized to receive 5 daily injections of CP-506/vehicle followed by single dose (SD) irradiation. In addition, CP-506 was combined once per week with fractionated irradiation (30 fractions/6 weeks). Animals were followed-up to score all recurrences. In parallel, tumours were harvested to evaluate pimonidazole hypoxia, DNA damage (cH2AX), expression of oxidoreductases.
Results: CP-506 treatment significantly increased local control rate after SD in FaDu, 62% vs. 27% (p = 0.024). In UT-SCC-5, this effect was not curative and only marginally significant. CP-506 induced significant DNA damage in FaDu (p = 0.009) but not in UT- SCC-5. Hypoxic volume (HV) was significantly smaller (p = 0.038) after pretreatment with CP-506 as compared to vehicle in FaDu but not in less responsive UT-SCC-5. Adding CP-506 to fractionated radiotherapy in FaDu did not result in significant benefit.
Conclusion: The results support the use of CP-506 in combination with radiation in particular using hypofractionation schedules in hypoxic tumours. The magnitude of effect depends on the tumour model, therefore it is expected that applying appropriate patient stratification strategy will further enhance the benefit of CP-506 treatment for cancer patients. A phase I-IIA clinical trial of CP-506 in monotherapy or in combination with carboplatin or a checkpoint inhibitor has been approved (NCT04954599).

Phenylgermaniumpyridine-2-olate PhGe(pyO)₃ (compound 1Ge) and CuCl react with the formation of the heteronuclear complex Ph(pyO)Ge(μ²-pyO)₂CuCl (2Ge’) rather than forming the expected compound PhGe(μ²-pyO)₃CuCl (2Ge). Single-point calculations (at the B2T-PLYP level) of the optimized molecular structures confirmed the relative stability of isomer 2Ge’ over 2Ge and, for the related silicon congeners, the relative stability of 2Si over 2Si’. Decomposition of a solution of 2Ge’ upon access to air provided access to some crystals of the copper(II) compound PhGe(μ²-pyO)₄CuCl (3Ge). Compounds 2Ge’ and 3Ge were characterized by single-crystal X-ray diffraction analyses, and the Ge–Cu bonds in these compounds were analyzed with the aid of quantum chemical calculations, e.g., Natural Bond Orbital analyses (NBO), Non-Covalent Interactions descriptor (NCI), and topology of the electron density at bond critical point using Quantum Theory of Atoms-In-Molecules (QTAIM) in conjunction with the related silicon compounds PhSi(μ²-pyO)₃CuCl (2Si), PhSi(μ²-pyO)₄CuCl (3Si), as well as the potential isomers Ph(pyO)Si(μ²-pyO)₂CuCl (2Si’) and PhGe(μ²-pyO)₃CuCl (2Ge). Pronounced Cu→Ge (over Cu→Si) lone pair donation was found for the Cu(I) compounds, whereas in Cu(II) compounds 3Si and 3Ge, this σ-donation is less pronounced and only marginally enhanced in 3Ge over 3Si.

We present all-electrical operation of a Fe$_x$Cr$_{1-x}$-based Curie switch at room temperature. More specifically, we study the current-induced thermally-driven transition from ferromagnetic to antiferromagnetic Ruderman-Kittel-Kasuya-Yosida (RKKY) indirect coupling in a Fe/Cr/Fe$_{17.5}$Cr$_{82.5}$/Cr/Fe multilayer. Magnetometry measurements at different temperatures show that the transition from the ferromagnetic to the antiferromagnetic coupling at zero field is observed at $\sim$325K. Analytical modelling confirms that the observed temperature-dependent transition from indirect ferromagnetic to indirect antiferromangetic interlayer exchange coupling originates from the modification of the effective interlayer exchange constant through the ferromagnetic-to-paramagnetic transition in the Fe$_{17.5}$Cr$_{82.5}$ spacer with minor contributions from the thermally-driven variations of the magnetization and magnetic anisotropy of the Fe layers. Room-temperature current-in-plane magnetotransport measurements on the patterned Fe/Cr/Fe$_{17.5}$Cr$_{82.5}$/Cr/Fe strips show the transition from the 'low-resistance' parallel to the 'high-resistance' antiparallel remanent magnetization configuration, upon increased probing current density. Quantitative comparison of the switching fields, obtained by magnetometry and magnetotransport, confirms that the Joule heating is the main mechanism responsible for the observed current-induced resistive switching.

The recently observed FLASH effect provides normal tissue protection at a similar tumor treatment efficacy via ultra-high dose rate (UHDR) irradiation and promises great benefits for radiotherapy patients. Dedicated studies are now necessary to define a robust set of dose application parameters for FLASH radiotherapy and to identify underlying mechanisms. These studies require particle accelerators with variable temporal dose application characteristics for numerous radiation qualities, equipped for preclinical radiobiological research. Here we present the DRESDEN PLATFORM, a research hub for ultra-high dose rate radiobiology. By uniting clinical and research accelerators with radiobiology infrastructure and know-how, the DRESDEN PLATFORM offers a unique environment for studying the FLASH effect. We introduce its experimental capabilities and qualify the platform for systematic investigation of FLASH by presenting results from a concerted in vivo radiobiology study with zebrafish embryos. The comparative pre-clinical study was conducted across three accelerator facilities, including an advanced laser-driven proton source applied for FLASH-relevant in vivo irradiations for the first time. The data show a protective effect of UHDR irradiation up to 10^5 Gy/s and suggests consistency of the protective effect even at escalated dose rates of 10^9 Gy/s. With
the first clinical FLASH studies underway, research facilities like the DRESDEN PLATFORM, addressing the open questions surrounding FLASH, are essential to accelerate FLASH’s translation into clinical practice.

Ion irradiation is a promising tool to emulate neutron-irradiation effects on reactor pressure vessel (RPV) steels, especially in the situation of limited availability of suitable neu-tron-irradiated material. This approach requires the consideration of ion-neutron transferability issues, which are addressed in the present study by comparing the effect of ions with neu-tron-irradiation effects reported for the same materials. The first part of the study covers a com-prehensive characterization, based on dedicated electron microscopy techniques, of the selected unirradiated RPV materials, namely a base metal and a weld. The results obtained for the grain size, dislocation density and precipitates are put in context in terms of hardening contributions and sink strength. The second part is focused on the depth-dependent characterization of the dislocation loops formed in ion-irradiated samples. This work is based on scanning transmission electron microscopy applied to cross-sectional samples prepared by the focused ion beam tech-nique. A band-like arrangement of loops is observed in the depths range close to the peak of in-jected interstitials. Two levels of displacement damage, 0.1 and 1 dpa (displacements per atom), as well as post-irradiation annealed conditions are included for both RPV materials. Compared with neutron irradiation, ion irradiation creates a similar average size but a higher number density of loops presumably due to the higher dose rate during ion irradiation.

Few-layer organic nanosheets are becoming increasingly attractive as two-dimensional (2D) materials due to their precise atomic connectivity and tailor-made pores. However, most strategies for synthesizing nanosheets rely on surface-assisted methods or top-down exfoliation of stacked materials. A bottom-up approach with well-designed building blocks would be the convenient pathway to achieve the bulk-scale synthesis of 2D nanosheets with uniform size and crystallinity. Herein, we have synthesized crystalline covalent organic framework nanosheets (CONs) by reacting tetratopic thianthrene tetraaldehyde (THT) and aliphatic diamines. The bent geometry of thianthrene in THT retards the out-of-plane stacking, while the flexible diamines introduce dynamic characteristics into the framework, facilitating nanosheet formation. Successful isoreticulation with five diamines with two to six carbon chain lengths generalizes the design strategy. Microscopic imaging reveals that the odd and even diamine-based CONs transmute to different nanostructures, such as nanotubes and hollow spheres. The single-crystal X-ray diffraction structure of repeating units indicates that the odd–even linker units of diamines introduce irregular–regular curvature in the backbone, aiding such dimensionality conversion. Theoretical calculations shed more light on nanosheet stacking and rolling behavior with respect to the odd–even effects.

Magnetic shape memory alloys are emerging multifunctional materials that enable applications
like high-stroke actuation, solid-state refrigeration, and energy harvesting of waste heat. Thin
films of these alloys promise integration in microsystems to exploit their multifunctional
properties at the microscale. However, the microfabrication process of these Heusler alloys is
difficult. Here, we investigate different etching techniques for the microfabrication of epitaxial
Ni-Mn-Ga films, explain the encountered challenges, and demonstrate ways to overcome them.
Our results show that wet chemical etching is suitable for large patterned structures, while
reactive ion etching of Ni-Mn-Ga films is unsuitable due to redeposition. For patterning
structures below 10 μm with clean and sharp edges, the best results are obtained by ion-beam
etching with adjusted sample-stage tilt. Finally, we demonstrate a microfabrication process
using Si microtechnology to fabricate partially free-standing structures. Our findings give
guidelines for the fabrication and integration of these smart materials in Si-based microsystems.

The inherent complexity of underground mining requires highly selective ore extraction and adaptive mine planning. Repeated geological face mapping and re-interpretation throughout mine life is therefore routine in underground mines. Hyperspectral imaging has successfully been applied to enhance geological mapping in surface mining environments but remains a largely unexplored opportunity in underground operations due to challenges associated with illumination, wet surfaces, and data corrections. In this study, we propose a workflow that paves the way for the operational use of hyperspectral imaging in active underground mines. In a laboratory setup, we evaluated different hyperspectral sensors and lighting setups as well as the effect of surface moisture. We then acquired hyperspectral data in an underground mine of the Zinnwald/Cínovec Sn-W-Li greisen-type deposit in Germany. These data were corrected for illumination effects, back-projected into 3-D and then used to map mineral abundance and estimate lithium content across the mine face. We validated the results with handheld laser-induced breakdown spectroscopy. Despite remaining challenges, we hope this study will help establish hyperspectral sensors in the extractive industry as a means to increase the volume and efficiency of raw material supply, advance digitalisation, and reduce the environmental footprint and other risks associated with underground mining.

This paper presents a novel control strategy for pumps in storage tanks that accounts for fluctuations in energy prices. Storage tanks are commonly used in industrial and commercial applications to store and transport large quantities of liquids or gases. The energy consumed by pumping systems can contribute up to 20% of the total electricity usage in industrialized countries. Recent spikes in energy prices have had a detrimental impact on industries reliant on pumping systems, but the growing adoption of renewable energy sources presents new opportunities for energy demand response strategies to balance supply and demand. This study proposes a control strategy that incorporates energy price fluctuations, liquid level, input flow rate, and storm forecasting as input variables. The controller adjusts the pump flow rate every five minutes based on all four inputs. Additionally, this study highlights the environmental advantages of shifting energy usage to maximize renewable energy consumption. The simulation results on a sewer system model demonstrate a 40% reduction in wastewater volume overflow and a 15.5% reduction in energy costs compared to the results of traditional control strategies.

Ultrakompakte Biosensoren in Nanogröße könnten in naher Zukunft eine ernsthafte Alternative zu modernen Systemen für die Vor-Ort-Diagnose darstellen. Impedimetrische Bionanosensoren gehören zur Gruppe der elektronischen Detektoren, die aus nanostrukturierten Elektroden bestehen, die mit einer Schicht biofunktioneller Moleküle überzogen sind, um eine hohe Spezifität für den gewünschten Analyten zu erreichen. Nach dem elektrischen Anschluss und dem Anlegen eines Wechselstrom-Eingangssignals wirkt der impedimetrische Bionanosensor wie ein durchlässiger Nanokondensator. Veränderungen in den Eigenschaften des Nanokondensators können mit der biochemischen Bindung der Moleküle und der Veränderung der elektrischen Eigenschaften der gesamten Molekülschicht in Verbindung gebracht werden. Diese Modulation der Eigenschaften des Nanokondensators kann in Echtzeit gemessen werden, indem die Änderungen der Amplitude und Phase der Ausgangswechselspannung überwacht werden.

We use experiments to study the evolution of bubble clusters in a swarm of freely rising,
deformable bubbles. A new machine learning-aided algorithm allows us to identify and track
bubbles in clusters and measure the cluster lifetimes. The results indicate that contamination in
the carrier liquid can enhance the formation of bubble clusters and prolong the cluster lifetimes.
The mean bubble rise velocities conditioned on the bubble cluster size are also explored, and we
find a positive correlation between the cluster size and the rise speed of the bubbles in the cluster,
with clustered bubbles rising up to 20% faster than unclustered bubbles.

Article about Heating in multi-layered target upon UHI laser irradiation

The recent experimental results of Ma et al. [1] reveal that with increasing concentration of surfactants, the generated bubble-induced turbulence (BIT) increases as well, although the bubbles rise slower. We show that this phenomenon has not be considered so far in the standard Reynolds-averaged Navier-Stokes (RANS) modelling for BIT, using the ansatz with source terms added to the transport equation of turbulent kinetic energy and dissipation, respectively. Some problematic issues related to the common concepts for closure of the liquid phase turbulence kinetic energy equation are also discussed. Furthermore, we demonstrated this issue by simulating the experiments using two-fluid approach.

Vorwort zur 9. Auflage
Begründet von Herrn Univ.-Prof. Dr. med. Harald Schicha und Herrn Univ.-Prof. Dr. med. Dr. rer. nat. Otmar Schober ist das Lehrbuch für Nuklearmedizin in seiner 9. Auflage im Thieme Verlag durch die u.g. Herausgeber neu aufgelegt worden. Über alle Buchkapitel hinweg wurden sowohl der Text als auch das Bildmaterial erweitert und aktualisiert. Adaptiert an die klinische Weiterentwicklung des Fachgebiets Nuklearmedizin werden in der 9. Auflage die konventionelle Nuklearmedizin, die PET/CT-Diagnostik und die nuklearmedizinische Therapie in zahlreichen aktualisierten oder neu erstellten Kapiteln abgebildet. Das bewährte einführende Kapitel zur Pathophysiologie der funktionellen Tumorbildgebung blieb erhalten, in der 9. Auflage mit eigenständigen Kapiteln für die konventionelle Nuklearmedizin und für die PET/CT.
Bei der konventionellen Nuklearmedizin wurden die aktuellen Leitlinien berücksichtigt, unter anderem bei der Indikationserweiterung der Herzbildgebung
(Amyloidose, Sarkoidose, Entzündungsdiagnostik) und bei der gastrointestinalen Diagnostik. Aktuelle Entwicklungen bei der neurologischen Diagnostik wurden aufgenommen.
Jede Tumorentität, bei der die PET/CT eine klinische Bedeutung in der Patientenversorgung erlangt hat, wurde mit einem eigenen Kapitel berücksichtigt.
Zum Zeitpunkt der Erstellung der 9. Auflage hat der Gemeinsame Bundesausschuss für inzwischen 9 Fachgebiete die PET/CT in der „Ambulanten Spezialärztlichen Versorgung“ für dezidierte Indikationen zugelassen. Diese sozialmedizinischen Aspekte werden in dem Kapitel zur PET/CT bei onkologischen Fragestellungen abgehandelt.
Die Therapiekapitel wurden erweitert und aktualisiert. Für jedes etablierte nuklearmedizinische Therapieverfahren wurde ein separates Kapitel geschaffen.
Dabei hat das verlängerte Gesamtüberleben in der Zulassungsstudie für 177Lu-PSMA-617 beim metastasierten kastrationsresistenten Prostatakarzinom
(VISION-Studie) eine weitere, breite Therapieoption für die Nuklearmedizin erschlossen.
Durch diese Umstrukturierung gewinnt das Lehrbuch in seiner 9. Auflage an Aktualität und Übersichtlichkeit. Trotz zahlreicher neuer Kapitel wurde der Umfang des Lehrbuchs konstant gehalten. Dieses Konzept eines handhabbaren Lehrbuchs hat sich über mittlerweile 3 Dekaden für die diversen Zielgruppen – Ärztinnen und Ärzte mit speziellem Interesse für das Fach Nuklearmedizin, Ärztinnen und Ärzte in Weiterbildung, Ärztinnen und Ärzte anderer Fachgebiete, Medizinstudierende, MTR/RT, Naturwissenschaftlerinnen und Naturwissenschaftler – bewährt. Die Herausgeber danken dem Thieme Verlag und den Leserinnen und Lesern für das nachhaltige Interesse an dem Querschnittsfach Nuklearmedizin.
Köln/Rossendorf, 2023
Markus Dietlein
Klaus Kopka
Matthias Schmidt

Gliomas are clinically challenging tumors due to their location and invasiveness nature, which often hinder complete surgical resection. The evaluation of the isocitrate dehydrogenase mutation status has become crucial for effective patient stratification. Through a transdisciplinary approach, we have developed an 18F-labeled ligand for non-invasive assessment of the IDH1R132H variant by using positron emission tomography (PET) imaging. In this study, we successfully prepared diastereomerically pure [¹⁸F]AG-120 with a copper-mediated radiofluorination approach of the stannyl precursor 6 without azeotropic drying on a TRACERlab FX2 N radiosynthesis module. In vitro internalization studies demonstrated significantly higher uptake of [¹⁸F]AG-120 in mutant IDH1R132H-U251 human high-grade glioma cells compared to wild-type IDH1-U251 cells (0.4 vs. 0.013% applied dose/μg protein at 120 min). In vivo studies conducted in mice, exhibited the excellent metabolic stability of [¹⁸F]AG-120, with parent fractions of 85% and 91% in plasma and brain at 30 min p.i., respectively. Dynamic PET studies with [¹⁸F]AG-120 in naïve mice and orthotopic glioma rat model reveal limited blood-brain barrier permeation along with a low uptake in the brain tumor. Interestingly, there was no significant difference in uptake between mutant IDH1R132H- and wild-type IDH1-tumors (tumor-to-blood ratio [40-60min]: ~1.7 vs. ~1.3). In conclusion, our preclinical evaluation demonstrated a target-specific internalization of [¹⁸F]AG-120 in vitro, a high metabolic stability in vivo in mice, and a slightly higher accumulation of activity in IDH1R132H-glioma compared to IDH1-glioma. Overall, our findings contribute to advancing the field of molecular imaging and encourage the evaluation of [¹⁸F]AG-120 to improve diagnosis and management of gliomas and other IDH1R132H-related tumors.

Urychlování iontů pomocí laserových impulzů se těší zvláštní pozornosti pro svoje významné aplikace, jako je hadronová terapie v onkologii a použití v materiálové a jaderné fyzice. Použitím plazmové závěrky (velmi tenké pevnolátkové fólie – plasma shutter) je možné tvarovat profil laserového impulsu, např. zmírnění předpulzu, generace strmě stoupající náběžné hrany a lokální zvýšení intenzity. V této práci jsme simulovali danou interakci vysoce-intenzivního laserového impulsu s plazmovou závěrkou a pevnolátkovým terčem pomocí 3D particle-in-cell (PIC) simulací. Aplikace plazmové závěrky měla za následek zvýšení maximální energie iontů a snížení divergence generovaného iontového svazku. Dále jsme 2D výsledky zkombinovaly hydrodynamickými simulacemi předpulzu pro použití dvojité závěrky, jejíchž prototyp byl připraven na ČVUT. Výsledky našich 3D simulací jsou také reprezentovány prostřednictvím interaktivní vizualizace ve virtuální realitě.

(The acceleration of ions by laser pulses has received particular attention for its important applications, such as hadron therapy in oncology and applications in materials and nuclear physics. By using a plasma shutter (a very thin solid-state film), it is possible to shape the profile of the laser pulse, e.g. to reduce the prepulse, generate a steeply rising leading edge and locally increase the intensity. In this work, we simulated the given interaction of a high-intensity laser pulse with a plasma shutter and a solid-state target using 3D particle-in-cell (PIC) simulations. The application of the plasma shutter resulted in an increase in the maximum ion energy and a decrease in the divergence of the generated ion beam. Furthermore, we combined the 2D results with hydrodynamic simulations of the prepulse to apply a double shutter, a prototype of which was prepared at the CTU. The results of our 3D simulations are also represented through interactive visualization in virtual reality.)

The retention of fission products in the form of aerosols and volatile species of iodine by bubbling them into liquid solution is known as pool scrubbing. It occurs frequently during accident scenarios such as SGTR (Steam Generator Tube Rupture), core meltdown and in BWR (boiling water reactor) suppression pool and FCVS (filtered containment venting system). Pool scrubbing is featured by complex hydrodynamics. The flow regime can be divided into injection, transition and bubble rise three zones. In each zone, different phenomena or mechanisms control the scrubbing of particles, e.g. globule breakup in the injection and transition zone, and swarm effect in the rise zone. Pool scrubbing codes were mostly developed in the 1980’s and 1990’s such as SUPRA, SPRAC and BUSCA, which have been widely used in the nuclear safety analysis. One major weakness of the lumped parameter codes is that they rely on various empirical correlations and assumptions, whose validity range is often limited. For example, the globule size in the jet regime and the rise velocity of large bubbles are found to be underestimated. CFD (computational fluid dynamics) has the advantage of resolving the gas-liquid interface and flow field inside the pool, capturing the coalescence and breakup of bubbles locally and physically. In the frame of IPRESCA project, several CFD studies on pool scrubbing have been published, using both VOF and two-fluid approaches. For three-dimensional large-scale pool simulations, the interface-tracking method is mainly restricted by high computational load and insufficient mesh resolution, while two-fluid method by the limitations in closure models. Reliable modelling of the processes, e.g. globule breakup in high-velocity injection zone, multiphase turbulence, interphase heat transfer, particle removal as well as bubble burst and entrainment at the free surface, remains a challenge.

The removal of aerosols, vapor as well as soluble gases by injecting the mixture into a water pool is referred to as pool scrubbing, which is known to be an effective means for mitigating the source term during severe nuclear accidents. The pool hydrodynamics and bubble dynamics has a significant effect on the retention efficiency, which is however still far from being understood due to the complexity of the process. One-dimensional system or lumped parameter codes are routinely used for the calculation of the decontamination factor, which describes the particle removal capability of a pool scrubbing process. These codes rely on a number of empirical correlations, e.g. for the determination of bubble size and shape, which are correlated with some global and geometrical parameters such as nozzle diameter, submergence and injection velocity. Because of limited data and knowledge, the validity of these correlations is largely limited. Computational Fluid Dynamics (CFD) has the advantage of resolving local flow field and phenomena and is able to provide more insights in the bubble dynamics. In the frame of IPRESCA project, HZDR is participating in the work package 3.1 “bubble dynamics -CFD”. The main activities include three types of CFD simulations, respectively using: a) two-fluid model, where both mono-disperse and poly-disperse approaches are investigated, b) VOF interface-tracking method, and c) hybrid method, which incorporates the two-fluid and VOF models in one framework. The results shown possibilities and challenges of CFD in applying to pool scrubbing, and further efforts are needed.

Molybdenum disulfide (MoS2) few-layer films have gained considerable attention for their possible applications in electronics, optics, and also as a promising material for energy conversion and storage. Intercalating alkali metals, like lithium, offers the opportunity to engineer the electronic properties of MoS2. However, the influence of lithium on the growth of MoS2 layers has not been fully explored. Here, we have studied how lithium affects the structural and optical properties of the MoS2 few-layer films prepared using a new method based on one-zone sulfurization with Li2S as a source of the lithium. This method enables incorporation of Li into octahedral and tetrahedral sites of the already prepared MoS2 films or during the MoS2 formation. Our results discover an important effect of lithium promoting the epitaxial growth and horizontal alignment of the films. Moreover, we have observed a vertical-to-horizontal reorientation in vertically aligned MoS2 films upon lithiation. The measurements show long-term stability and preserved chemical composition of the horizontally aligned Li-doped MoS2.

Biogas is an important driver in carbon-neutral energy sources. Many biogas digester setups, however, are not well optimized and waste energy or fail to maximize their gas output potential. To optimize these systems, a framework was developed to measure and predict digester systems’ efficiencies by closely monitoring fluid movements. This framework includes a numerical calculation of fluid behavior (Computational Fluid Dynamics (CFD)), and Deep Learning to estimate the fluid shear-rates introduced by the agitator’s action. Additionally, a novel measurement system is presented that can measure the same metrics, as simulated, in real-world environments. Lastly, an outlook is given that presents the options and extensions of the presented setup to reduce prediction error, minimize measuring efforts further, and recommend optimization approaches to the operator.

Geometry optimization
Directory `calc_structure_optimization_ReaxFF`: calculation files of the structure optimization of all studied structures, done with ReaxFF.
Directory `calc_structure_optimization_DFT`: validation calculation files of the ReaxFF-optimized structures using DFT optimization.
Electronic structure calculations
Directory `calc_electronic_properties_DFT`: calculation files of electronic structure calculations on the DFT level.
Directory `calc_electronic_properties_DFTB`: calculation files of electronic structure calculations on the DFTB level
Results
Directory `structures_rigidly_twisted`: structure files in cif format of the rigidly twisted (flat) systems, labeled by their twist angle.
Directory `structures_fully_optimized`: structure files in cif format of the fully ReaxFF-optimized systems, labeled by their twist angle.
Directory `movies`: visualization of the change of the interlayer distance landscape and the strain fields with the twist angle.
Additionally, the script `plot_interlayer_distance.py` is included, which was used to create the individual frames of the movie showing the interlayer distance.

Manipulating the interlayer twist angle is a powerful tool to tailor the properties of layered two-dimensional crystals. The twist angle has a determinant impact on these systems’ atomistic structure and electronic properties. This includes the corrugation of individual layers, formation of stacking domains and other structural elements, and electronic structure changes due to the atomic reconstruction and superlattice effects. However, how these properties change with the twist angle, θ, is not yet well understood. Here, we monitor the change of twisted bilayer MoS2 characteristics as a function of θ. We identify distinct structural regimes, each with particular structural and electronic properties. We employ a hierarchical approach ranging from a reactive force field through the density-functional-based tight-binding approach and density-functional theory. To obtain a comprehensive overview, we analyzed a large number of twisted bilayers with twist angles in the range of θ = 0.2◦ . . . 59.6◦. Some systems include up to half a million atoms, making structure optimization and electronic property calculation challenging. For 13◦ ⪅ θ ⪅ 47◦, the structure is well-described by a moir ́e regime composed of two rigidly twisted monolayers. At small twist angles (θ ≤ 3◦ and 57◦ ≤ θ), a domain-soliton regime evolves, where the structure contains large triangular stacking domains, separated by a network of strain solitons and short-ranged high-energy nodes. The corrugation of the layers and the emerging superlattice of solitons and stacking domains affects the electronic structure. Emerging predominant characteristic features are Dirac cones at K and kagome bands. These features flatten for θ approaching 0◦ and 60◦. Our results show at which range of θ the characteristic features of the reconstruction, namely extended stacking domains, the soliton network, and superlattice, emerge and give rise to exciting electronics. We expect our findings also to be relevant for other twisted bilayer systems.

"ReaxFF_structure_optimization.zip": contains the inputs and outputs for all structure optimizations for ML, BL, and tBL systems using the Reax force field, performed using LAMMPS.
" bilayer_verification_ReaxFF_with_DFT.zip": contains the inputs and outputs for verifying the results of the Reax force field by running DFT geometry optimization and total energy calculations in FHI-aims for the high-symmetry bilayer stackings.
"QATK_band_structures_and_eff_mass.zip": contains the inputs and outputs of all calculations done via QuantumATK (QATK), including calculations for ML, BL, and tBL systems on DFT and DFTB level of theory.
"TB_fit.zip": contains the Python scripts and input data (DFTB band structure) used to fit the TB Hamiltonians as described in the Methods section and shown in the Supplementary Material.
"effective_masses_from_bands.zip": contains the extraction of the effective hole masses from the bands calculated at the DFTB level of theory in QATK.

Angeli and MacDonald reported a superlattice-imposed Dirac band in twisted bilayer molybdenum disulphide (tBL MoS2) for small twist angles towards the R_h^M (parallel) stacking. Using a hierarchical set of theoretical methods, we show that the superlattices differ for twist angles with respect to metastable R_h^M (0°) and lowest-energy H_h^h (60°) configurations. When approaching R_h^M stacking, identical domains with opposite spatial orientation emerge. They form a honeycomb superlattice, yielding Dirac bands and a lateral spin texture distribution with opposite-spin-occupied K and K’ valleys. Small twist angles towards the H_h^h configuration (60°) generate H_h^h and H_h^X stacking domains of different relative energies and, hence, different spatial extensions. This imposes a symmetry break in the moiré cell, which opens a gap between the two top-valence bands, which become flat already for relatively small moiré cells. The superlattices impose electronic superstructures resembling graphene and hexagonal boron nitride into trivial semiconductor MoS2.

PtSe2 is a promising 2D material for nanoelectromechanical sensing and photodetection in the infrared regime. One of its most compelling features is the facile synthesis at temperatures below 500 °C, which is compatible with current back-end-of-line semiconductor processing. However, this process generates polycrystalline thin films with nanoflake-like domains of 5 to 100 nm size. To investigate the lateral quantum confinement effect in this size regime, we train a deep neural network to obtain an interatomic potential at DFT accuracy and use that to model ribbons, surfaces, nanoflakes, and nanoplatelets of PtSe2 with lateral widths between 5 to 15 nm. We determine which edge terminations are the most stable and find evidence that the electrical conductivity is localized on the edges for lateral sizes below 10 nm. This suggests that the transport channels in thin films of PtSe2 might be dominated by networks of edges, instead of transport through the layers themselves.

This work adapts the schlieren technique for in-situ measurement of temperature fields around gas bubbles growing during water electrolysis. First, the optical setup and the algorithm of data processing are explained. The method is then validated by comparing measurements near a laser-heated spherical thermocouple with numerical simulations. Further validation is obtained by comparing with temperature data measured earlier by a different method near a hydrogen bubble generated at a platinum microelectrode. The schlieren technique is shown to deliver accurate temperature distributions with an uncertainty of less than 15%. The method was then used to investigate the temperature distribution near hydrogen bubbles during growth at different cathodic potentials. Additionally, particle tracking velocimetry was used to visualize the Marangoni flow pattern generated by strong Joule heating near the bubble foot. Combining the information from schlieren and PTV imaging allows to provide a more complete understanding of the fluid dynamics and heat transfer around gas bubbles growing during electrolysis.

The continuous evolution of photon sources and their instrumentation enables more and new scientific endeavors at ever increasing pace. This technological evolution is accompanied by an exponential growth of data volumes of increasing complexity, which must be addressed by maximizing efficiency of scientific experiments and automation of workflows covering the entire data lifecycle, aiming to reduce data volumes while producing FAIR and open data of highest reliability. This papers briefly outlines the strategy of the league of European accelerator-based photon sources user facilities to achieve these goals collaboratively in an efficient and sustainable way which will ultimately lead to an increase in the number of publications.

One of the main approaches to increase the tool lifetime during dry machining of “hard-to-machine” aerospace alloys is self-lubrication by the incorporation of noble metals in hard matrixes with good mechanical and diffusion barrier properties. In this paper, the diffusion of an Ag-rich layer sandwiched between two layers of either TiN or TiSiN is studied by transmission electron microscopy and in situ Rutherford backscattering spectrometry. The layer stacks were subjected to annealing treatments at 600 ºC and 800 ºC for 2 hours. Three processes were found to control the diffusion of silver: the morphology of the “sandwich” layers, the formation of small voids in the involved interfaces and the sublimation of Ag in the surface at temperatures near the melting point. The study revealed that the dense TiSiN matrix allowed a significantly better control of Ag diffusion than the more open TiN matrix.

In this talk, I will present our recent advancements in utilizing machine learning 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 at finite 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 has resulted in significant savings in computational resources when identifying optimal neural network architectures, thereby laying the foundation for large-scale 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]. 

[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).

ASL was invented pre-clinically in 19901. The first human applications appeared in 1996 when the post-labeling delay (PLD) was introduced to compensate for the larger distance between labeling in the neck and readout in the brain2. The initially low clinical reliability improved with the implementation of background suppression in 19993,4, the increasing availability of 3T MRI, and the invention of pseudo-continuous ASL in 20085. In 2012, the European COST-action BM1103 "ASL In Dementia” was founded and worked towards reducing the ASL differences between MRI scanners to improve between-center reproducibility. Together with other ISMRM ASL investigators, this resulted in the 2014 consensus paper that recommended single-PLD PCASL with a 3D readout, background suppression, no vascular crushing, the acquisition of a separate M0 image, and a simplified single-compartment quantification model for clinical ASL6.

Hydrodynamics and mass transfer characteristics are analyzed in a bubble column subjected to simulated ship motions using a hexapod robot with six-degree-of-freedom motions. Wire-mesh sensors have been used for collecting local gas holdup and flow patterns under non-reactive conditions. Additionally, the electrical conductivity of the liquid phase during CO2 uptake was extracted to determine hydroxide ion consumption rates as an indicator of mass transfer. The two-phase flow patterns in the bubble column operating under offshore conditions deviate significantly from the stationary ones due to the buoyancy-driven lateral migration of bubbles. The consumption rates of hydroxide ions during the chemical absorption of CO2 revealed that the amplitude of oscillations imposed on the bubble column is the dominant factor for the mass transfer in moving columns. Contrarily, the effect of the oscillation frequency is negligible, which is attributed to bubble coalescence and bubble flow maldistribution in the bubble column subjected to rotational oscillations. Bubble-free zones are formed in the liquid phase because of the buoyancy effects in the column tilted from the vertical axis, while the frequency of the oscillations does not add any additional effects to the bubble kinematics. The latter is attributed to the low shear rates maintained over the range of frequencies simulating marine swells.

This study presents a recycling initiative conducted at STENA Recycling GmbH, focusing on the systematic recycling of 100 refrigerators. The recycling process employed a combination of manual dismantling, depollution, and mechanical techniques. Manual dismantling followed a predefined protocol to extract various materials, while the mechanical process involved shredding, zigzag separation, magnetic separation, and eddy current separation to isolate different components. The recovered materials were analyzed and categorized, providing valuable insights into the composition of refrigerator elements. Simulations were then performed to recover metals from the ferrous and non-ferrous fractions using pyrometallurgical methods. An Electric Arc Furnace (EAF) was utilized for iron recovery, while a Re-smelter process was employed for aluminum recovery, and a reducing-oxidation process was used for copper recovery. HSC Sim software and FactSage were utilized for accurate thermodynamic calculations and simulations. Furthermore, the environmental impact of the recycling process was evaluated through a Life Cycle Assessment (LCA) using Open LCA software. The LCA analysis provided insights into the environmental burdens associated with the recycling process and facilitated the identification of potential areas for improvement. The study highlights the effective utilization of resources, waste reduction, and sustainable practices in the recycling industry, considering both material recovery and environmental considerations.

The formation and behavior of gas bubbles is experimentally investigated in a liquid metal downward pipe flow, a configuration that largely corresponds to the situation in a submerged entry nozzle (SEN) in the continuous casting process in steel making. The experimental mockup is operated at room temperature using the ternary alloy GaInSn as model fluid. Argon gas is injected through an orifice located in the SEN wall. The gas distribution in the pipe is visualized by means of the X-ray radiography. The set-up is completed by an electromagnetic stirrer, which is used to create a swirling flow in the tube. Depending on the volume flow rates of the gas and the liquid metal, as well as the intensity of the swirl flow generated by the stirrer, 4 flow regimes are observed: (1) the formation of an almost stationary gas pocket in the region below the injection point without any electromagnetic stirring, (2) a twisted void zone along the side wall, (3) a straight void zone in the center of the pipe, and (4) a bubble chain in the core of the pipe flow. The experiments reveal that the wetting conditions at the inner SEN wall have a decisive influence on the resulting flow regime.

Photonic integrated circuits require photodetectors that operate at room temperature with sensitivity at telecom wavelengths and are suitable for integration with planar complementary-metal-oxide-semiconductor (CMOS) technology. Silicon hyperdoped with deep-level impurities is a promising material for silicon infrared detectors because of its strong room-temperature photoresponse in the short-wavelength infrared region caused by the creation of an impurity band within the silicon band gap. In this work, we present the first experimental demonstration of lateral Te-hyperdoped Si PIN photodetectors operating at room temperature in the optical telecom bands. We provide a detailed description of the fabrication process, working principle, and performance of the photodiodes, including their key figure of merits. Our results are promising for the integration of active and passive photonic elements on a single Si chip, leveraging the advantages of planar CMOS technology.

The data includes physical contact network of employees.

Effective personnel scheduling is crucial for organizations to match workload demands. However, staff scheduling is sometimes affected by unexpected events, such as the COVID-19 pandemic, that disrupt regular operations. Limiting the number of on-site staff in the workplace together with regular testing is an effective strategy to minimize the spread of infectious diseases like COVID-19 because they spread mostly through close contact with people. Therefore, choosing the best scheduling and testing plan that satisfies the goals of the organization and prevents the virus’s spread is essential during disease outbreaks. In this paper, we formulate these challenges in the framework of two Mixed Integer Non-linear Programming (MINLP) models. The first model aims to derive optimal staff occupancy and testing strategies to minimize the risk of infection among employees, while the second is aimed only at optimal staff occupancy under a random testing strategy. To solve the problems expressed in the models, we propose a canonical genetic algorithm as well as two commercial solvers. Using both real and synthetic contact networks of employees, our results show that following the recommended occupancy and testing strategy reduces the risk of infection 25–60% under different scenarios. The minimum risk of infection can be achieved when the employees follow a planned testing strategy. Further, vaccination status and interaction rate of employees are important factors in developing scheduling strategies that minimize the risk of infection.

Despite the fundamental and technological importance of the elastic constants, a suitable method
for their full characterization in epitaxial films is missing. Here we show that transient grating
spectroscopy (TGS) with highly 𝑘−vector-selective generation and detection of acoustic waves
is capable of determination of all independent elastic coefficients of an epitaxial thin film
grown on a single-crystalline substrate. This experimental setup enables detection of various
types of guided acoustic waves and evaluation of the directional dependence of their speeds
of propagation. For the studied model system, which is a 3 μm thin epitaxial film of the NiTi
shape memory alloy on an MgO substrate, the TGS angular maps include Rayleigh-type surface
acoustic waves as well as Sezawa-type and Love-type modes, delivering rich information on
the elastic response of the film under different straining modes. The resulting inverse problem,
which means the calculation of the elastic constants from the TGS maps, is subsequently solved
using the Ritz-Rayleigh numerical method. Using this approach, tetragonal elastic constants of
the NiTi film and their changes with the austenite→martensite phase transition are analyzed.

Density Functional Theory (DFT) is a widely used method for computing numerous properties in materials science and chemistry. Despite its usefulness, its inherent computational scaling with system size often limits its applicability and makes large-scale simulations infeasible. Our team develops a machine-learning approach to accelerate Kohn-Sham DFT calculations using deep neural networks within the Materials Learning Algorithms (MALA) Python framework. Our method employs bispectrum descriptors to encode roto-translationally equivariant representations of atomic neighborhoods as input to the neural networks. The networks then predict the local density of states (LDOS) from which various quantities of interest can be calculated. Our MALA models are trained on DFT data which serve as the ground-truth for the machine-learning models. Our MALA models significantly reduce the computational demands compared to conventional DFT methods. In this poster, we demonstrate the efficacy of our approach on a system of hydrogen molecules under various pressure and temperature conditions, showcasing the potential of our methods for molecular systems. Furthermore, we explore the use of SE(3)-equivariant graph neural networks (equiformer GNNs) to enhance the generalizability and extrapolation capabilities of our models while further reducing the computational cost. Our results indicate that the MALA framework provides a powerful and efficient tool for accelerating Kohn-Sham DFT calculations in molecular systems. The proposed approach has the potential to revolutionize the field of materials science by enabling researchers to perform large-scale simulations and explore complex molecular systems more efficiently. This work paves the way for future research in developing advanced machine-learning algorithms for accelerating electronic structure calculations and determining properties in materials science and chemistry both accurately and efficiently.

We present advances in the development of our multi-physics hydrodynamic code, which is designed for simulations of interaction of a laser with a solid target. Unlike the classical codes in this field, it applies the Lagrangian formulation of magnetohydrodynamics, which is ideally suited for the rapid expansion or compression of the matter during the laser-target interaction. Moreover, it is based on the modern high-order curvilinear finite elements, providing the code computational efficiency, flexibility and precision. The construction and models included in code are charted and the design of the new Arbitrary Lagrangian-Eulerian extension is presented with an outline of the possible applications.

This module introduces computer vision and deep learning algorithms with applications to physics problems. It covers the basics of extracting trajectories and dynamics from videos of physical phenomena, as well as how computer vision algorithms work for detection and tracking of objects. Students will gain an understanding of how information is extracted from pixels from first principles and then learn how to apply commonly used computer vision libraries. By the end of this module, participants will have an understanding of the use of computer vision and deep learning algorithms and can apply them to analyze videos from lab experiments.

Technetium-99 (⁹⁹Tc) is a long-lived fission product (2.13∙10⁵ years) of uranium-235 (²³⁵U) and plutonium-239 (²³⁹Pu) and therefore, of great concern for the long-term safe management of nuclear waste. The migration of Tc in the environment is highly influenced by the redox conditions since Tc may be present in various oxidation states. Depending on the chemical properties of environmental relevant systems Tc is expected to mainly occur as Tc(VII) and as Tc(IV) under oxidizing and reducing conditions, respectively. The anion pertechnetate (Tc(VII)O₄⁻) is known to barely interact with mineral surfaces; this, in turn, enhances its migration in groundwater and favours its entry into the biosphere. On the contrary, the formation of Tc(IV) limits the migration of Tc since it forms a low soluble solid (TcO₂) and/or species whose interaction with minerals is more favourable. In the last decades Tc migration has been focused on the reduction of Tc(VII) to Tc(IV) by various reductants, such as Fe(II), Sn(II) or S(-II) either present in solution, taking part in mineral structures, (Pearce et al., 2019) or metabolically induced by microbial cascades (Newsome et al., 2014).
We have studied the immobilization of Tc by various Fe(II)-containing phases: Fe²⁺ pre-sorbed on alumina nanoparticles (Mayordomo et al., 2020), Fe(II)-Al(III) layered double hydroxide (Mayordomo et al., 2021), and Fe(II) sulfides (Rodriguez et al., 2020; Rodríguez et al., 2021). We have combined sorption experiments, with microscopic and spectroscopic techniques (scanning electron microscopy, Raman microscopy, X-ray photoelectron spectroscopy, infrared spectroscopy, and X-ray absorption spectroscopy) to elucidate the mechanisms responsible of Tc(VII) reductive immobilization.
Those works have been focused on binary systems i.e., studies of the interaction of Tc with a given reductant. However, the environment is a complex system where different components often depend on and modify each other. Thus, Tc migration is susceptible and varies upon environmental conditions and should not be studied in an isolated manner. The young investigator group TecRad (HZDR, 2022), funded by the German Federal Ministry of Education and Research, aims at analyzing Tc chemistry from a wider perspective. Our goal is to study the biogeochemical behavior of Tc when it interacts with: i) microorganisms, ii) metabolites, iii) Fe(II) minerals, and iv) Fe(II) minerals in presence of metabolites.
An important part of this project deals with implementing new spectro-electrochemical methods to monitor in-situ the behavior of Tc in solution and at interfaces as a function of the redox potential. With these tools, we aspire at characterizing the molecular structures of Tc species under a variable range of redox conditions, to broaden the understanding of the chemical behavior of the pollutant.
We aim at generating valuable thermodynamic data (complex formation constants, solubility constants of minerals, redox potentials and Tc distribution coefficients) that will be uses to implement a geochemical modeling able to explain Tc environmental fate even under different redox conditions.
The authors acknowledge the German Federal Ministry of Education and Research (BMBF) for the financial support of NukSiFutur TecRad young investigator group (02NUK072) and the German Federal Ministry of Economic Affairs and Climate Action (BMWK, former BMWi) for the financial support of Vespa II (02E11607B).

References

HZDR 2022, accessed March 29th. https://www.hzdr.de/db/Cms?pNid=1375.

Mayordomo, N., Rodríguez, D.M., Rossberg, A., Foerstendorf, H., Heim, K., Brendler, V., Müller, K., 2021. Analysis of technetium immobilization and its molecular retention mechanisms by Fe(II)-Al(III)-Cl layered double hydroxide. Chem. Eng. J. 408, 127265. doi:10.1016/j.cej.2020.127265

Mayordomo, N., Rodríguez, D.M., Schild, D., Molodtsov, K., Johnstone, E. V., Hübner, R., Shams Aldin Azzam, S., Brendler, V., Müller, K., 2020. Technetium retention by gamma alumina nanoparticles and the effect of sorbed Fe2+. J. Hazard. Mater. 388, 122066. doi:10.1016/j.jhazmat.2020.122066

Newsome, L., Morris, K., Lloyd, J.R., 2014. The biogeochemistry and bioremediation of uranium and other priority radionuclides. Chem. Geol. 363, 164–184. doi:10.1016/j.chemgeo.2013.10.034

Pearce, C.I., Moore, R.C., Morad, J.W., Asmussen, R.M., Chatterjee, S., Lawter, A.R., Levitskaia, T.G., Neeway, J.J., Qafoku, N.P., Rigali, M.J., Saslow, S.A., Szecsody, J.E., Thallapally, P.K., Wang, G., Freedman, V.L., 2019. Technetium immobilization by materials through sorption and redox-driven processes: A literature review. Sci. Total Environ. 132849. doi:10.1016/j.scitotenv.2019.06.195

Rodriguez, D.M., Mayordomo, N., Scheinost, A.C., Brendler, V., Müller, K., Stumpf, T., 2020. New insights into 99Tc(VII) removal by pyrite : A spectroscopic approach. Env. Sci. Technol. 54, 2678–2687. doi:10.1021/acs.est.9b05341

Rodríguez, D.M., Mayordomo, N., Schild, D., Shams Aldin Azzam, S., Brendler, V., Müller, K., Stumpf, T., 2021. Reductive immobilization of 99Tc(VII) by FeS2: the effect of marcasite. Chemosphere 281, 130904. doi:10.1016/j.chemosphere.2021.130904

Techntium-99 (⁹⁹Tc) is one of the most concerning fission products due to its long half-life (2.13∙10⁵ years) and the high mobility of the anion pertechnetate (TcO₄⁻) [1]. Tc migration decreases significantly when Tc(VII) is reduced to Tc(IV). This scavenging step can be induced by Fe(II) minerals, which have been widely studied due to their versatility, low cost, and ubiquity [2]. In addition, Fe(II) minerals will play an important role in the near-field of the nuclear waste repository, in case that corrosion of the waste canisters will occur and radioactive material be leaked in the environment.
Green rust is formed when Fe²⁺ interacts with Fe(III) minerals [3]. Thus, its presence is expected in both the near- and far-field of a repository. It is a Fe(II)-Fe(III) hydroxide that can immobilize radionuclides by adsorption, anion exchange, and reduction mechanisms. A previous work reports the interaction of green rust with Tc, but the results are limited to very narrow experimental conditions [4]. Thus, further studies are needed to both identify the optimal Tc scavenging conditions by green rust and the mechanism responsible of Tc retention.
Our studies consisted of a combination of batch contact studies, microscopic and spectroscopic analysis. Batch contact studies were performed under a wide range of conditions, i.e. pH (3.5 - 11.0), Tc concentration (nM - mM), and ionic strength (0.0 - 0.1 M). X-ray powder diffraction, Raman microscopy, X-ray photoelectron spectroscopy (XPS), and X-ray absorption spectroscopy provided information on Tc oxidation state and speciation as well as on secondary redox products related to the Tc interaction with chloride green rust (GR(Cl)). In addition, re-oxidation experiments have been performed for one year to analyze the Tc retention reversibility.
The results show that GR(Cl) removes Tc from solution with efficiencies between 80% (Kd = 8.0∙10³ mL/g) and ≈ 100% (Kd = 9.9∙10⁵ mL/g) for pH > 6.0 (Figure 1). In contrast, Tc removal for pH < 6.0 drops with decreasing pH, and ranges from 80% to 50% (Kd = 2.0∙10³ mL/g), reaching a minimum at pH 3.5.

XPS analysis reveals the predominance of Tc(IV) at all evaluated pH values (3.5 to 11.5), supporting that Tc reductive immobilization is the main retention mechanism. Re-oxidation experiments show that Tc is slowly solubilized when time increases.
The analysis of the extended X-ray absorption fine structure indicates a change of the Tc(IV) atomic environment depending on pH and Tc loading. The most probable structural rearrangements are represented by Tc(IV) sorption on Fe(III) minerals formed as secondary phases with Tc polynuclear species contribution.

The authors acknowledge the German Federal Ministry of Education and Research (BMBF) for the financial support of the NukSiFutur TecRad young investigator group (02NUK072) [5].

References
[1] Meena, A. H. and Arai, Y (2017). Environmental geochemistry of technetium. Env. Chem. Lett. 15: 241-263.
[2] Pearce, C. I. et al. (2020). Technetium immobilization by materials through sorption and redox-driven processes: A literature review. Sci. Total Environ. 716: 132849.
[3] Usman, M. et al (2018). Magnetite and green rust: Synthesis, Properties, and Environmental Applications of Mixed-Valent Iron Minerals. Chem. Rev. 118: 3251-3304.
[4] Pepper, S. et al. (2003). Treatment of radioactive wastes: An X-ray absorption spectroscopy study of the reaction of technetium with green rust. J. Colloid Interface Sci. 268: 408-412.
[5] TecRad webpage: https://www.hzdr.de/db/Cms?pNid=1375, vis. Feb 9th 2023.

The controlled, self-assembled synthesis of multinuclear coordination compounds can be performed via different approaches. Frequently, steric, geometric and/or electronic factors located at the ligand systems predefine the way in which metal ions can assemble them to large aggregates. For the compounds in the present paper, also the Pearson’s acidities and preferred coordination geometries of the metal ions have been used as organization principles. The ligand under study, 2,6-dipicolinoylbis(N,N-diethylthiourea), H2L1ethyl, possesses ‘soft’ sulfur and ‘hard’ nitrogen and oxygen donors. One-pot reactions of this compound with [AuCl(tht)] (tht = tetrahydrothiophene) and M3+ salts (M = Sc, Y, La, Ln, Ga, In) give products with gold-based {Au3(L1ethyl)3}3+ or {Au2(L1ethyl)2}2+ coronands, which host central M3+ ions. The formation of such units is templated by the M3+ ions and the individual size of the coronand rings is dependent on the ionic radii of the central ions in a way that small ions such as Ga3+ form a [Ga{Au2(L1ethyl)2}]+ assembly, while larger ions (starting from Sc3+/In3+) establish neutral [M{Au3(L1ethyl)3}] units with nine-coordinate central ions.

Technetium-99 (⁹⁹Tc) is a long-lived fission product (2.13∙10⁵ years) of uranium-235 (²³⁵U) and plutonium-239 (²³⁹Pu) and therefore, of great concern for the long-term safe management of nuclear waste. The migration of Tc in the environment is highly influenced by the redox conditions, since Tc may be present in various oxidation states. Under environmental conditions, Tc is expected to mainly occur as Tc(VII) under oxidizing conditions and as Tc(IV) under reducing conditions. The anion pertechnetate (Tc(VII)O₄⁻) is known to barely interact with mineral surfaces; this, in turn, enhances its migration in groundwater and favors its entry in the biosphere. On the contrary, the formation of Tc(IV) limits the migration of Tc since it forms a low soluble solid (TcO2) and/or species whose interaction with minerals is more favorable. In the last decades Tc migration has been focused on the reduction of Tc(VII) to Tc(IV) by various reductants, such as Fe(II), Sn(II) or S(-II) either present in solution, taking part in mineral structures, [1] or metabolically induced by microbial cascades [2].
Most of the published studies have been focused on binary systems i.e., studies of the interaction of Tc with a given reductant. However, the environment is a complex system where different components often depend on and modify each other. Thus, Tc migration is susceptible and varies upon environmental conditions and should not be studied in an isolated manner. The young investigator group TecRad [3], funded by the German Federal Ministry of Education and Research, aims at analyzing Tc chemistry from a wider perspective. Our goal is to study the biogeochemical behavior of Tc when it interacts with: i) microorganisms, ii) metabolites, iii) Fe(II) minerals, and iv) Fe(II) minerals in presence of metabolites.
An important part of this project deals with implementing new spectro-electrochemical methods to monitor in situ the behavior of Tc in solution and at interfaces as a function of the redox potential. With these tools we aspire at characterizing the molecular structures of Tc species under a variable range of redox conditions, to broaden the understanding of the chemical behavior of the pollutant.
Our goal is to generate valuable thermodynamic data (complex formation constants, solubility constants of minerals, redox potentials and Tc distribution coefficients) that we will use to implement a geochemical modeling able to explain Tc environmental fate even under different redox conditions.

The authors acknowledge the German Federal Ministry of Education and Research (BMBF) for the financial support of NukSiFutur TecRad young investigator group (02NUK072).

References
[1] Pearce, C. et al. (2020). Technetium immobilization by materials through sorption and redox-driven processes: A literature review. Sci. Total Env. 716: 132849.
[2] Newsome, L. et al. (2014). The biogeochemistry and bioremediation of uranium and other prioriy radionuclides. Chem. Geol. 363: 164-184.
[3] TecRad webpage: https://www.hzdr.de/db/Cms?pNid=1375 vis on February 9th 2023.

Robust and fast in-vivo treatment verification is expected to increase the clinical efficacy of proton therapy. The combined detection of prompt gamma-rays and neutrons has rececntly been proposed for this purpose and shown to increase the monitoring accuracy. However, the potential of this technique is not fully exploited yet since the proton range reconstruction relies only on a simple landmark of the particle production distributions. Here, we apply machine learning based feature selection and multivariate modelling to improve the range reconstruction accuracy of the system in an exemplary lung cancer case in silico. We show that the mean reconstruction error of this technique is reduced by 30 \% to 50 % to a root mean squared error (RMSE) per spot of 0.4 mm, 1.0 mm, and 1.9 mm for pencil beam scanning spot intensities of 1e8, 1e7, and 1e6 initial protons, respectively. The best model performance is reached when combining distributions features of both gamma-rays and neutrons. This confirms the advantage of hybrid gamma/neutron imaging over a single-particle approach in the presented setup and increases the potential of this system to be applied clinically for proton therapy treatment verification.

For a wide range of applications the structure of systems like Neural Networks or complex simulations, is unknown and approximation is costly or even impossible. Black-box optimization seeks to find optimal (hyper-) parameters for these systems such that a pre-defined objective function is minimized. Polynomial-Model-Based Optimization (PMBO) is a novel blackbox optimizer that finds the minimum by fitting a polynomial surrogate to the objective function.

Motivated by Bayesian optimization the model is iteratively updated according to the acquisition function Expected Improvement, thus balancing the exploitation and exploration rate and providing an uncertainty estimate of the model. PMBO is benchmarked against other state-of-the-art algorithms for a given set of artificial, analytical functions. PMBO competes successfully with those algorithms and even outperforms all of them in some cases. As the results suggest, we believe PMBO is the pivotal choice for solving blackbox optimization tasks occurring in a wide range of disciplines.

In recent years, research in plasma physics has made significant progress. One area of focus is the advancement of techniques for analyzing the ever-increasing amounts of data generated from experiments and simulations. This has led to the flourishing of novel machine learning and uncertainty quantification methods. Another direction of research is to enhance artificial-intelligence and machine-learning algorithms themselves by integrating knowledge about the studied systems into the inference process. This approach leads to the development of physics-informed algorithms, which take into account constraints such as energy or momentum conservation.

As machine learning and data-driven techniques continue to gain momentum in plasma physics research, we have compiled a collection of papers from authors who are actively involved in these areas. This special issue covers a wide range of topics, including physics-informed machine learning, reduced-complexity approaches, experimental design, and real-time control applications. In the following paragraphs, we provide a summary of each paper included in this issue.

The progress in the application of data-driven algorithms is largely driven by the increasing availability of training data. Accordingly, several papers in this special issue address the challenges of improved data generation, data augmentation, and data selection. Dave et al.[1] utilize generative adversial networks to synthesize time-series such as the plasma current, which can be used to train other algorithms. In the paper of Rath et al.,[2] time-series data augmentation is explored with a focus on the robust handling of outlying data points, leading to the use of Student-t processes instead of the more familiar Gaussian processes based on experimental data.

Interpolating machine-learning algorithms, such as Gaussian processes, often suffer from a super-linear run-time dependency on the amount of data. To address this challenge, Kremers et al.[3] propose a data thinning approach based on a two-step clustering that reduces the amount of redundant data. This allows for the removal of data points that have limited impact on the quality of the resulting model, reducing both computational costs and model complexity. Gaffney et al.[4] propose a different approach for collecting simulation data using ideas from active learning[5] and experimental design approaches.[6] They suggest generating simulation data primarily in information-rich regions.

In the field of artificial-intelligence and machine-learning algorithms, one recurring topic is the replacement of expensive simulator codes that encode the underlying physics processes with suitable emulators. These are algorithms that emulate the input–output relation of the simulator with significantly reduced computational effort. Depending on the application, emulators may be realized using neural networks, polynomial chaos expansions, or reduced complexity models. Emulators are often used to perform sensitivity studies or inferences that are otherwise numerically challenging using the underlying simulator. The paper of Köberl et al.[7] demonstrates such an application, analyzing the uncertainty of a 3D magnetohydrodynamic equilibrium reconstruction using an emulator based on polynomial chaos expansions. While other machine-learning methodologies are useful, neural networks are the most common emulators due to the availability of open-source libraries and generic applicability. In Honda et al.,[8] a convolutional neural network emulates gyrokinetic simulations and shows some promising generalization capabilities in predicting the heat fluxes of ions and electrons. Similarly, in Narita et al,[9] a neural network is used to compute diffusive and non-diffusive transport parameters of tokamak fusion plasmas. Cheng et al.[10] compare different machine-learning algorithms for predicting properties of helicon plasmas and conclude that their deep neural networks outperform other approaches.

Neural networks have very fast response times, which opens up the possibility of using them for real-time control or online monitoring diagnostic settings. Tang et al.[11] describe the implementation of a recurrent neural network as a disruption predictor into a control system intended to gracefully shut down the device before a damaging disruption can occur. Similarly, Morosohk et al.[12] describe an application of neural networks, using Thomson scattering diagnostic data for real-time profile reconstruction, allowing for improved machine control based on derived physics information.

The recent trend in machine learning, which incorporates physics knowledge, is reflected in the papers of T. Nishizawa[13] and T. M. Tyranowski et al.[14] In the former paper, transport parameters are inferred based on an integrated data analysis approach, using an appropriately constrained Gaussian process. In the latter paper, a reduced complexity model for the kinetic Vlasov equation is derived, taking the underlying Hamiltonian structure of the Vlasov equation into account. This model significantly improves upon standard approaches like dynamic mode decomposition or singular value decomposition.

The intersection between plasma physics research and data science is anticipated to become increasingly interconnected in the future. As such, it is our hope that this compilation of papers will serve as a valuable source of inspiration for future endeavors in this field.

Vibration measurements were carried out using highly sensitive accelerometers in an experimental ladle integrated into the LIMMCAST (Liquid Metal Model for Steel Casting) facility at HZDR. The model is operated with liquid Sn–40 wt pctBi alloy at 200°C, whose physical properties are close to those of molten steel. Three accelerometers were attached to the outer wall of the LIMMCAST vessel to record the vibrations caused by the argon bubble flow in the liquid metal at different process parameters. The results obtained at the liquid metal experiments differ from those reported for water models where the relationship between root mean square (RMS) value of the vibration amplitude and the gas flow rate follows different curve shapes. Furthermore, the results of vibration measurements in the LIMMCAST model are compared with vibration measurements in a steel plant during vacuum degassing. The comparison of the RMS data shows a fairly good agreement. This indicates that the vibrations in both the industrial process and the laboratory model are caused by the same physical mechanisms, and thus, the vibration behavior in an industrial steelmaking ladle can be reproduced quite well by suitable liquid metal models. These studies on bubble flows can help to improve the understanding of industrial stirring processes and thus contribute to a better process control.

Experimentelle Bestimmung der Aktivierung von deutschen Druckwasserreaktoren zur Validierung der Aktivitätsberechnungen

A sustainable future requires a responsible handling of our material and energy resources. However, our modern products are becoming increasingly complex with respect to the material combinations and their linkages. While we engineer multi-material structures against failure for the use phase, we also need them to be dismantled in the end-of-life phase during recycling. This describes a main functional contradiction of the structure under the scope of a circular economy and sustainability.
To achieve good material-specific recovery rates, materials locked in joints have to be liberated, which is typically achieved by breaking materials and joints in mechanical shredding processes. Unfortunately, no adequate models exist currently to describe these processes, which constitutes a missing link for a recycling-oriented design.
The presented approach models the shredding of multi-material structures with adhesion joint through numerical simulations using the finite element method (FEM). For shredding, a rotary shear is employed as usual first process stage in recycling. A rotary shear consists of two counter-rotating shafts with discs and V-shaped teeth turning at a fixed speed (circumferential velocity at teeth <0.5 m/s) and exerting tensile stresses in conjunction with bending and torsion (tearing stresses) on specimens. An A-frame dummy specimen for lightweight automotive applications was used consisting of a sheet steel top-hat profile with a glass fibre-reinforced polyamide composite layer and polyamide rib structure glued to it.
LS-DYNA software was used for explicit FE analysis as well as material models that consider the plasticity and failure of different materials and their interfaces. Furthermore, simulations were performed for different load cases, representing different orientations of the test specimen relative to the rotary shear as observed in experiments. A model evaluation workflow was developed in Python and R to quantify the shredding performance in terms of the metrics liberation degree, particle sizes and energy consumption.
Simulation results show high qualitative and quantitative agreement regarding deformation, fracture and liberation phenomena observed in previous experiments, e.g., brittle breakage of polymers into many fragments, partial to full detachment of adhesion joint, as well as high degree of plastic deformation of steel that sometimes even clamped-in polymer material thus forming new form-locking joints. One highlight is the realistic estimation of the mechanical energy consumption required for shredding. However, mass losses occur due to element deletion at failure, which are observed with increasing element size of the mesh. In addition, the model underestimates the number of generated fragments especially in the small size range (< 5 mm). Better results are expected by incorporating strain-rate dependent material behaviour in the future.
The developed simulation process could be integrated into a new design assistance tool for the conceptual design phase of multi-material structures with two main outcomes. First, to provide quantitative metrics linking the design and the failure behaviour during shredding of such structures, and consequently, to estimate the impact of design decisions on the recycling phase of a product enabling a recycling-oriented design.

We used acoustic pressure waves to control the bubble formation from a submerged sub-millimeter orifice. The method enables the controlled periodic formation of bubbles with a high degree of reproducibility. Therefore, we were able to generate a continuous stream of fine bubbles as small as the orifice itself. This has a high demand in many industrial applications and fundamental research at the time. Using high-speed videometry, we studied the mechanism of the bubble formation and detachment along with the effect of various parameters on the bubble size. The analysis of forces acting on a growing bubble revealed the decisive effect of the liquid inertia on the bubble detachment. Moreover, based on the experimental results, we derived new detachment criteria for the bubble departure. These criteria can be used as the boundary condition for modeling the temporal evolution of the bubble size as well as calculating the final bubble volume using the Rayleigh-Plesset equation.

Centered at the Jožef Stefan Institute, Ljubljana, Slovenia, five top research & innovation partners across Europe are creating an innovation hub to study microbe-colloid–surface interactions using high-tech methodologies and equipment. The SURFBIO Innovation Hub aims to provide biotechnology researchers, academic institutions, industry and policy makers with training services and assessments to optimize novel materials for a variety of applications and will offer new, industry-oriented, research services opened to industry and institutions, covering all the needs in only one Hub, and collecting the activities together. This will lead to the founding of a SURFBIO professional society to act as a network center with the goal of fostering advanced microbial materials applications throughout Europe.
Understanding the interactions of colloids (microorganisms, nanoparticles and biomolecules) with surfaces and between themselves is a key factor that can lead to improvements of advanced materials. As such the emerging field of Colloid Biology is positioned on the intersection between material science and molecular microbiology, dealing with artificial multispecies bio-aggregates, bio- films and bio-nano-constructs of bacteria and nanoparticles, to create novel advanced materials. The colloid-biological interactions can be studied and analyzed by applying different tools and techniques. Impacts of the networking activities will be:

• high-impact research results on surface and colloid biology
• improved knowledge transfer
• increased patenting
• increased peer-reviewed publications on the topic
• expanded range of testable samples
• contract research for industry
• boosted interest on surface and colloid biology
• standardization of methodologies
• new possibilities in analytical testing

In order to characterize the potential hazards of anthropogenic nanomaterials to humanity and the environment, as well as the successful implementation of SSbD approaches, it is imperative to have access to analytic tools that provide sensitive detection at low concentrations in complex media such as surface and waste water, sewage sludge, soil, biota, etc. against same element and particle backgrounds. The radiolabeling of nanomaterials provides these features for laboratory studies. We present an overview of our radiolabelling efforts with examples of their applications.
We have developed a library of radiolabelling methods for the most common anthropogenic nanomaterials, including nanoplastics, that allow us to track nanomaterials in release, mobility and uptake studies including such complex systems as waste water treatment plants, plants, water organisms and soil. The labeling techniques are the synthesis of the nanoparticles using radioactive starting materials, the binding of the radiotracer to the nanoparticles, the activation of the nanoparticles using proton/neutron irradiation, the recoil labeling utilizing the recoil of a nuclear reaction to implant a radiotracer into the nanoparticle, and the in-diffusion of radiotracers into the nanoparticles at elevated temperatures. Using these methods we have produced [105/110mAg]Ag, [124/125/131I]CNTs, [48V]TiO2, [139/141Ce]CeO2, [7Be]MWCNT, [64Cu]SiO2, [64Cu]PS, etc. for accurate quantification in complex media at an environmentally relevant low concentrations range even with a background of the same element and without complicated sample preparations necessary.
Using these approaches, we can go beyond mere quantification and gain mechanistic insights into nanomaterial behavior in the environment. For example, we have tracked the dissolution and internalization of CeO2 NP in freshwater shrimp, the dissolution of CdSe/ZnS quantum dots in waste water treatment or the size-dependent uptake of TiO2 in plants.

The current paper documents the Computational Fluid Dynamics (CFD) code validation activity, carried out at the Nuclear Research Center of Birine relevant of Atomic Energy Commission of Algeria as part of International Atomic Energy Agency (IAEA) Coordinated Research Project (CRP): Application of Computational Fluid Dynamics Codes for Nuclear Power Plant Design to assess the current capabilities of these codes and to contribute to technological progress in their verification and validation. A set of ROCOM CFD-grade test data of Pressurized Thermal Shock test (PTS) specifications was made available in the framework of this (CRP) by Helmholtz Zentrum Dresden-Rossendorf, (HZDR) Germany, to perform detailed calculations of the proposed test. The reference point is the injection of relatively cold core cooling water (ECC), which can induce buoyant stratification. The data obtained from the PTS experiment were compared with the results of Ansys-CFX calculations in this paper. Unsteady Reynolds-Averaged Navier-Stokes (URANS) model is used to examine the buoyancy-influenced flows in the reactor pressure vessel for condition where natural circulation is a dominant factor. The Shear Stress Transport (SST k-ω) turbulence model is used to take into account the turbulence effects on the mean flow. Calculation results show a good qualitative and quantitative agreement with the experiment data.