Publications Repository - Helmholtz-Zentrum Dresden-Rossendorf

In dieser Bachelorarbeit wurde ein Testprogramm für die Validierung der Stromdichteberechnung in der Current-Deposition-Phase des Particle-in-Cell-Codes PIConGPU [13] entwickelt. Ausgehend von der (diskretisierten) Kontinuitätsgleichung und unter Nutzung des Prinzips von Cloud-Shapes nach Hockney sowie Esirkepovs Methode und dem daraus hergeleiteten Konstrukt des Current-Deposition-Vektors wird eine rekursive Methode zur Berechnung der Stromdichte eines geladenen Teilchens in einem Gitter konstruiert. Diese berechnete Stromdichte wird in einem Vergleichsprogramm genutzt, um sie bei gleicher Teilchenbewegung mit dem Ergebnis von PIConGPU zu vergleichen. Anhand der relativen Abweichung des simulierten Ergebnisses der Stromdichte verifiziert oder falsifiziert das Vergleichsprogramm die Current-Deposition von PIConGPU. Damit eine standardisierte Verwendung des Tests zu ermöglicht wird, wird er durch zwei Bash-Skripte automatisch ausgeführt, sobald eine Änderung am Code von PIConGPU vorgenommen wurde. Dadurch können Fehler frühzeitig erkannt werden und ein möglichst einfacher und schneller Arbeitsfluss wird gewährleistet.

Plasma acceleration processes have garnered extensive research interest in recent years
due to the versatile applications of high-energy X-rays, including medical diagnostics and
treatment, semiconductor manufacturing, and the hardening of material surfaces. However,
simulating these processes demands a complex workflow and considerable computational
time, rendering in-situ analysis impractical. To mitigate these challenges, simulation-based
inference and data-driven methods for one-step inversion can be utilized to recover the
matching phase-space representation and elucidate the underlying physics.

This work presents the adaptation of a surrogate model specifically for plasma physics
processes, such as beam transport in a Free Electron Laser (FEL). A previously proposed
model, which uses a mixture of normalizing flows to learn multi-modal distributions, is
systematically investigated. Conditionality as a means of surrogate modeling in plasma
physics is investigated and trained on simulation results of plasma physics processes.

Initial experiments involved using various custom test distributions to derive key insights
into the model’s operation. Conditionality was incorporated into the model by utilizing the
single-view reconstruction provision appropriately, allowing it to handle a wider range of
input conditions. This conditioning has been introduced in two forms, scalar conditioning,
and one-hot vector conditioning, and the effectiveness of each method is studied. This
redefined architecture was rigorously tested on various test distributions with differing
characteristics to validate its performance. The reconstruction quality was then compared
to point clouds generated by single normalizing flow-based models with similar network
sizes. Additionally, a significant reduction in trainable parameters was achieved, making the
model more computationally feasible. Custom training protocols were introduced to further
reduce overall training time.

The enhanced architecture was subsequently applied to simulation data from a free electron
laser. A comprehensive analysis of the results demonstrated the surrogate model’s capability
to accurately capture the complex dynamics of plasma acceleration processes. This work
highlights the potential of advanced surrogate models in reducing computational demands
and providing deeper insights into plasma physics, paving the way for more efficient and
practical applications in high-energy X-ray technologies.

Es wird der Cowan-Cole-Kärkkäinen (CCK) Maxwell Solver in PIConGPU implementiert und validiert. Der CCK Solver hat gegenüber dem standard Yee Solver den Vorteil, dass er entlang der Achse mit dem geringsten Gitterabstand dispersionsfrei ist. Dadurch wird beispielsweise bei Laser Wakefield Acceleration Simulationen keine numerische Cherenkov Strahlung erzeugt. Dabei wird die in der Simulation beobachtbare Phasengeschwindigkeit einer Welle mit den theoretischen Werten aus den numerischen Dispersionsrelationen verglichen.

Change detection (CD) from remote sensing (RS) images using deep learning has been widely investigated in the literature. It is typically regarded as a pixel-wise labeling task that aims to classify each pixel as changed or unchanged. Although per-pixel classification networks in encoder-decoder structures have shown dominance, they still suffer from imprecise boundaries and incomplete object delineation at various scenes. For high-resolution RS images, partly or totally changed objects are more worthy of attention rather than a single pixel. Therefore, we revisit the CD task from the mask prediction and classification perspective and propose MaskCD to detect changed areas by adaptively generating categorized masks from input image pairs. Specifically, it utilizes a cross-level change representation perceiver (CLCRP) to learn multiscale change-aware representations and capture spatiotemporal relations from encoded features by exploiting deformable multihead self-attention (DeformMHSA). Subsequently, a masked cross-attention-based detection transformers (MCA-DETR) decoder is developed to accurately locate and identify changed objects based on masked cross-attention and self-attention mechanisms. It reconstructs the desired changed objects by decoding the pixel-wise representations into learnable mask proposals and making final predictions from these candidates. Experimental results on five benchmark datasets demonstrate the proposed approach outperforms other state-of-the-art models. Codes and pretrained models are available online (https://github.com/EricYu97/MaskCD).

Positron Profilometry . Can we overcome expensive facilities with new concepts?

I will discuss possible applications of RFQ-type 8Radio-Frequency Quadrupole) particle accelerators for efficient positron collection, bunching and post-acceleration im combination with radio-isotope based positron sources.

A transverse deflecting cavity is being developed for the electron linac ELBE to separate the bunches into two or more beamlines so that multiple user experiments can be carried out simultaneously. A normal conducting double quarter-wave cavity has been designed to deliver a transverse kick of 300 kV when driven by an 800 W solid-state amplifier at 273 MHz. The main challenges in fabrication were machining the complex cavity parts with high precision, pre-tuning the cavity frequency, and the final vacuum brazing within the tolerances, which are described in this paper. The reason for a low intrinsic quality factor measured during the low power test was investigated, and suitable steps were taken to improve the quality factor. The cavity field profiles obtained from the bead-pull measurement matched the simulation results. Further, the cavity was driven up to 1 kW using a modified pick-up antenna, and eventually, vacuum conditioning of the cavity was accomplished. The cavity fulfils the design requirements and is ready for beam tests.

Ute₂ is a spin-triplet superconductor candidate for which high quality samples with long mean free paths have recently become available, enabling quantum oscillation measurements to probe its Fermi surface and effective carrier masses. It has recently been reported that UTe₂ possesses a 3D Fermi surface component [Phys. Rev. Lett. 131, 036501 (2023)]. The distinction between 2D and 3D Fermi surface sections in triplet superconductors can have important implications regarding the topological properties of the superconductivity. Here we report the observation of oscillatory components in the magnetoconductance of UTe₂ at high magnetic fields.We find that these oscillations are well described by quantum interference between quasiparticles traversing semiclassical trajectories spanning magnetic breakdown networks. Our observations are consistent with a quasi-2D model of this material’s Fermi surface based on prior dHvA-effect measurements. Our results strongly indicate that UTe₂—which exhibits a multitude of complex physical phenomena—possesses a remarkably simple Fermi surface consisting exclusively of two quasi-2D cylindrical sections.

The linear electron accelerator, ELBE (Electron Linac for beams with high Brilliance
and low Emittance) at Helmholtz-Zentrum Dresden-Rossendorf, Dresden, Germany,
is a versatile machine that drives six distinct secondary particle and radiation sources
used in a wide range of experiments related to health, matter, transmutation, and
accelerator development. The accelerator can efficiently handle 1 mA beam current
at a 13 MHz bunch repetition rate in continuous-wave mode with a maximum beam
energy of 40 MeV. Currently, it is not possible to simultaneously operate more
than one ELBE secondary source. In this work, a suitable beam separator device
for ELBE was developed to overcome the limitation of single beamline operation.
The developed kicker can distribute the bunches from the existing single beam into
two or more beamlines, which will enable the simultaneous operation of multiple
downstream secondary sources, significantly enhancing the accelerator’s capabilities.
The state-of-the-art transverse deflecting structures suitable for beam separation were
reviewed. Subsequently, pulsed magnet, stripline kicker, and radio-frequency (RF)
cavity designs were adapted for the current requirements, and RF cavities were found
suitable. Furthermore, the cavity operating frequency was set to 273 MHz, reducing
both the differential kick voltage error and projected emittance growth and providing
a better field homogeneity. The cavity can be easily integrated into the ELBE’s
existing low-level RF control system. Six deflecting cavity designs were shortlisted,
and the cavity geometries were scaled and adapted to match the requirements. Then,
a cavity design was selected based on lower power loss, peak electric field and surface
power loss density, as well as better field homogeneity.
Subsequent to the cavity design, the cavity components were adapted from the
existing designs. Next, beam loading and multipacting in the cavity were analyzed,
and the effect of higher-order modes on the cavity was studied. A multiphysics
analysis was carried out to aid in the engineering design of the cavity. Thereafter,
the copper cavity parts were machined, and the cavity frequency was pre-tuned
before the final vacuum brazing was performed.
Finally, RF measurements were performed to validate the simulation. A thorough
investigation was carried out to determine the cause of the low intrinsic quality factor of the cavity. Consequently, the quality factor was improved by eliminating the RF
filter present at the vacuum port. A bead-pull measurement setup was built, and
the measured field profiles matched the simulation results. Further, the cavity was
driven up to 1 kW using the modified pick-up antenna, and eventually, the vacuum
conditioning of the cavity was accomplished. The cavity’s performance meets the
design requirements and is ready to be installed in the beamline for further testing.

In the present study, organic acids - oxalic acid, citric acid, tartaric acid and siderophore Desferrioxamine B were evaluated for their efficiencies to selectively recover Cu from its mold production waste. XRD analysis showed that copper mold production waste mainly consisted of Fe and Cu. The complete dissolution of this waste in aqua regia and subsequent analysis via ICP-MS revealed metal contents of 355.3 mg/g Fe and 293.9 mg/g Cu. Among all the organic acids, citric acid had the highest leaching efficiency (58.5 %) for Fe while leaching <1 % of Cu. Whereas, the leaching of Cu and Fe was poor in oxalic acid medium and Cu leaching was also negligible in tartaric acid medium. Only Fe showed 11.2 % leaching efficiency at 2 mol/L tartaric acid. The step-by-step leaching of production waste with citric acid lead to 100 % leaching of Fe while leaving 93.1 % of Cu with a yield of >99 % in the solid residue in the 4th step. Further, the siderophore Desferrioxamine B could effectively leach Fe (91.2 %) while 21.4 % leaching of Cu in 30 days. The presence of Fe impedes the leaching of Cu from the waste as demonstrated by leaching and DFT calculations due to higher stability of Fe-citrate and Fe-desferrioxamine B complex compared to Cu-organic complexes. This recycling technique described herein is simple, reliable and environmentally friendly for recovery of Cu from copper mold production waste.

Siderophores are a diverse group of small of iron-chelating compounds which are secreted by a plethora of bacteria and fungi. In nature, their purpose is the sequestration of iron. However, due to their chemical characteristrics they are able to bind various other metals as well, making them promising compounds for the utilization in future green recycling technologies.
This work aims to find siderophores, that selectively complex the critical elements indium and germanium. As there are more than 500 different siderophores reported to this day, exhaustive experimental evaluation is highly impractical, though. Therefore, density functional theory (DFT) was utilized to model the complexation reactions and as a result estimate the affinities of the respective siderophores towards the metals of interest. With this in silico approach, siderophores that exhibited favourable binding energies were found and evaluated experimentally in order to verify the results obtained by theoretical means.
Proofing the suitability of siderophores for the selective recovery of indium and germanium from low-concentrated sources would pose as a first step in the creation of future applications of the compounds in a variety of bio-based recycling technologies, as they could aid to secure the supply of a multitude of strategic metals.

In KONA 2022, the fundamentals of two- and multidimensional particle size distributions were introduced. The next question in the field of two- and multidimensional distributions addresses their application to describe a particle process, e.g., agglomeration or separation. A multidimensional separation can be seen as retrieving only particles with a specific set of properties from a multidimensionally distributed system, e.g., retrieving only small particles (below a certain threshold in size) with a compact spherical shape (above a certain threshold in sphericity). The multidimensional separation allows the generation of functional particle systems with specific properties, e.g., semiconducting, optical, or electronic properties, which are required for high-technology applications. Starting from so-called particle-discrete information, i.e., an information vector for each particle containing its compositional, geometrical, and physical properties, it is possible to describe a multidimensional separation in full detail based on various properties. Each particle can be evaluated according to different separation properties, e.g., size, shape, and material composition. With this database, it is possible to define and work with separation functions to describe the multidimensional separation and quantify the separation results. For example, in the two-dimensional case, the median cut size becomes a median cut line, where the probability for a particle to belong to the concentrate is 0.5. Some case studies and examples show different approaches and possibilities to achieve a multidimensional separation in one or several connected process steps.

Understanding laser-solid interactions is important for the development of laser-driven particle and photon sources, e.g., tumor therapy, astrophysics, and fusion. Currently, these interactions can only be modeled by simulations that need to be verified experimentally. Consequently, pump-probe experiments were conducted to examine the laser-plasma interaction that occurs when a high intensity laser hits a solid target. Since we aim for a femtosecond temporal and nanometer spatial resolution at European XFEL, we employ Small-Angle X-ray Scattering (SAXS) and Phase Contrast Imaging (PCI) that can each be approximated by an analytical propagator. In our reconstruction of the target, we employ gradient descent (GD) to iteratively minimize the error between experimental and synthetic patterns propagated from proposed target structures. By implementing the propagator in PyTorch, we leverage the automatic differentiation and GPU acceleration for the GD fit and at the same time obtain a differentiable physically-based loss function for unsupervised training of inversion or surrogate models. For a classical fit, we sample many different initial values for parameters, such as target asymmetry, to find the global minimum, leveraging batch-parallelism. A data-driven model to predict initial conditions close to actual minima can be trained in an unsupervised manner using our pipeline.

Accurate estimation of contaminant transport in cementitious material using numerical tools plays a key role in the risk assessments of nuclear waste disposal. At the pore scale, the increase of microbial activity, such as microbially induced calcite precipitation on cementitious material, causes changes in solid surface topography, pore network geometry, and pore water chemistry, which affect contaminant transport at the core scale and beyond. Consequently, a meaningful estimation of contaminant migration in the subsurface requires a pore-scale investigation of the influence of microbial activity on transport processes. In this study, a pore-scale reactive transport model is presented to simulate the physicochemical processes resulting from microbially induced calcite precipitation on a cement surface. Numerical investigations focus on modeling the reactive transport in a two-dimensional flow-through cell. The model results are validated by experimental data showing an increase in pH and a decrease in calcium concentration due to microbially induced calcite precipitation. Our results show heterogeneous calcite precipitation under transport-limited conditions and homogeneous calcite precipitation under reaction-limited conditions, resulting in non-uniform and uniform changes in the material surface topography. Moreover, power spectral density analysis of the surface data demonstrates that microbially induced calcite precipitation affects the surface topography via both general changes over the entire frequency and local modifications in the high-frequency region. The sensitivity studies provide a comprehensive understanding of the evolution of surface topography due to the microbially induced calcite precipitation at the pore scale, thus contributing to an improved predictability of contaminant transport at the core scale and beyond.

Competing magnetic interactions, frustration-driven quantum fluctuations, and spin correlations offer an ideal route for the experimental realization of emergent quantum phenomena with exotic quasiparticle excitations in three-dimensional frustrated magnets. In this context, trillium lattice, wherein magnetic ions decorate a three-dimensional chiral network of corner-shared equilateral triangular motifs, provides a viable ground. Herein, we present the crystal structure, dc and ac magnetic susceptibilities, specific heat, electron spin-resonance (ESR), muon spin-relaxation (μSR) results on the polycrystalline samples of K₂CrTi(PO₄)₃ wherein the Cr³⁺ ions form a two-coupled trillium lattice. The Curie-Weiss fit of the magnetic susceptibility data above 100 K yields a Curie-Weiss temperature θ_CW = −23 K, which indicates the presence of dominant antiferromagnetic interactions between S = 3/2 moments of Cr³⁺ ions. For temperatures below 40 K, the Curie-Weiss temperature is reduced to θCW = −3.5 K, indicative of the appearance of subdominant ferromagnetic interactions. The specific heat measurements reveal the occurrence of two consecutive phase transitions, at temperatures T_L = 4.3 K and T_H = 8 K, corresponding to two different magnetic phases. Additionally, it unveils the existence of short-range spin correlations above the ordering temperature T_H. The power-law behavior of ESR linewidth suggests the persistence of short-range spin correlations over a relatively wide critical region (T – T_H)/T_H > 0.25 in agreement with the specific heat results. The μSR results provide concrete evidence of two different phases corresponding to two transitions, coupled with the critical slowing down of spin fluctuations above T_L and persistent spin dynamics below T_L, consistent with the thermodynamic results. Moreover, the μSR results reveal the coexistence of static and dynamic local magnetic fields below T_L, signifying the presence of complex magnetic phases owing to the entwining of spin correlations and competing magnetic interactions in this three-dimensional frustrated magnet.

We have, in-situ, prepared and measured the temperature dependence of thermopower S(T) and resistance R(T) of Bi₂Te₃ topological insulator (TI) thin films in the amorphous and crystalline phase. Samples were prepared by sequential flash-evaporation at liquid ⁴He temperature. The S(T) in the amorphous phase is negative and much larger compared to other known amorphous materials, while in the crystalline phase it is also negative and behaves linearly with the temperature. The resistivity ρ(T) in the amorphous phase shows a semiconducting like behavior that changes to a linear metallic behavior after crystallization. S(T) an ρ(T) results in the crystalline phase are in good agreement with results obtained both in bulk and thin films reported in the literature. Linear behavior of the ρ(T) for T >15 K indicates the typical metallic contribution from the surface states as observed in other TI novel materials. The low temperature conductivity T <10 K exhibits logarithmic temperature dependent positive slope κ ≈ 0.21, indicating the dominance of electron-electron interaction (EEI) over the quantum interference effect, with a clear two dimensional nature of the contribution. Raman spectroscopy showed that the sample has crystallized in the trigonal R3m space group. Energy-dispersive x-ray spectroscopy reveales high homogeneity in the concentration and no magnetic impurities introduced during preparation or growth.

Structure and magnetic properties of layered GdMn₂(Ge_1-xSix)₂ (0 ≤ x ≤ 1) compounds were studied. All the compounds crystallize in the tetragonal ThCr₂Si₂-type structure. It was shown by magnetization measurements at low temperature on quasi-single crystals that, with increasing Si concentration, the easy magnetization direction reorients from the c-axis to the basal plane. The spin reorientation occurs via an angular phase. A model of three magnetic sublattices coupled by negative intersublattice exchange interactions was used to describe the field dependences of the magnetization. For GdMn₂Ge₂ and GdMn₂(Ge_0.9Si_0.1)₂ in the fields applied along the c-axis, seven different magnetic structures were predicted, including two angular structures considered for the first time. The model explains formation of angular magnetic structures in zero field in GdMn₂(Ge_1-xSi_x)₂ system by taking into account magnetic anisotropy of Mn sublattices with a positive anisotropy constant K₁ and negative K₂.

Magnetic refrigeration (MR) based on the magnetocaloric effect (MCE) has been recognized as an environmentally benign and energy-efficient cooling technology. Exploring suitable magnetocaloric materials is a crucial prerequisite for practical MR applications. We have herein provided a systematic investigation of the crystal structure, microstructure, electronic structure, magnetic phase transition, critical behavior, and MCE of the GdCoC compound featuring excellent cryogenic magnetocaloric performance by means of experimental determination and theoretical calculation. The GdCoC compound is crystallized in a simple layered tetragonal crystal structure with a P4₂/mmc space group and undergoes two successive ferromagnetic (FM) transitions along with a low-temperature weak antiferromagnetic (AFM) transition under low magnetic fields. Density functional theory calculations confirms the FM coupling of the Gd and Co intra-sublattice interactions, whereas AFM coupling for their inter-sublattice interaction. The magnetic transitions are merged in to one under high magnetic fields which has been confirmed to be second-order type and its critical behavior can be understood in the framework of tricritical mean-field model, whereas the low-temperature weak AFM transition is belonging to the first-order type. The excellent magnetocaloric performance of the GdCoC compound was identified by the parameters of magnetic entropy change, adiabatic temperature change, temperature-averaged entropy change, relative cooling power, and refrigerant capacity, which are superior to most of the well-known magnetocaloric materials with similar working temperatures, making it attractive for practical cryogenic MR applications.

Electrochemical system requires catalysts based on critical raw materials to improve their performances, especially high temperature water electrolyzers (HTELs) contain valuable fine particles such as rare earth elements, strontium, scandium, and nickel.
While many studies are working towards the scale-up of hydrogen production using water electrolysis and it is therefore important to investigate the recycling process of catalyst materials used in HTELs, there has been a lack of studies on mechanical recycling for fine particles.
In this study, we characterized the model particle mixture consisting of Nickel oxide (NiO), Lanthanum strontium manganite (LSM), Yttria stabilized zirconia (YSZ), and Zirconium oxide (ZrO2). Different ceramic materials used in a HTEL cell have a similar wettability. The various ceramic materials used in HTEL cells generally have similar wettability (hydrophilicity) and it can be selectively changed by exploiting their surface charge and adding surfactants. There is a specific pH range (pH 9 - 11) where the surface charge of NiO and LSM is opposite to that of ZrO2 and YSZ, and the modification of its hydrophobicity is successfully reached by using cationic and anionic surfactants. During our research, we observed that the LSMs exhibited ferromagnetism that was different from the rest of the material and they could be selectively separated later by magnetic separation. With different combinations of surfactant, dispersant, and pH, particles can be selectively separated by using particle liquid-liquid extraction.
This study would provide the design of the mechanical separation study for the end-of-life HTEL recycling stream.

Self-diffusion in amorphous germanium is studied at temperatures between 325 and 370 °C utilizing amorphous isotopically controlled germanium multilayer structures. The isotope multilayer is epitaxially grown on a single crystalline germanium-on-insulator structure by means of molecular beam epitaxy and subsequently amorphized by self-ion implantation. After heat treatment, the diffusional broadening of the isotope structure is measured with time-of-flight secondary ion mass spectrometry. The temperature dependence of self-diffusion is accurately described by the Arrhenius equation with the activation enthalpy Q = (2.21 ± 0.12) eV and pre-exponential factor D0 = (2.32 +20.79 −2.10 ) cm2 s−1. The activation enthalpy equals the activation enthalpy of solid phase epitaxial recrystallization (SPER). This agreement suggests that self-diffusion in amorphous germanium is similar to SPER, also mainly mediated by local bond rearrangements. Classical molecular dynamics simulations with a modified Stillinger–Weber-type interatomic potential yield results that are consistent with the experimental data and support the proposed atomic mechanism.

We design a novel class of Janus structures PbXY (X,Y = F, Cl, Br, I) and propose it for the solar mediated photocatalytic water splitting hydrogen production and for the bulk photovoltaic effect. The relaxed layers show a strong variation of the structural parameters which is due to the electronegativity of the halide atoms. The stability of the Janus structures is investigated using formation energy, phonon spectra, elastic constants and Ab-Initio Molecular Dynamics simulations. Using differential charge density calculations and Bader charge analysis, it is found that the atomic bonds may have covalent or ionic character, which depends on the halide atoms in top and bottom layers of the Janus structure. Electronic structure calculations are performed using the GGA functional and the more precise HSE functional. From the band structure, band gap and effective masses of electrons and holes are determined. The large difference between the mobility of both charge carriers as well as the built-in electrical dipole indicate beneficial conditions for charge separation and suppression of charge recombination. The calculated optical absorption spectra show that the Janus structures are suitablefor UV-visible light absorption. Based on VBM and CBM calculation using the HSE functional it is demonstrated that the novel PbXY Janus layers are suitable for water splitting reaction, i.e. for the use as a photocatalyst.

As one of the promising hydrogen production technologies, the development of water electrolysis systems including recycling of their functional components is actively investigated. However, the focus lies on energy and chemicals intensive metallurgical operations and less on mechanical separation processes in most studies. Here, an innovative surfactant-based separation process (using CTAB and SDS) is being investigated to contribute to developing a selective physical separation process for ultrafine particles used in high temperature water electrolyzers (composed of NiO, LSM, ZrO2, and YSZ). Their different surface charge in alkaline solutions influences the adsorption of surfactants on particle surfaces as well as the modification of the particulate wettability, which is a key separation feature. Through the observations of changes in surface charge and wetting behavior in the presence of surfactants, a feasibility of liquid-liquid particle separation (LLPS) is evaluated. The performance of LLPS with model particle mixtures shows a potential of selective separation with recovery of NiO in the organic phase, while the rest of the particles remain in the aqueous phase. The perovskite LSM is not considered in this system because it shows a high possibility of being recovered by magnetic separation. The proposed process can be further optimized by increasing the phase separation stages, and further research is needed on the NiO phase, which showed exceptional behaviors in presence of the surfactants.

Recent decades have seen enormous progress in the experimental investigation of fundamental processes that are relevant to geophysical and astrophysical fluid dynamics. Liquid metals have proven particularly suited for such studies, partly owing to their small Prandtl numbers that are comparable to those in planetary cores and stellar convection zones, partly owing to their high electrical conductivity that allows the study of various magnetohydrodynamic phenomena. After introducing the theoretical basics and the key dimensionless parameters, we discuss some of the most important liquid-metal experiments on Rayleigh–Bénard convection, Alfvén waves, magnetically triggered flow instabilities such as the magnetorotational and Tayler instability, and the dynamo effect. Finally, we summarize what has been learned so far from those recent experiments and what could be expected from future ones.

Aim: Gaussian filters are commonly used to improve signal to noise ratio (SNR) of PET images but reduce spatial resolution, thus increasing partial volume effects. Edge preserving filters can alleviate this problem. Especially, the bilateral filter (BF) has shown to have very good performance but requires manual tuning of its two parameters (σS, σI) for optimal results. This is time consuming and hampers clinical use. In this work we, therefore, investigated an automatic method for parameter optimization.

Methods: PET-data from 69 patients were included: 18F-FDG(N=33), 18F-LDOPA(N=25), 68Ga-DOTATATE(N=11). All scans were performed with respiratory gating (8 gates), resulting in 552 low SNR PET volumes. Four 3D ROIs were placed in each volume: one within the liver (to assess noise) and three in areas with elevated focal uptake and various SNR levels. Optimal parameters were determined by a grid search in the (σS,σI) plane aiming at parameters that simultaneously leave SUV_max of the focal uptake mostly unaltered while yielding a noise level comparable to that seen in the sum over all gates. BF with the optimized parameters was then applied and images were visually inspected and analyzed regarding ΔSUV_max and ΔNoise differences (BF vs. unfiltered) in the respective ROIs.

Results: In 19/69 datasets our method failed (over-smoothed background or artifacts). For these images the parameters had to be manually tuned. Overall, optimal parameter values varied over a substantial range (mean±sd: σI=(1.4±1.5) SUV and σS=(5.5±1.7) mm) with σI exhibiting a pronounced tracer dependance. ΔSUV_max of the focal uptake ROIs across all datasets was small (-0.5±0.8) while substantial noise reduction was achieved by (-12.3±3.5) percentage points although detailed behaviour differed between tracers.

Conclusions: Our results demonstrate inter-individual and tracer-specific variability of optimal BF parameters and thus underline the need for careful parameter optimization. In 72% of all investigated cases our automated method was able to perform this optimization without any user intervention. More work is needed to further improve the success rate. However, already in its current form our method does notably reduce workload imposed on the user when considering BF for routine use.

Aim: PET images can exhibit high noise levels which adversely affects qualitative and quantitative image evaluation. Especially challenging are respiratory gated studies and dynamic studies. In such cases, Gaussian filtering is routinely used to improve the signal to noise ratio. However, this degrades the spatial resolution and leads to reduced contrast recovery (CR) in small lesions. Edge preserving bilateral filtering is able to overcome this shortcoming but requires careful tuning of its 2 parameters on a per case basis in order to produce optimal results. In this work we evaluate the potential of using a deep neural network for automatic edge preserving image filtering utilizing a training set of manually filtered PET images.

Methods: We collected unfiltered gated PET data from clinical PET/MR (Philips PET/MR) and PET/CT (Siemens PET/CT) systems and interactively optimized bilateral filtering to achieve the best combination of noise reduction and preservation of spatial resolution. The set of pairs of corresponding unfiltered and filtered images was randomly split into training, validation, and testing sets. The convolutional neural network (CNN) was trained to generate the filtered images from the unfiltered ones. The resulting network model was then evaluated using the ROVER software package regarding its denoising and CR performance and also for presence of artifacts.

Results: With the preliminary data available so far, evaluation of the images filtered with CNN yielded results closely resembling these obtained with manually tuned bilateral filtering in terms of noise level and CR. No apparent image artifacts were found.

Conclusions: Our initial results indicate that the CNN-based post-filtering produces images comparable to interactively optimized filtering. However, more thorough analyses with more image data for testing and training is required to draw definite conclusions about reliably of the proposed solution and will be performed in the coming months. Furthermore, integration of the derived network into a new respiratory motion compensation framework is planned.

Aim: Spatial resolution is one of the key parameters for assessment of PET scanner performance. However, spatial resolution is usually determined with point or line sources, not allowing to study the finite object size and contrast effects known to affect iterative image reconstruction results. We present an approach to determine the spatial resolution at finite background for extended objects. The method was applied to preclinical PET/CT systems (Bruker PET/CT Si78, Mediso PET/CT).

Methods: Spatial resolution is assessed as the full width at half maximum (FWHM) of the point spread function (PSF, approximated by a 3D Gaussian). FWHM is determined from a fit of the convolution of the considered object (homogeneous sphere or rod) with the PSF to the reconstructed image data. In this process, the full 3D vicinity of each sphere/rod is evaluated by transforming the data to spherical/cylindrical coordinates relative to the respective object center/axis. F-18 measurements were performed with a cylindrical phantom (diameter 3.5cm) with a cylindrical insert (diameter 1cm). Measurements were performed without background and at contrast ratio 3:1, respectively.

Results: Without background, we obtained FWHM=1.3mm for the Mediso system, but severe Gibbs artefacts are present, indicating a too aggressive resolution recovery approach. The Bruker system achieves FWHM=2.1mm while avoiding any Gibbs artefacts. At 3:1 contrast, resolution of both systems decreases (to FWHM=2.6mm and 3.2mm, respectively) while Gibbs artefacts are not visible for the Mediso system, too.

Conclusions: Our preliminary results show that both investigated systems have a strongly contrast dependent spatial resolution. Optimizations of reconstruction parameters are currently underway with the aim of reducing the adverse effects of Gibbs artefacts on quantification and improving reconstructed image resolution at finite background while avoiding any negative effects on potential quantification.

Background: Residual image noise is substantial in positron emission tomography (PET) and one of the factors limiting lesion detection, quantification, and overall image quality. Thus, improving noise reduction remains of considerable interest. This is especially true for respiratory-gated PET investigations. The only broadly used approach for noise reduction in PET imaging has been the application of low-pass filters, usually Gaussians, which however leads to loss of spatial resolution and increased partial volume effects affecting detectability of small lesions and quantitative data evaluation. The bilateral filter (BF) – a locally adaptive image filter – allows to reduce image noise while preserving well defined object edges but manual optimization of the filter parameters for a given PET scan can be tedious and time-consuming, hampering its clinical use. In this work we have investigated to what extent a suitable deep learning based approach can resolve this issue by tasking a suitable network with reproducing the results of manually adjusted case-specific bilateral filtering.

Methods: Altogether, 69 respiratory-gated clinical PET/CT scans with three different tracers ([¹⁸F]FDG, [¹⁸F]L-DOPA, [⁶⁸Ga]DOTATATE) were used for the present investigation. Prior to data processing, the gated data sets were split, resulting in a total of 552 single-gate image volumes. For each of these image volumes, four 3D ROIs were delineated: one ROI for image noise assessment and three ROIs for focal uptake (e.g. tumor lesions) measurements at different target/background contrast levels. An automated procedure was used to perform a brute force search of the two-dimensional BF parameter space for each data set to identify the “optimal” filter parameters to generate user-approved ground truth input data consisting of pairs of original and optimally BF filtered images. For reproducing the optimal BF filtering, we employed a modified 3D U-Net CNN incorporating residual learning principle. The network training and evaluation was performed using a 5-fold cross-validation scheme. The influence of filtering on lesion SUV quantification and image noise level was assessed by calculating absolute and fractional differences between the CNN, manual BF, or original (STD) data sets in the previously defined ROIs.

Results: The automated procedure used for filter parameter determination chose adequate filter parameters for the majority of the data sets with only 19 patient data sets requiring manual tuning. Evaluation of the focal uptake ROIs revealed that CNN as well as BF based filtering essentially maintain the focal SUVmax values of the unfiltered images with a low mean±SD difference of δSUV_max^CNN,STD =(-3.9±5.2)% and δSUV_max^BF,STD =(-4.4±5.3)%. Regarding relative performance of CNN vs. BF, both methods lead to very similar SUV_max values in the vast majority of cases with an overall average difference of δSUV_max^CNN,BF =(0.5±4.8)%. Evaluation of the noise properties showed that CNN filtering mostly satisfactorily reproduces the noise level and characteristics of BF with δNoise^CNN,BF=(5.6±10.5)%. No significant tracer dependent differences between CNN and BF were observed.

Conclusions: Our results show that a neural network based denoising can reproduce the results of a case by case optimized BF in a fully automated way. Apart from rare cases it led to images of practically identical quality regarding noise level, edge preservation, and signal recovery. We believe such a network might proof especially useful in the context of improved motion correction of respiratory-gated PET studies but could also help to establish BF-equivalent edge-preserving CNN filtering in clinical PET since it obviates time consuming manual BF parameter tuning.

We propose an efficacious approach to derive the generalized parton distributions for the pion and proton, based upon prior knowledge of their respective parton distribution functions (PDFs). Our method leverages on integral representations of the electromagnetic form factors derived from the light-front holographic QCD (LFHQCD) formalism, coupled with PDFs computed from continuum Schwinger functional methods at the hadronic scale. Using these techniques, we calculate gravitational form factors and associated mass distributions for each hadron. Remarkably, our calculations yield results that closely match recent lattice QCD simulations conducted near the physical pion mass. This work not only deepens our understanding of hadronic structure but also highlights the efficacy of the LFHQCD approach in modeling fundamental properties of hadrons.

A recent study by Wang {\it et al.}(arXiv:2308.14871) proposed a novel connection between the nature of the parton distribution function (PDF) and the characteristics of its moments. In this study, we apply these findings to analyze the evolution of the pion valence quark PDF, garnering valuable qualitative insights. Firstly, we validate the non-negativity and continuity of the PDF across a wide range of scales, indicating the logical consistency of our chosen evolution scheme. Subsequently, we examine the unimodality of both the PDF and its transformed counterpart, the xPDF, i.e., the parton distribution function multiplied by the momentum fraction. We observe a smooth evolution of the peak position of the xPDF towards the small-x region with increasing scale, while intriguingly, the PDF undergoes a phase of bimodal competition as the energy scale evolves.

The design of multiphase reaction and separation processes, such as for example catalytic hydrogenations, distillation and absorption processes, extraction processes, wastewater treatment, and many more, require a profound understanding of the multiphase fluid dynamics inside reactors and contactors. As Computational Multiphase Fluid Dynamics is still not fully mature to simulate complex two-phase and three-phase flow with overlaying heat and mass transfer as well as chemical reaction with sufficient accuracy there is a constant need for advanced experimental and measurement techniques; may it be for the provision of operational, design or thermodynamic parameters or for the validation of codes. In this talk we report on three different novel measurement techniques for this purpose. The presentation shall exemplarily demonstrate how advanced measurement and imaging techniques can be used to study opaque two-phase and three-phase flows in lab environment and potentially also in the field. We report on a) the use of ultrafast X-ray tomography and wire-mesh sensors for the study of reactive bubbly flow in a bubble column, b) the application of a large flow profiler in studying two-phase flow on a distillation column tray, and c) a method to obtain gas dispersion parameters in gas-liquid contactors using modulated gas flow.

Electronic biosensors have found numerous applications in point-of-care (POC) diagnostics thanks to their affordability and facile integration into portable devices, enabling rapid digital display of measured data. However, this class of biosensors still did not reach the stability and reliability required for demanding healthcare applications, such as the diagnostics of complex diseases or therapy monitoring, where multiple biomarkers need to be measured simultaneously with high accuracy and sensitivity. In these application scenarios, multiplexing represents a promising practical solution enabling simultaneous and reproducible measurements at many sensing points, as well as robust statistics. Extended gate (EG) field-effect transistor (FET) biosensor systems are excellent candidates for multiplexed sensing of various physiologically relevant (bio)chemical analytes, from ions to biomolecules. The FET transducer endows the system with exceptional sensitivity and straightforward interfacing with readout electronics, while the physical separation of the gate electrode from the transducer facilitates the integration of multiple individually tailored sensing points into the compact, disposable, and cost-effective sensing interface with versatile architectures [1]. We have demonstrated multiplexed, portable, and standalone EG-FET biosensing platforms combining the optimized design of conventional electronics based on off-the-shelf components and different innovative assay strategies, thereby achieving remarkable detection limits for biomolecules, improved by several orders of magnitude compared to clinical gold standard ELISA assays. Using gold nanoparticle analyte labels as nanoantennae, we realized a highly sensitive POC immunosensor [2]. Moving beyond the traditional POC diagnostics applications, we implemented an indirect assay methodology enabling the detection of target molecules relevant for monitoring cancer immunotherapy [3]. Our EG-FET platforms offer a great opportunity for advanced digitalized healthcare screening and monitoring by quickly providing more comprehensive information to clinicians. They can be easily upgraded to support data connectivity and effective incorporation of artificial intelligence. We envision EG-FET biosensing platforms as important components of future digital health ecosystems.

References
[1] Ž. Janićijević, T.-A. Nguyen-Le, and L. Baraban, ‘Extended-gate field-effect transistor chemo- and biosensors: State of the art and perspectives’, Next Nanotechnology, vol. 3–4, p. 100025, Sep. 2023, doi: 10.1016/j.nxnano.2023.100025.
[2] Ž. Janićijević, T.-A. Nguyen-Le et al., ‘Multiplexed extended gate field-effect transistor biosensor with gold nanoantennae as signal amplifiers’, Biosensors and Bioelectronics, vol. 241, p. 115701, Dec. 2023, doi: 10.1016/j.bios.2023.115701.
[3] T.-A. Nguyen-Le et al. ‘Towards precision immunotherapy: FET biosensors for immunotherapeutic drug monitoring in UniCAR T-cell therapy’, Manuscript in preparation

Long-wavelength free-electrons lasers are unique sources of intense, narrowband THz radiation. I will discuss here time-resolved experiments, where intense THz radiation strongly drives and excites charge carriers in two different types of nanomaterials.
In the first experiment a single GaAs/InGaAs core-shell nanowire with a strained GaAs core and a highly doped InGaAs shell is excited with 12-THz radiation near the tip of a Neaspec scattering scanning near-field microscope (s-SNOM). Subsequently the spectrally resolved mid-infrared response (20-60 THz) is probed using a difference-frequency mixing source. Resulting from this intraband pumping we observe a red shift of the nanowire plasma resonance both in amplitude and phase spectra, which is ascribed to a heating of the electron distribution in the nonparabolic band and to electron transfer into the side valleys, resulting in an increase of the average effective mass.
In the second experiment we excite a single 2D layer of MoSe2 with THz radiation of photon energy in the vicinity of the trion binding energy (here 26 meV). A trion is an exciton that binds a second electron; it is known, even from the hydrogen atom, that its binding energy is roughly an order of magnitude smaller than the exciton binding energy. Subsequently the time-resolved photoluminescence is monitored to observe exciton and trion populations for different excitation photon energies. We clearly identify the resonant ionization of the trion and its conversion to an exciton.

Acoustic focusing of particle flow in microfluidics has been shown to be an efficient tool for particle separation for various chemical and biomedical applications. The mechanism behind the method is the selective effect of the acoustic radiation force on distinct particles. In this way, they can be selectively focused and separated. The technique can also be applied under stationary conditions, i.e., in the absence of fluid flows. In this study, the manipulation of self-propelled particles, such as Janus particles, in an acoustofluidic setup was investigated. In experiments with self-propelled Janus particles and passive beads, we explored the interplay between self-propulsion and the acoustic radiation force. Our results demonstrated unusual and potentially useful effects such as selective trapping, escape, and assisted escape in binary mixtures of active and passive particles. We also analyzed various aspects related to the behavior of Janus particles in acoustic traps in the presence and absence of flows.

The talk gives a short overview about the combination of flash lamp annealing and roll-to-roll applications including the application fields of inkjet printing with nanoparticle inks, transparent conduction oxides, and energy materials.

METABOLATOR is a web application for automated analysis of microcalorimetric metabolic data using Monod's equation. The software was developed in collaboration between the Institute of Resource Ecology and the Department of Information Services and Computing at Helmholtz-Zentrum Dresden - Rossendorf (HZDR), and is now offered as a web service for the community. In addition to publishing the software under an open source license, we made the service, which is hosted on HZDR infrastructure, citable by registering its metadata with DataCite and minting a dedicated Digital Object Identifier (DOI). In this talk, we will present the results of our collaboration from the point of view of a Research Software Engineer (RSE). We will introduce the METABOLATOR software, and discuss its development from initial trials into an installable package and web service. Moreover, we will debate the importance of persistent identifiers (PIDs) for reproducible, citable, and overall FAIR data analysis workflows.

We reveal and analyze an efficient magnetic dynamo action due to precession-driven hydrodynamic turbulence in the local model of a precessional flow, focusing on the kinematic stage of this dynamo. The growth rate of the magnetic field monotonically increases with the Poincaré number Po, characterizing precession strength, and the magnetic Prandtl number Pm, equal to the ratio of viscosity to resistivity, for the considered ranges of these parameters. The critical Po for the dynamo onset decreases with increasing Pm. To understand the scale-by-scale evolution (growth) of the precession dynamo and its driving processes, we perform spectral analysis by calculating the spectra of magnetic energy and of different terms in the induction equation in Fourier space. To this end, we decompose the velocity field of precession-driven turbulence into two-dimensional (2D) vortical and three-dimensional (3D) inertial wave modes. It is shown that the dynamo operates across a broad range of scales and exhibits a remarkable transition from a primarily vortex-driven regime at lower Po to a more complex regime at higher Po where it is driven jointly by vortices, inertial waves, and the shear of the background precessional flow. Vortices and shear drive the dynamo mostly at large scales comparable to the flow system size, and at intermediate scales, while at smaller scales it is mainly driven by inertial waves. This study can be important not only for understanding the magnetic dynamo action in precession-driven flows, but also in a general context of flows where vortices emerge and govern the flow dynamics and evolution.

Industrial multiphase flows are typically characterized by coexisting morphologies. Modern simulation methods are well established for dispersed (e.g., Euler-Euler) or resolved (e.g., Volume-of-Fluid) interfacial structures. A simulation method that requires less knowledge about the flow in advance would be desirable and should allow describing both types of interfacial structures – resolved and dispersed – in a single computational domain. Such methods that combine interface-resolving and non-resolving approaches are called hybrid models. A morphology adaptive multifield two-fluid model, named MultiMorph Model, is proposed, which is able to handle dispersed and resolved interfacial structures coexisting in the computational domain with the same set of equations. For large interfacial structures an interfacial drag formulation is used to describe them in a volume-of-fluid-like manner. For the dispersed structures, the baseline model developed at Helmholtz-Zentrum Dresden - Rossendorf e.V. (HZDR) is applied. The functionality of the framework is demonstrated by several test cases, including a single rising gas bubble in a stagnant water column. Recent developments focus on the transition region, where bubbles are over- or under-resolved for Euler-Euler or for Volume-of-Fluid, respectively. The contribution will focus on an overview about the fundamentals of the MultiMorph Model and recent simulation results for a plunging jet, a stratified counter-current air-water flow and a column tray of a distillation column.

The variable energy availability in the future energy system requires a certain flexibility of energy consumption by energy-intensive industrial processes. The raw materials industry traditionally has high energy demands and low flexibility. This contribution is concerned with the flexibility potential of the copper recycling industry. The current study utilized FactSage and HSC Chemistry software to simulate secondary copper production and OpenLCA, to quantify the environmental impacts of using various flexibility options, such as change in throughput, temporary shutdown of unit operations, and temporarily switching to hydrogen as an alternative energy source.

The folded structure and stability of proteins emanates from their interaction with the water solvent. Water at the protein surface is strongly impacted, resulting in a region with a perturbed hydrogen bonding network. This region, the solvation shell, has distinct properties from that of bulk water, including retarded dynamics and fewer hydrogen bonds. Changes in the structure and dynamics of solvation water can be both perturbed and reported on by Terahertz radiation. Yet, some fundamental properties of solvation water, such as energy transfer within the hydrogen bonding network, remain largely unexplored.
Here, we utilize the TELBE free electron laser source to investigate the nonlinear transmission of lysozyme protein solutions. Z-scan experiments were performed at 0.5 THz, revealing a large nonlinear transmission of water. The nonlinear transmission of lysozyme solutions had a concentration dependent effect, showing that the amount of available water has a role. For the largest protein concentration measured, an inversion in the sign of the nonlinear transmission was observed. These results indicate that the nonlinear properties of protein solutions depend on the fraction of bulk and solvation water, and suggest that the mechanism of energy transfer changes at a threshold value. This work has implications for the study of nonlinear properties in biological systems.

Biomolecular condensates are membrane-less organelles formed via liquid-liquid phase separation of intrinsically disordered proteins. Here, THz spectroscopy is utilized to reveal the structure and dynamics of hydration water in these liquid-like protein environments.

Investigations on how the froth height is influencing the flotation of ultrafine particles using the newly developed separation apparatus MultiDimFlot

We prepared two-dimensional concentric lateral heterostructures of the monolayer transition metal dichalcogenides (TMDCs) MoS₂ and TaS₂ by reactive molecular beam epitaxy (MBE) on chemically inert and weakly interacting Au(111). The heterostructures are in a size regime where quantum confinement can be expected. Despite large lattice mismatch a seamless interconnection of the two materials has been achieved, confirming that the semiconducting core is fully enclosed by a metallic border around its circumference. The resulting strain is analyzed on the atomic scale using scanning tunneling microscopy (STM), corroborated by calculations based on empirical potentials and compared to results from finite elements simulations.

Considering the increasing demand for Li-ion batteries, there is a need for sophisticated recycling strategies with both high recovery rates and low costs. Applying optical sensors for automating component detection is a very promising approach because of the non-contact, real-time process monitoring and the potential for complete digitization of mechanical sorting processes. In this work, mm-scale particles from shredded end-of-life Li-ion batteries are investigated by five different reflectance sensors, and a range from the visible to long-wave infrared is covered to determine the ideal detection window for major component identification as relevant input signals to sorting technologies. Based on the characterization, a spectral library including Al, Cu, separator foil, inlay foil, and plastic splinters was created, and the visible to near-infrared range (400–1000 nm) was identified as the most suitable spectral range to reliably discriminate between Al, Cu, and other battery components in the recycling material stream of interest. The evaluation of the different sensor types outlines that only imaging sensors meet the requirements of recycling stream monitoring and can deliver sufficient signal quality for subsequent mechanical sorting controls. Requirements for the setup parameters were discussed leading to the setup recommendation of a fast snapshot camera with a sufficiently high spectral resolution and signal-to-noise ratio.

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 [1,2] foreshadows a new direction in 2D systems research. To elucidate their structure and properties, electron microscopy and first-principles calculations are indispensable tools.

Contributing to the predictive design of these novel nanoscale compounds, here, we present several dozens of candidates derived from applying data-driven research methodologies
in conjunction with autonomous first-principles calculations [3,4]. We find that the oxidation state of the surface cations of the 2D sheets as well as accounting for strong surface relaxations upon exfoliation are crucial factors determining their stabilization.
The candidates exhibit a wide range of appealing electronic, optical and in particular magnetic properties owing to the (magnetic) cations at the surface of the sheets. Despite of several ferromagnetic candidates, even for the antiferromagnetic representatives, the surface spin polarizations are diverse ranging from moderate to large values modulated in addition by ferromagnetic and antiferromagnetic in-plane coupling [3]. These features can be accessed by experimental techniques such as (spin-polarized) scanning tunnelling microscopy. At the same time, chemical tuning by surface passivation provides a valuable handle to further control the magnetic properties of these novel 2D compounds [5] thus rendering them an attractive platform for fundamental and applied nanoscience.

[1] A. Puthirath Balan et al., Nat. Nanotechnol. 13, 602 (2018).
[2] A. Puthirath Balan et al., Mater. Today 58, 164 (2022).
[3] R. Friedrich et al., Nano Lett. 22, 989 (2022).
[4] T. Barnowsky et al., Adv. Electron. Mater. 9, 2201112 (2023).
[5] T. Barnowsky et al., Nano Lett. in press (2024).

This repository contains data to test, develop and debug MALA and MALA based runscripts. If you plan to do machine-learning tests ("Does this network implementation work? Is this new data loading strategy working?"), this is the right data to test with. It is NOT production level data!

We report on defects dynamics during heat treatment in plastically deformed metallic materials using positron annihilation lifetime spectroscopy carried out on the intense pulsed positron beam. The conducted experiment allowed us to observe the changes in the concentration and sizes of vacancy-like defects observed during in-situ annealing. We monitored heat treatments up to 300 oC in hydrostatic extruded Ti and cavitation peened V-4Cr-4Ti alloy. We were able to track the recovery processes in Ti and redistribution of large voids at the surface of cavitation peened V-4Cr-4Ti alloy. The relaxation time during recovery was about 20 minutes. Performed experiments show that in cold-worked metallic materials significant changes in vacancy clusters concentrations occur at mildly elevated temperatures. The presented results give opportunity to the application of in-situ observation of defects dynamic to similar problems related to thermomechanical processing of metallic materials.

Matter at extreme densities and temperatures displays a complex quantum behavior that is characterized by Coulomb interactions, thermal excitations, and partial ionization. Such warm dense matter (WDM) is ubiquitous throughout the universe and occurs in a host of astrophysical objects such as giant planet interiors and white dwarf atmospheres. A particularly intriguing application is given by inertial confinement fusion, where both the fuel capsule and the ablator have to traverse the WDM regime in a controlled way to reach ignition.

In practice, rigorously understanding WDM is highly challenging both from experimental measurements and numerical simulations [1]. On the one hand, interpreting and diagnosing experiments with WDM requires a suitable theoretical description. One the other hand, there is no single method that is capable of accurately describing the full range of relevant densities and temperatures, and the interpretation of experiments is, therefore, usually based on a number of de-facto uncontrolled approximations. The result is the vicious cycle of WDM diagnostics: making sense of experimental observations requires theoretical modeling, whereas theoretical models must be benchmarked against experiments to verify their inherent assumptions.

In this work, we outline a strategy to break this vicious cycle by combining the X-ray Thomson scattering (XRTS) technique [2] with new ab initio path integral Monte Carlo (PIMC) capabilities [3,4,5]. As a first step, we have proposed to interpret XRTS experiments in the imaginary-time (Laplace) domain, which allows for the model-free diagnostics of the temperature [6] and normalization [7]. Moreover, by switching to the imaginary-time, we can directly compare our quasi-exact PIMC calculations with the experimental measurement [5]. This opens up novel ways to diagnose the experimental conditions, as we have recently demonstrated for the case of strongly compressed beryllium at the National Ignition Facility.

Our results open up new possibilities for improved XRTS set-ups that are specifically designed to be sensitive to particular parameters of interest [8]. Moreover, the presented PIMC capabilities are important in their own right and will allow for a gamut of applications, including equation-of-state calculations and the estimation of structural properties and linear response functions.

[1] T. Dornheim et al., Phys. Plasmas 30, 032705 (2023) [2] S. Glenzer and R. Redmer, Rev. Mod. Phys. 81, 1625 (2009) [3] T. Dornheim et al., J. Phys. Chem. Lett. 15, 1305-1313 (2024) [4] T. Dornheim et al., arXiv:2403.01979 [5] T. Dornheim et al., arXiv:2402.19113 [6] T. Dornheim et al., Nature Commun. 13, 7911 (2022) [7] T. Dornheim et al., arXiv:2305.15305 [8] Th. Gawne et al., arXiv:2403.02776

This study explores defect engineering in 2D materials using ion beam irradiation to modify the electrical and optical properties with potential in advancing quantum electronics and photonics. Helium and neon ions ranging from 5 to 7.5 keV are employed to manipulate charge transport in monolayer molybdenum disulfide (MoS2). In situ electrical characterization occurs without vacuum breakage post-irradiation. Raman and photoluminescence spectroscopy quantify ion irradiation’s impact on MoS2. Small doses of helium ion irradiation enhance monolayer MoS2 conductivity in field-effect transistor geometry by inducing doping and substrate charging. Findings reveal a strong correlation between the electrical properties of MoS2 and the primary ion used, as well as the substrate on which the irradiation occurred. Using hexagonal boron nitride (h-BN) as a buffer layer between MoS2 flake and SiO2 substrate yields distinct alterations in electrical behavior subsequent to ion irradiation compared to the MoS2 layer directly interfacing with SiO2. Molecular dynamics simulations and density functional theory provide insight into experimental results, emphasizing substrate influence on measured electrical properties post-ion irradiation.

This work details a Compton-scattering-based methodology, referred to as Backscatter Gating (BSG), for characterizing the time, energy, and position resolutions of long form factor organic scintillators using a single, fairly minimal measurement setup. Such a method can ease the experimental burden in scenarios where many such scintillator elements may need to be individually characterized before assembly into a larger detector system. A thorough theoretical exploration of the systematic parameters is provided, and the BSG method is then demonstrated by a series of experimental measurements. This “complete” characterization via the BSG method is novel, having previously been used primarily for energy resolution characterization. The method also allows for determination of the assembled scintillator’s technical attenuation length and provides a means of verifying the presence or absence of flaws within the scintillator or its optical coupling.

Transition metal oxynitrides are a promising class of functional materials for photoelectrochemical (PEC) applications. Although these compounds are most commonly synthesized via ammonolysis of oxide precursors, such synthetic routes often lead to poorly controlled oxygen-to-nitrogen anion ratios, and the harsh nitridation conditions are incompatible with many substrates, including transparent conductive oxides. Here, we report direct reactive sputter deposition of a family of zirconium oxynitride thin films and the comprehensive characterization of their tunable structural, optical, and functional PEC properties. Systematic increases of the oxygen content in the reactive sputter gas mixture enable access to different crystalline structures within the zirconium oxynitride family. Increasing oxygen contents lead to a transition from metallic to semiconducting to insulating phases. In particular, crystalline Zr2ON2-like films have band gaps in the UV−visible range and are n-type semiconductors. These properties, together with a valence band maximum position located favorably relative to the water oxidation potential, make them viable photoanode candidates. Using chopped linear sweep voltammetry, we indeed confirm that our Zr2ON2 films are PEC-active for the oxygen evolution reaction in alkaline electrolytes. We further show that high-vacuum annealing boosts their PEC performance characteristics. Although the observed photocurrents are low compared to state-of-the-art photoanodes, these dense and planar thin films can offer a valuable platform for studying oxynitride photoelectrodes, as well as for future nanostructuring, band gap engineering, and defect engineering efforts.

Froth flotation is an efficient separation process for particles with sizes between 10 μm and 200 μm, which is based on differences in the particle wettabilities, or more precisely dewettingability. Therefore, a fundamental understanding of the interfacial properties is required. Within the project MultiDimFlot, which is part of the priority programme SPP2045, funded by the German research foundation (DFG), the selective separation of ultrafine particles (< 10 μm) according to multiple particle properties (e.g. wettability, shape, size) by flotation is investigated. For this purpose, two ultrafine glass particle fractions with different shapes are used, i.e. glass spheres and fragments, and their wettability is modified via an esterification reaction using alcohols, where the wettability of the esterified particles is controlled by the length of the alkyl chain.
In order to investigate the influence of wetting heterogeneities on the separation via flotation, glass slides with the same chemical composition as the glass particles and that were esterified in the same way, were analysed via atomic force microscopy (AFM). By applying colloidal probe AFM in dry and liquid mode, information on the hydrophobic interactions on the surface of the glass slides with different levels of wettability are obtained. Furthermore, the esterified glass slides are analysed by measuring static and dynamic contact angles against water using the sessile drop method. This information is set into context with the surface energy results of the glass particles, obtained via inverse gas chromatography as well as results obtained by liquid-liquid extraction of particles, which is used to study the behaviour of the particles at the interface.
The correlation of the various methods shed light on the (de)wetting(ability) heterogeneities, how these are changed through esterification and how these results can be transferred to flotation.

Stable composite objects (e.g. hadrons, nuclei, atoms, molecules, and superconducting pairs) formed by attractive forces are ubiquitous in nature. In contrast, composite objects stabilized via repulsive forces were long thought to be theoretical constructions due to their fragility in naturally occurring systems. Surprisingly, the formation of bound atom pairs by strong repulsive interactions has been demonstrated experimentally in optical lattices1. Despite this success, repulsively bound particle pairs were believed to have no analogue in condensed matter due to strong decay channels. Here, we present spectroscopic signatures of repulsively bound three-magnon states and bound magnon pairs, in the Ising-like chain antiferromagnet BaCo2V2O8. In large transverse fields, below the quantum critical point, we identify repulsively bound magnon states by comparing terahertz spectroscopy measurements to theoretical results for the Heisenberg-Ising chain antiferromagnet, a paradigmatic quantum many-body model2–5. Our experimental results show that these high-energy repulsively bound magnon states are well separated from continua, exhibit significant dynamical responses and, despite dissipation, are sufficiently long-lived to be identified. As the transport properties in spin chains can be altered by magnon bound states, we envision such states could serve as resources for magnonics based quantum information processing technologies6–8.

To improve the quality of photocathodes is one of the critical issues in enhancing the stability and reliability of photo-injector systems. Magnesium has a low work function (3.6 eV) and shows high quantum efficiency (QE) after proper surface cleaning. This paper presents the investigation of alternative surface cleaning procedures, such as ps laser cleaning, thermal cleaning and ion beam cleaning. The QE is able to be improved two magnitudes after the treatment.

Superconducting radio frequency (SRF) photoinjectors offer advantages for continuous wave (CW) operation and high brightness, high current beam generation. One of the critical components for successful operation of SRF photoinjectors is the photocathode system. HZDR is building a sophisticated cathode exchange system to ensure accurate, particle-free and warm cathode exchange. A novel alignment process aligns the cathode to the gun axis without touching the cathode plug itself. Less than 10 particles as small as 0.3 micrometer are detected
during the cathode load-lock tests.

Ongoing miniaturization down to a few nanometers will lead to further significant
reductions in the power consumption of microchips and sensors. The number of
innovative applications immediately arise from the potential of integrating a
microbattery as a power source for flexible electronics, wearables, the Internet of
Things, medical implants and sensor chips.
In this work, a thin film lithium-Ion battery (TF-LIB) is demonstrated. The TF-LIB consists
of a high potential copper silicide anode (CuSi-anode) that can be integrated on a Siwafer
with standard semiconductor technology and a hybrid polymer electrolyte with a
high lithium-ion transference number. Two cathode materials were tested: LiFePO4 and
NCA.
The CuSi-anode is fabricated by Si sputtering followed by flash lamp annealing (FLA).
This anode material replaces metallic lithium for reaching high energy densities and
provides the thermal stability required in microelectronics (> 230 °C for soldering).
The hybrid polymer electrolyte is mechanically stable against the volume change of the
silicon during the lithiation/ delithiathion processes. The electrolyte is unreactive and
thermally stable at high temperatures during operation.

Amyotrophic lateral sclerosis (ALS) leads to death within 2–5 yr. Currently, available drugs only slightly prolong survival. We present novel insights into the pathophysiology of Superoxide Dismutase 1 (SOD1)- and in particular Fused In Sarcoma (FUS)-ALS by revealing a supposedly central role of glycolic acid (GA) and D-lactic acid (DL)— both putative products of the Parkinson’s disease associated glyoxylase DJ-1. Combined, not single, treatment with GA/DL restored axonal organelle phenotypes ofmitochondria and lysosomes in FUS- and SOD1-ALS patient-derived motoneurons (MNs). This was not only accompanied by restoration of mitochondrial membrane potential but even dependent on it. Despite presenting an axonal transport deficiency as well, TDP43 patient-derived MNs did not share mitochondrial depolarization and did not respond to GA/DL treatment. GA and DL also restored cytoplasmic mislocalization of FUS and FUS recruitment to DNA damage sites, recently reported being upstream of the mitochondrial phenotypes in FUS-ALS. Whereas these data point towards the necessity of individualized (gene-) specific therapy stratification, it also suggests common therapeutic targets across different neurodegenerative diseases characterized by mitochondrial depolarization.

Industrial effluents or process waters generated from spent lithium-ion batteries (LIBs) recycling operations often contain high concentrations of lithium ions (Li+). This study characterizes the composition of process water obtained from pre-treatment and concentration operations of LIBs recycling. Ion-exchange experiments are conducted using synthetic lithium solutions (1 g/L) and industrial waters to understand Li+ recovery. Employing four commercial cationic resins, fast Li+ exchange kinetics are observed fitting the pseudo-second order model. The equilibrium isotherm data corresponds to the Langmuir adsorption model and reveals a Li capacity of 30 32 mg/g using AmberliteTM IRC 120 H, 70 mg/g using Lewatit® TP 308 H, 37 40 mg/g using Lewatit® TP 208 Na, and 37-41 mg/g using Lewatit® TP 260 Na. While the resins initially demonstrate moderate affinity for Li+, this can be significantly enhanced by increasing the Li+ concentration. Notably, as LIBs recycling operation effluents typically contain minimal competing ions, these results underscore the potential of employing ion exchange as a viable method to recover and concentrate lithium before precipitation into lithium salts.

Quantum path interferences occur whenever multiple equivalent and coherent transitions result in a common final state. Such interferences strongly modify the probability of a particle to be found in that final state, a key concept of quantum coherent control. When multiple nonlinear and energy-degenerate transitions occur in a system, the multitude of possible quantum path interferences is hard to disentangle experimentally. Here, we analyze quantum path interferences during the nonlinear emission of electrons from hybrid plasmonic and photonic fields using time-resolved photoemission electron microscopy.We experimentally distinguish quantum path interferences by exploiting the momentum difference between photons and plasmons and through balancing the relative contributions of their respective fields. Our work provides a fundamental understanding of the nonlinear photon–plasmon–electron
interaction. Distinguishing emission processes in momentum space, as introduced here, could allow nano-optical quantum-correlations to be studied without destroying the quantum path interferences.

We consider birefringent (i.e., polarization changing) scattering of x-ray photons at the superposition of two optical laser beams of ultrahigh intensity and study the resonant contributions of axions or axionlike particles, which could also be short lived. Applying the specifications of the Helmholtz International Beamline for Extreme Fields (HIBEF), we find that this setup can be more sensitive than previous light-bylight scattering (birefringence) or light-shining-through-wall experiments in a certain domain of parameter space. By changing the pump and probe laser orientations and frequencies, one can even scan different axion masses, i.e., chart the axion propagator.

Thermochemical treatment is significantly impacted by the physiochemical properties of lignocellulosic biomass. Traditional characterization methods lack granularity, requiring advanced analytical techniques for comprehensive biomass characterization. This study analyzed elemental composition and their distribution in untreated rice husk, rice straw, and bamboo chips at micron and sub-micron scales. Results reveal significant variations in composition and spatial distribution of metallic components among agro-residues. Thermogravimetric analysis shows divergent decomposition patterns, while spectroscopic analysis indicates structural complexities and distinct silica content. Surface mapping illustrates prevalent silica and alkali metals on rice husk and rice straw. Atomic force microscopy depicts distinctive surface morphologies, with rice straw exhibiting heightened roughness due to silica bodies. Inductively coupled plasma-mass-spectrometry identified the abundance of alkali and alkaline earth metals in rice waste. Time-of-flight secondary ion mass spectrometry elucidates elemental spatial localization, affirming heterogeneous distribution across rice waste and homogenous distribution across bamboo waste. This study bridges the gap between biomass composition and optimized thermochemical conversion outcomes.

The in vivo evolution of radiotherapy necessitates innovative platforms for preclinical investigation, bridging the gap between bench research and clinical applications. Understanding the nuances of radiation response, specifically tailored to proton and photon therapies, is critical for optimizing treatment outcomes. Within this context, preclinical in vivo experimental setups incorporating image guidance for both photon and proton therapies are pivotal, enabling the translation of findings from small animal models to clinical settings. The SAPPHIRE project represents a milestone in this pursuit, presenting the installation of the small animal radiation therapy integrated beamline (SmART+ IB, Precision X-Ray Inc., Madison, Connecticut, USA) designed for preclinical image-guided proton and photon therapy experiments at University Proton Therapy Dresden. Through Monte Carlo simulations, low-dose on-site cone beam computed tomography imaging and quality assurance alignment protocols, the project ensures the safe and precise application of radiation, crucial for replicating clinical scenarios in small animal models. The creation of Hounsfield lookup tables and comprehensive proton and photon beam characterizations within this system enable accurate dose calculations, allowing for targeted and controlled comparison experiments. By integrating these capabilities, SAPPHIRE bridges preclinical investigations and potential clinical applications, offering a platform for translational radiobiology research and cancer therapy advancements.

The discovery of the first binary neutron star merger, GW170817, has spawned a plethora of global numerical relativity simulations. These simulations are often ideal (with dissipation determined by the grid) and/or axisymmetric (invoking ad hoc mean-field dynamos). However, binary neutron star mergers (similar to X-ray binaries and active galactic nuclei inner discs) are characterized by large magnetic Prandtl numbers, Pm, (the ratio of viscosity to resistivity). Pm is a key parameter determining dynamo action and dissipation but it is ill-defined (and likely of order unity) in ideal simulations. To bridge this gap, we investigate the magnetorotational instability (MRI) and associated dynamo at large magnetic Prandtl numbers using fully compressible, three-dimensional, vertically stratified, isothermal simulations of a local patch of a disc. We find that, within the bulk of the disc (z ≲ 2H, where H is the scale-height), the turbulent intensity (parametrized by the stress-to-thermal-pressure ratio α), and the saturated magnetic field energy density, Emag, produced by the MRI dynamo, both scale as a power with Pm at moderate Pm (4 ≲ Pm ≲ 32): Emag ~ Pm0.74 and α ~ Pm0.71, respectively. At larger Pm (≳ 32), we find deviations from power-law scaling and the onset of a plateau. Compared to our recent unstratified study, this scaling with Pm becomes weaker further away from the disc mid-plane, where the Parker instability dominates. We perform a thorough spectral analysis to understand the underlying dynamics of small-scale MRI-driven turbulence in the mid-plane and of large-scale Parker-unstable structures in the atmosphere.

The Julia programming language was created 10 years ago and is now a mature and stable language with a large ecosystem including more than 8,000 third-party packages. It was designed for scientific programming to be a high-level and dynamic language as Python is, while achieving runtime performances comparable to C/C++ or even faster. With this, we ask ourselves if the Julia language and its ecosystem is ready now for its adoption by the High Energy Physics community. We will report on a number of investigations and studies of the Julia language that have been done for various representative HEP applications, ranging from computing intensive initial data processing of experimental data and simulation, to final interactive data analysis and plotting. Aspects of collaborative code development of large software within a HEP experiment has also been investigated: scalability with large development teams, continuous integration and code test, code reuse, language interoperability to enable an adiabatic migration of packages and tools, software installation and distribution, training of the community, benefit from development from industry and academia from other fields.

The critical behavior of the order-disorder phase transition in the buckled dimer structure of the Si(001) surface is investigated both theoretically by means of first-principles calculations and experimentally by spot profile analysis low-energy electron diffraction (SPA-LEED). We use density functional theory (DFT) with three different functionals commonly used for Si to determine the coupling constants of an effective lattice Hamiltonian describing the dimer interactions. Experimentally, the phase transition from the low-temperature c(4×2)- to the high-temperature p(2×1)-reconstructed surface is followed through the intensity and width of the superstructure spots within the temperature range 78–400K. Near the critical temperature Tc = 190.6K, we observe universal critical behavior of spot intensities and correlation lengths, which falls into the universality class of the two-dimensional (2D) Ising model. From the ratio of correlation lengths along and across the dimer rows we determine effective nearest-neighbor couplings of an anisotropic 2D Ising model,
J = (−24.9 ± 0.9stat ± 1.3sys )meV and J⊥ = (−0.8 ± 0.1stat )meV.We find that the experimentally determined coupling constants of the Ising model can be reconciled with those of the more complex lattice Hamiltonian
from DFT when the critical behavior is of primary interest. The anisotropy of the interactions derived from the
experimental data via the 2D Ising model is best matched by DFT calculations using the PBEsol functional.
The trends in the calculated anisotropy are consistent with the surface stress anisotropy predicted by the
DFT functionals, pointing towards the role of surface stress reduction as a driving force for establishing the
c(4×2)-reconstructed ground state.

Utilization of plastic materials (e.g., polyethylene) in mulching film production has inevitably resulted in nondegradable
pollutants in soil, which accordingly promotes the development of biodegradable mulching film
industry. As a rich renewable, biodegradable aromatic polymer, Lignin exhibits great potential for fabricating
functional biodegradable composite mulching films. In recent years, composite mulching films containing lignin
have garnered more interest for both practical applications and fundamental research, but comprehensive reviews
detailing preparation and application of this rapidly developing composite are still limited. Herein, we
begin with a brief description about the processes used to prepare lignin-based biodegradable mulching film.
Furthermore, the design and application advances of lignin-based biodegradable mulching films are elaborated
based on the polymer materials used, including natural and synthetic biodegradable polymers. Finally, the
remaining challenges and future perspectives of lignin-based biodegradable mulching films are summarized. We
expect that this finding will shed light on the forthcoming research of lignin-based biodegradable mulching film,
and stimulate the development in this research area.

This study provides for the first time details of the mineralogy, petrography and mineral paragenetic relationships of manganese ores of the Avontuur deposit, a prominent northern outlier of the Kalahari Manganese Field in the Northern Cape Province of South Africa. Using a combination of light and electron microscopy and X-ray powder diffractometry on an extensive suite of exploration drill core samples, it is shown that the manganese ores comprise an exceptionally fine-grained assemblage of Mn2+-silicates (friedelite, tephroite, gageite), Mn2+/Mn3+-oxides (jacobsite, hausmannite) and Mn2+-carbonates (rhodochrosite, kutnahorite, Mn-dolomite and Mn-calcite). This mineral assemblage is a product of diagenesis and very low-grade regional metamorphism. Locally, this assemblage is overprinted by contact metamorphism or supergene alteration. Despite close geochemical and textural similarities, the manganese ores of the Avontuur deposit are surprisingly different in their mineralogy compared to the carbonate- and braunite-dominated mangano-lutites of the main Kalahari deposit. Distinctly higher concentrations of both SiO2and Fe2O3in the mangano-lutites of the Avontuur deposit as compared to the main Kalahari Deposit provide the reason for the markedly different mineralogy. Such marked differences in bulk chemistry are tentatively attributed to systematic lateral variations in the physicochemical conditions of mineral precipitation during the deposition of the Hotazel Formation.

The Mn₂ complex (Mn(II)₂(TPDP)(O₂CPh)₂)(BPh₄) (1, TPDP = 1,3-bis(bis(pyridin-2-ylmethyl)amino)propan-2-ol, Ph = phenyl) was prepared and subsequently characterized via single-crystal X-ray diffraction, X-ray absorption, electronic absorption, and infrared spectroscopies, and mass spectrometry. 1 was prepared in order to explore its properties as a structural and functional mimic of class Ib ribonucleotide reductases (RNRs). 1 reacted with superoxide anion (O₂(•–)) to generate a peroxido-MnIIMnIII complex, 2. The electronic absorption and electron paramagnetic resonance (EPR) spectra of 2 were similar to previously published peroxido-Mn(II)Mn(III) species. Furthermore, X-ray near edge absorption structure (XANES) studies indicated the conversion of a Mn(II) 2 core in 1 to a Mn(II)Mn(III) state in 2. Treatment of 2 with para-toluenesulfonic acid (p-TsOH) resulted in the conversion to a new Mn(II)Mn(III) species, 3, rather than causing O—O bond scission, as previously encountered. 3 was characterized using electronic absorption, EPR, and X-ray absorption spectroscopies. Unlike other reported peroxido-Mn(II)Mn(III) species, 3 was capable of oxidative O—H activation, mirroring the generation of tyrosyl radical in class Ib RNRs, however without accessing the Mn(III)Mn(IV) state.

Cycling stability of the photochromic effect in rare-earth oxyhydride thin films is of great importance for longterm applications such as smart windows. However, an increasingly slower bleaching rate upon photochromic cycling was found in yttrium oxyhydride thin films; the origin of this memory effect is yet unclear. In this work, the microstructural changes under six photodarkening-bleaching cycles in YHxOy and GdHxOy thin films are investigated by in situ illumination Doppler broadening positron annihilation spectroscopy, complemented by positron annihilation lifetime spectroscopy (PALS) investigations on YHxOy films before and after one cycle. For the first three cycles, the Doppler broadening S parameter after bleaching increases systematically with photodarkening-bleaching cycle, and correlates with the bleaching time constant extracted from optical transmittance measurements. This suggests that the icrostructural evolution that leads to progressively slower bleaching involves vacancy creation and agglomeration. PALS suggests that during a photodarkening-bleaching cycle, divacancies are formed that are possibly composed of illumination-induced hydrogen vacancies and preexisting yttrium monovacancies, and vacancy clusters grow, which might be due to local removal of hydrogen. If bleaching is a diffusion-related process, the formed vacancy defects induced by illumination might affect the diffusion time by reducing the diffusion coefficient. Hydrogen loss could also be a key factor in the reduced bleaching kinetics. Other microstructural origins including domain growth, or formation of OH−hydroxide groups, are also discussed with respect to the slower bleaching kinetics. During the fourth to sixth photodarkening-bleaching cycle, reversible shifts in the Doppler S and W parameters are seen that are consistent
with the reversible formation of metallic-like domains, previously proposed as a key factor in the mechanism for the photochromic effect.

Neutron reflectivity (NR) was used to study the sorption of Eu(III) by graphene oxide (GO) films exposed to ethanol solution of EuCl3. Most of the earlier sorption studies have been performed using GO dispersed in solution. In contrast, layered structure of GO films imposes limitations for penetration of ions between individual sheets. The analysis of NR data recorded before and after sorption under vacuum demonstrates an increase of GO film thickness due to sorption by 35–40%. The characterization of chemical state of Eu(III) sorbed by GO films by X-ray absorption near-edge structure (XANES) in high-energy resolution fluorescence detection (HERFD) method at the Eu L3 edge reveals that it remains the same as in anhydrous EuCl3. Analysis of all collected data including reference experiments with bulk GO samples allows to conclude that EuCl3 penetrates into GO interlayers with ethanol solution and remains trapped in interlayers after evaporation of ethanol. Sorption of EuCl3 results in nearly complete amorphization of film and likely formation of voids, thus making NR models based on specific volume of unit cell not valid for quantitative evaluation of Eu sorption. Limitations of NR method must be taken into account in future studies of sorption by thin films.

In recent years, density functional theory (DFT) has revolutionzed simulations in the domain of warm dense matter (WDM) which focuses on unraveling behavior of matter in fusion reactor, planetary interiors and other areas of high energy physics. The success of DFT relies on accurate approximations of the exchange-correlation (XC) effects based on exact quantum monte carlo (QMC) results. In this contribution, we summarize our recent work toward improving XC at finite temperatures, which is called thermal PBE[1] and incorporting the improvements in LIBXC[2], a library widely used in the material science community. We highlight the software engineering challenges in the field of high performance computing including: (i) deployment of continuous integration (CI) using Gitlab runners, (ii) incorporating containers for CI and reproducibility and (iii) refactoring strategies. We also highlight the importance of research software engineering (RSE) for validating accurate utilization of community high-performance-computing codes.

References

[1] https://doi.org/10.48550/arXiv.2308.03319
[2] https://doi.org/10.1016/j.softx.2017.11.002

In this work, we propose a supervised framework for spectral unmixing of binary intimate mixtures. The core idea is based on geodesic distance measurements and regression to estimate the fractional abundances. The main assumption is that spectral reflectances of binary mixtures form a curve between the two endmembers, and the mixture's relative position on this curve serves as an indicator of its fractional abundances. We propose four novel approaches to approximate this relative position. From this, the fractional abundances are obtained using Gaussian process regression. The proposed framework simultaneously copes with the spectral variability by hypersphere and high-dimensional simplex projections. The approach is extensively validated on real datasets, including binary mineral mixtures and industrial clay powder mixtures produced in a laboratory setting, comprising 60 binary mixtures derived from five types of clay powders: Kaolin, Roof clay, Red clay, mixed clay, and Calcium hydroxide, measured by a variety of hyperspectral sensors in the VNIR-SWIR and mid-and longwave infrared regions. A comparison with the linear mixing model and several nonlinear mixing models demonstrates the superiority of the proposed approach.

CoNb₂O₆ is a model system for a spin-1/2 one-dimensional (1D) transverse-field Ising magnet (TFIM) with a rather low three-dimensional (3D) Néel ordering temperature at T_N = 2.95 K. We studied CoNb₂O₆ using ultrasound measurements down to 0.3 K in transverse magnetic fields applied along the b direction. Upon entering the 3D ordered state, we observe pronounced anomalies in the transverse acoustic mode c₆₆. In particular, from 1.3 to 1.5 K and around 4.7 T, this mode reveals an almost diverging softening, which is considerably reduced at lower and higher magnetic fields. We interpret this as an influence of quantum critical fluctuations emerging from the quantum critical point (QCP) of the 1D Ising spin chains at about 4.75 T, which lies below the QCP of the 3D ordering at about 5.4 T. This is clear experimental evidence of the predicted generic phase diagram for a TFIM with superimposed 3D ordering.

In this work, we study magnetoelastic interactions by means of ultrasound experiments in α-RuCl₃—a prototypical material for the Kitaev spin model on the honeycomb lattice, with a possible spin-liquid state featuring Majorana fermions and Z₂-flux excitations. We present results of the temperature and in-plane magnetic-field dependence of the sound velocity and sound attenuation for several longitudinal and transverse phonon modes propagating along high-symmetry crystallographic directions. A comprehensive data analysis above the magnetically ordered state provides strong evidence of phonon scattering by Majorana fermions. This scattering depends sensitively on the value of the phonon velocities relative to the characteristic velocity of the low-energy fermionic excitations describing the spin dynamics of the underlying Kitaev magnet. Moreover, our data displays a distinct reduction of anisotropy of the sound attenuation, consistent with the presence of thermally excited Z₂ visons. We demonstrate the potential of phonon dynamics as a promising probe for uncovering fractionalized excitations in α-RuCl₃ and provide new insights into the H-T phase diagram of this material.

We present a ³¹P NMR investigation of BaCdVO(PO₄)₂ focusing on the nearly saturated regime between μ₀H_c1 = 4.05 T and μ₀H_c2 = 6.5 T, which used to be considered a promising candidate for a spin-nematic phase. NMR spectra establish the absence of any dipolar order there, whereas the weak field dependence of the magnetization above H_c1 is accounted for by Dzyaloshinskii-Moriya interaction terms. The low-energy spin dynamics (fluctuations), measured by the nuclear spin-lattice relaxation rate T₁ ⁻¹, confirms the continuity of this phase and the absence of any low-temperature phase transition. Unexpectedly, the spin dynamics above H_c1 is largely dominated by two-magnon processes, which is expected above the saturation field of a spin-nematic phase, but not inside. This shows that BaCdVO(PO₄)₂ is indeed close to a spin-nematic instability; however, this phase is not stabilized. We thus confirm recent theoretical predictions that the spin-nematic phase can be stabilized, at most, in an extremely narrow field range close to saturation or is rather narrowly avoided [Jiang et al., Phys. Rev. Lett. 130, 116701 (2023)].

The ionic structure of high-pressure, high-temperature fluids is a challenging theoretical problem with applications to planetary interiors and fusion capsules. Here we report a multimessenger platform using velocimetry and in situ angularly and spectrally resolved x-ray scattering to measure the thermodynamic conditions and ion structure factor of materials at extreme pressures. We document the pressure, density, and temperature of shocked silicon near 100 GPa with uncertainties of 6%, 2%, and 20%, respectively. The measurements are sufficient to distinguish between and rule out some ion screening models.

The low efficiency of conventional liquefaction technologies based on the Joule-Thomson expansion makes liquid hydrogen currently not attractive enough for large-scale energy-related technologies that are important for the transition to a carbon-neutral society. Magnetocaloric hydrogen liquefaction has great potential to achieve higher efficiency and is therefore a crucial enabler for affordable liquid hydrogen. Cost-effective magnetocaloric materials with large magnetic entropy and adiabatic temperature changes in the temperature range of 77 ∼ 20 K under commercially practicable magnetic fields are the foundation for the success of magnetocaloric hydrogen liquefaction. Heavy rare-earth-based magnetocaloric intermetallic compounds generally show excellent magnetocaloric performances, but the heavy rare-earth elements (Gd, Tb, Dy, Ho, Er, and Tm) are highly critical in resources. Yttrium and light rare-earth elements (La, Ce, Pr, and Nd) are relatively abundant, but their alloys generally show less excellent magnetocaloric properties. A dilemma appears: higher performance or lower criticality? In this review, we study how cryogenic temperature influences magnetocaloric performance by first reviewing heavy rare-earth-based intermetallic compounds. Next, we look at light rare-earth-based, "mixed" rare-earth-based, and Gd-based intermetallic compounds with the nature of the phase transition order taken into consideration, and summarize ways to resolve the dilemma.