Publications Repository - Helmholtz-Zentrum Dresden-Rossendorf

Particle or grain size distributions often play an important role in understanding processes in the geosciences. Functional data analysis allows applying multivariate methods like principal components and discriminant analysis directly to such distributions. These are however often observed in the form of samples, and thus with a sampling error, i.e. each data point is a distribution, but one where the sampling error is present. This additional sampling error changes the properties of the multivariate variance and thus the value, number and direction of the principle components. The result of the principal component analysis becomes an artefact of the sampling error and can negatively affect the following data analysis.

Our contribution presents how to compute this sampling error and how to confront it in the context of principal component analysis. We demonstrate the effect of the sampling error and the effectiveness of the correction with a simulated dataset. We show how the interpretability and reproducibility of the principal components improve and become independent of the selection of the basis. We also demonstrate how the correction improves interpretability of the results on a grain size distribution dataset from river sediments.

Geometallurgy is an interdisciplinary research field concerned with the planning, monitoring, and optimisation of mineral resource extraction and beneficiation. Geometallurgy relies on a quantitative understanding of primary resource characteristics such as mineralogical composition and texture, the spatial distribution and variability of these characteristics, and how they interact with mining and beneficiation processes. Thus, ­geometallurgy requires accurate analytical data for resource characterisation and detailed models of orebody geology, mining and processing technologies, mineral economics, and the often-complex interactions between them. Here, we introduce the fundamental concepts relevant to the field, with particular emphasis on the current state-of-the-art and some notes on potential future developments

The chelating ability of quinoxaline cores and the redox activity of organosulfide bridges in layered covalent organic frameworks (COFs) offer dual active sites for reversible lithium (Li)-storage. The designed COFs combining these properties feature disulfide and polysulfide-bridged networks showcasing an intriguing Li-storage mechanism, which can be considered as a lithium–organosulfide (Li–OrS) battery. The experimental–computational elucidation of three quinoxaline COFs containing systematically enhanced sulfur atoms in sulfide bridging demonstrates fast kinetics during Li interactions with the quinoxaline core. Meanwhile, bilateral covalent bonding of sulfide bridges to the quinoxaline core enables a redox-mediated reversible cleavage of the sulfursulfur bond and the formation of covalently anchored lithium–sulfide chains or clusters during Li-interactions, accompanied by a marked reduction of Li–polysulfide (Li–PS) dissolution into the electrolyte, a frequent drawback of lithium–sulfur (Li–S) batteries. The electrochemical behavior of model compounds mimicking the sulfide linkages of the COFs and operando Raman studies on the framework structure unravels the reversibility of the profound Li-ion–organosulfide interactions. Thus, integrating redox-active organic-framework materials with covalently anchored sulfides enables a stable Li–OrS battery mechanism which shows benefits over a typical Li–S battery.

Photodetectors and sensors have a prominent role in our lives and cover a wide range of applications, including intelligent systems and the detection of harmful and toxic elements. Although there have been several studies in this direction, their practical applications have been hindered by slow response and low responsiveness. To overcome these problems, we have presented here a self-powered (photoelectrochemical, PEC), ultrasensitive, and ultrafast photodetector platform. For this purpose, a novel few-layered palladium–phosphorus–sulfur (PdPS) was fabricated by shear exfoliation for effective photodetection as a practical assessment. The characterization of this self-powered broadband photodetector demonstrated superior responsivity and specific detectivity in the order of 33 mA W–1 and 9.87 × 1010 cm Hz1/2 W–1, respectively. The PEC photodetector also exhibits a broadband photodetection capability ranging from UV to IR spectrum, with the ultrafast response (∼40 ms) and recovery time (∼50 ms). In addition, the novel few-layered PdPS showed superior sensing ability to organic vapors with ultrafast response and a recovery time of less than 1 s. Finally, the photocatalytic activity in the form of hydrogen evolution reaction was explored due to the suitable band alignment and pronounced light absorption capability. The self-powered sensing platforms and superior catalytic activity will pave the way for practical applications in efficient future devices.

The vibrational spectra of the copper(i) cation–dihydrogen complexes Cu+(H2)4{,} Cu+(D2)4 and Cu+(D2)3H2 are studied using cryogenic ion trap vibrational spectroscopy in combination with quantum chemical calculations. The infrared photodissociation (IRPD) spectra (2500–7300 cm−1) are assigned based on a comparison to IR spectra calculated using vibrational second-order perturbation theory (VPT2). The IRPD spectra exhibit ≈60 cm−1 broad bands that lack rotational resolution{,} indicative of rather floppy complexes even at an ion trap temperature of 10 K. The observed vibrational features are assigned to the excitations of dihydrogen stretching fundamentals{,} combination bands of these fundamentals with low energy excitations as well as overtone excitations of a minimum-energy structure with Cs symmetry. The three distinct dihydrogen positions present in the structure can interconvert via pseudorotations with energy barriers less than 10 cm−1{,} far below the zero-point vibrational energy. Ab initio Born–Oppenheimer molecular dynamics (BOMD) simulations confirm the fluxional behavior of these complexes and yield an upper limit for the timeframe of the pseudorotation on the order of 10 ps. For Cu+(D2)3H2{,} the H2 and D2 loss channels yield different IRPD spectra indicating non-ergodic behavior.

In Rayleigh–Bénard convection, the size of a flow domain and its aspect ratio Γ (a ratio
between the spatial length and height of the domain) affect the shape of the large-scale
circulation. For some aspect ratios, the flow dynamics includes a three-dimensional
oscillatory mode known as a jump rope vortex (JRV); however, the effects of varying
aspect ratios on this mode are not well investigated. In this paper, we study these aspect
ratio effects in liquid metals, for a low Prandtl number Pr = 0.03. Direct numerical
simulations and experiments are carried out for a Rayleigh number range 2.9 × 104 ≤
Ra ≤ 1.6 × 106 and square cuboid domains with Γ = 2, 2.5, 3 and 5. Our study
demonstrates that a repeating pattern of a JRV encountered at aspect ratio Γ ≈ 2.5 is the
basic structural unit that builds up to a lattice of interlaced JRVs at the largest aspect ratio.
The size of the domain determines how many structural units are self-organised within
the domain; the number of the realised units is expected to scale as Γ 2 with sufficiently
large and growing Γ . We find the oscillatory modes for all investigated Γ ; however, they
are more pronounced for Γ = 2.5 and 5. Future studies for large-aspect-ratio domains of
different shapes would enhance our understanding of how the JRVs adjust and reorganise
at such scaled-up geometries, and answer the question of whether they are indeed the
smallest superstructure units.

Flexible porous frameworks are at the forefront of materials research. A unique feature is their ability to open and close their pores in an adaptive manner induced by chemical and physical stimuli. Such enzyme-like selective recognition offers a wide range of functions ranging from gas storage and separation to sensing, actuation, mechanical energy storage and catalysis. However, the factors affecting switchability are poorly understood. In particular, the role of building blocks, as well as secondary factors (crystal size, defects, cooperativity) and the role of host–guest interactions, profit from systematic investigations of an idealized model by advanced analytical techniques and simulations. The review describes an integrated approach targeting the deliberate design of pillared layer metal–organic frameworks as idealized model materials for the analysis of critical factors affecting framework dynamics and summarizes the resulting progress in their understanding and application.

wo-dimensional conjugated covalent organic frameworks (2D c-COFs) are emerging semiconductor materials for optoelectronic and photothermal applications. In particular, the highly tailorable, semiconducting thiophene-based 2D c-COFs have attracted considerable interest due to their nontrivial physicochemical properties such as photo-activity, broad optical absorption, tunable electronic structures, and so forth. Herein, we demonstrate a novel, crystalline 2D c-COF based on thienyl-functionalized benzodithiophene (BDT) and biphenyl (BP) via the Schiff-base polycondensation reaction. The resultant BDT-BP-COF exhibits a broad optical absorption up to ca. 600 nm and decent π-conjugation along the 2D polymer skeleton, as revealed by the optical absorption and theoretical calculations. The favorable π-conjugation and the abundant electron-rich thiophene units confer excellent photo-activity to BDT-BP-COF towards the usage of solar energy. As a proof-of-concept application, we explore BDT-BP-COF in photothermal conversion, in which it shows a fast surface-temperature increase upon light irradiation for seconds.

The field of geometallurgy has largely contributed to the efficiency of the raw materials sector. In this workshop, we covered the main building blocks of a geometallurgy program: geostatistics, mineral characterization, uncertainties, mineral processing, and particle-based modelling.

Triangulene and its analogue metal-free magnetic systems have garnered increasing attention since their discovery. Predicting the magnetic coupling and spin-polarization energy with quantitative accuracy is beyond the predictive power of today’s density functional theory (DFT) due to their intrinsic multireference character. Herein, we create a benchmark dataset of 25 magnetic systems with nonlocal spin densities, including the triangulene monomer, dimer, and their analogues. We calculate the magnetic coupling (J) and spin-polarization energy (ΔEspin) of these systems using complete active space self-consistent field (CASSCF) and coupled-cluster methods as high-quality reference values. This reference data is then used to benchmark 22 DFT functionals commonly used in material science. Our results show that, while some functionals consistently correctly predict the qualitative character of the ground state, achieving quantitative accuracy with small relative errors is currently not feasible. PBE0, M06-2X, and MN15 are predicting the correct electronic ground state for all systems investigated here and also have the lowest mean absolute error for predicting both ΔEspin (0.34, 0.32, and 0.31 eV) and J (11.74, 12.66, and 10.64 meV). They may therefore also serve as starting points for higher-level methods such as the GW or the random phase approximation. As other functionals fail for the prediction of the ground state, they cannot be recommended for metal-free magnetic systems.

The field of automated mineralogy has largely contributed to our understanding of mineral processing. Lately, by evaluating the particle information collected with automated mineralogy using statistical learning methods, it became possible to quantify the process behaviour of individual particles with consideration to their size, shape, liberation, and mineral association. In this workshop, we explore the latest methods used to quantify the recoverability of individual particles and how their results can be used to better understand mineral processing.

Tellurium oxides of the ATeO3 form typically do not crystallize in perovskite structures.
Here, we show that perovskite-like ATeO3 (A = Ca, Sr, Ba) thin films can be grown on perovskite
single-crystal substrates via epitaxial stabilization. These films are stable with high optical bandgaps,
low dielectric losses, and a high electric breakdown strength. Hysteretic dielectric behavior found
in SrTeO3 and BaTeO3 strongly suggests the presence of antiferroelectricity and ferroelectricity,
respectively. These properties make perovskite tellurium oxides possibly appealing candidates for
thin film coating or insulator materials in advanced microelectronics. Tellurium oxides constitute a
largely unexplored class of materials that might show new and interesting functionalities in epitaxial
thin-films. Our work encourages new work within this field.

We report a chemically programmed design and the switching characteristics of a functional metal–DNA-origami–polyoxometalate (POM) material obtained from the solution-processed assembling of biocompatible molecular precursors. The DNA origami is immobilized on the gold surface via thiolate groups and acts as a carrier (ad-layer) structure, ensuring the spatially controlled hybridization of the pre-defined six-helix bundle (6HB) positions with DNA-augmented, tris(alkoxo)-ligated Lindqvist-type polyoxovanadate (POV6) units. The DNA-confined POV6 units accept electrons in a stepwise fashion, allowing for a multi-logic function, which we directly probe using scanning tunneling electron microscopy and spectroscopy. Electron acceptance and injection into the originally non-conducting DNA structure and the subsequent release to the gold substrate depend upon the potential at the nanoscale tip and the oxidation state of POV6, as well as on the mechanism of action of POV6 countercations. By combining experiment and theory, we show that the bio-hybrid heterojunction has far-reaching potential to create a chemically controlled POM-based nano-environment with synaptic behavior.

We study the properties of hybrid stars containing a color superconducting quark matter phase in their
cores, which is described by the chirally symmetric formulation of the confining relativistic density
functional approach. It is shown that, depending on the dimensionless vector and diquark couplings of
quark matter, the characteristics of the deconfinement phase transition are varied, allowing us to study the
relation between those characteristics and mass-radius relations of hybrid stars. Moreover, we show that the
quark matter equation of state (EoS) can be nicely fitted by the Alford-Braby-Paris-Reddy model that gives
a simple functional dependence between the most important parameters of the EoS and microscopic
parameters of the initial Lagrangian. Based on it, we analyze the special points of the mass-radius diagram
in which several mass-radius curves intersect. Using the found empirical relation between the mass of the
special point, the maximum mass of the mass-radius curve, and the onset mass of quark deconfinement,
we constrain the range of values of the vector and diquark couplings of the quark matter model. With this
constraint, we construct a family of mass-radius curves, which allow us to describe the black widow pulsar
PSR J0952-0607 with a mass of 2.35 +/- 0.17M⊙ as a hybrid star with a color superconducting quark
matter core.

Metal-free magnetism remains an enigmatic field, offering prospects for unconventional magnetic and electronic devices. In the pursuit of such magnetism, triangulenes, endowed with inherent spin polarization, are promising candidates to serve as monomers to construct extended structures. However, controlling and enhancing the magnetic interactions between the monomers persist as a significant challenge in molecular spintronics, as so far only weak antiferromagnetic coupling through the linkage has been realized, hindering their room temperature utilization. Herein, we investigate 24 triangulene dimers using first-principles calculations and demonstrate their tunable magnetic coupling (J), achieving unprecedented strong J values of up to −144 meV in a non-Kekulé dimer. We further establish a positive correlation between bandgap, electronic coupling, and antiferromagnetic interaction, thereby providing molecular-level insights into enhancing magnetic interactions. By twisting the molecular fragments, we demonstrate an effective and feasible approach to control both the sign and strength of J by tuning the balance between potential and kinetic exchanges. We discover that J can be substantially boosted at planar configurations up to −198 meV. We realize ferromagnetic coupling in nitrogen-doped triangulene dimers at both planar and largely twisted configurations, representing the first example of ferromagnetic triangulene dimers that cannot be predicted by the Ovchinnikov rule. This work thus provides a practical strategy for augmenting magnetic coupling and open up new avenues for metal-free ferromagnetism.

Recent research on two-dimensional (2D) transition metal dichalcogenides (TMDCs) has led to remarkable discoveries of fundamental phenomena and to device applications with technological potential. Large-scale TMDCs grown by chemical vapor deposition (CVD) are now available at continuously improving quality, but native defects and natural degradation in these materials still present significant challenges. Spectral hysteresis in gate-biased photoluminescence (PL) measurements of WSe2 further revealed long-term trapping issues of charge carriers in intrinsic defect states. To address these issues, we apply here a two-step treatment with organic molecules, demonstrating the ``healing'' of native defects in CVD-grown WSe2 and WS2 by substituting atomic sulfur into chalcogen vacancies. We uncover that the adsorption of thiols provides only partial defect passivation, even for high adsorption quality, and that thiol adsorption is fundamentally limited in eliminating charge traps. However, as soon as the molecular backbone is trimmed and atomic sulfur is released to the crystal, both bonds of the sulfur are recruited to passivate the divalent defect and the semiconductor quality improves drastically. Time-dependent X-ray photoelectron spectroscopy (XPS) is applied here together with other methods for the characterization of defects, their healing, leading energies and occupation. First-principles calculations support a unified picture of the electronic passivation of sulfur-healed WSe2 and WS2. This work provides a simple and efficient method for improving the quality of 2D semiconductors and has the potential to impact device performance even after natural degradation.

In recent years, several definitions of entropy have been proposed and used in the literature to assess the efficiency of processes in the field of raw materials, including waste management, the circular economy, and mineral separation. However, these definitions have lacked a common framework, making it difficult to compare them and assess their similarities, connections, and complementarities. In this contribution, we propose a common framework which describes the calculation of the entropy of particulate systems. This framework extends existing definitions and introduces new insights into their combination. Our approach focuses on the description of disperse particulate systems in comminution, separation, and classification processes, with potential extensions to evaluate other processes of particle technology, such as mixing, sampling, and agglomeration

Increasing habitat fragmentation and disturbance threaten long-distance movements of ungulates. While the effects of impermeable barriers on ungulate migrations have been well researched, quantitative evidence for gradual, long-term changes of mobility remains rare.

We investigated changes in movement behavior of Mongolian gazelle Procapra gutturosa using GPS tracking data collected from 62 gazelle individuals between 2007 and 2021. We quantified 16-day displacement distances as a metric for long-distance movements before using linear mixed models, generalized additive models and quantile regressions to assess how anthropogenic and environmental factors affected gazelle movement behavior.

Long-distance 16-day movements decreased by 36 %, from 142 km in 2007 to 92 km in 2021. Changes in mobility were affected by increasing vehicle numbers in Mongolia, but could not be explained by concurrent changes in other environmental factors like temperature, precipitation or vegetation greenness. Gazelle movement decreased close to roads, and gazelles stayed further away from roads during the snow-free season, when traffic likely is most intense.

Conserving landscape permeability is essential for maintaining populations of highly mobile species. Our study provides evidence for a gradual decline in gazelle mobility over fifteen years as a response to increasing anthropogenic impact. The transportation infrastructure permeating the Eastern Steppe does not pose physical barriers, yet our findings suggest that increasing traffic volume may create semipermeable barriers to gazelle movement. As human activity is increasing, interactions between ungulates and vehicle traffic need to be closely monitored to identify and mitigate semipermeable barrier effects before landscape permeability is severely altered.

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The strategic combination of redox-active triazine- or quinoxaline-based lithium-ion battery (LIB) mechanisms with the polysulfide ring-mediated lithium-sulfur battery (Li-SB) mechanism enabled the configuration of covalent organic-framework (COF)-derived lithium-organosulfide (Li-OrSB) battery systems. Two vinylene-linked frameworks were designed by enclosing polysulfide rings via postsynthetic framework sulfurization, allowing for the separate construction of triazine-polysulfide and quinoxaline-polysulfide redox couples that can readily interact with Li ions. The inverse vulcanization of the vinylene linking followed by the sulfurization-induced nucleophilic aromatic substitution reaction (SNAr) on the perfluorinated aromatic center of the COFs enabled the covalent trapping of cyclic-polysulfides. The experimentally observed reversible Li-interaction mechanism of these highly conjugated frameworks was computationally verified and supported by in situ Raman studies, demonstrating a significant reduction of polysulfide shuttle in a conventional Li-SB and opening the door for a COF-derived high-performing Li-OrSB.

Abstract Carbonyl aromatic compounds are promising cathode candidates for lithium-ion batteries (LIBs) because of their low weight and absence of cobalt and other metals, but they face constraints of limited redox-potential and low stability compared to traditional inorganic cathode materials. Herein, by means of first-principles calculations, a significant improvement of the electrochemical performance for carbonyl-bridged heterotriangulenes (CBHTs) is reported by introducing pyridinic N in their skeletons. Different center atoms (B, N, and P) and different types of functionalization with nitrogen effectively regulate the redox activity, conductivity, and solubility of CBHTs by influencing their electron affinity, energy levels of frontier orbitals and molecular polarity. By incorporating pyridinic N adjacent to the carbonyl groups, the electrochemical performance of N-functionalized CBHTs is significantly improved. Foremost, the estimated energy density reaches 1524 Wh kg−1 for carbonyl-bridged tri (3,5-pyrimidyl) borane, 50\% higher than in the inorganic reference material LiCoO2, rendering N-functionalized CBHTs promising organic cathode materials for LIBs. The investigation reveals the underlying structure-performance relationship of conjugated carbonyl compounds and sheds new lights for the rational design of redox-active organic molecules for high-performance lithium ion batteries (LIBs).

Characterization of diglycolamide resin using XRF, SEM, XPS, FTIR.

Abstract Partially occupied orbitals play a pivotal role in enhancing the performance of electrocatalyst by facilitating electron acceptance and donation, thus enabling the activation of molecular bonds. According to this principle, the basal plane of most 2D semiconductors is inert for electrocatalysis because of the fully occupied orbitals at the surface. Here, taking monolayer CrX (X = P, As, Sb) and Cr2PY (Y = As, Sb) as examples and through first-principles calculations, it is revealed that even with fully occupied surface orbitals, the basal planes exhibit remarkable catalytic activity for the nitrogen oxide reduction reaction (NORR). This leads to the concept of the pseudo-inert electrocatalyst. The underlying physics behind such pseudo-inert character can be attributed to the reversal-activation mechanism: contrary to conventional expectations, the adsorbed NO molecule reversely triggers the activity of the inert basal plane first, and then the basal plane activates NO molecules, forming the intriguing “Reversal Activation-Transfer-Donation-Backdonation” process. This study further predicts that such pseudo-inert character can demonstrate many distinctive properties, for example, it can introduce a novel type of surface catalysis, one that selectively targets radicals possessing an inherent dipole moment such as NO. The explored phenomena and insights greatly enrich the realms of electrocatalysis and 2D materials.

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The quality of results obtained by a scanning electron microscope-based automated mineralogy systems strongly depend on the project-specific library of spectra of the minerals considered to form the samples analysed, the mineral table. Mineral tables can be selected from existing universal libraries according to the expected or suspected minerals, and/or can be constructed based on spectra collected in the samples of a specific project. One can prefer extense mineral tables to enhance the chances of capturing variations in chemical composition of specific minerals; or else smaller, compact mineral tables to reduce misclassification. No general, perfect balance within generality-specificity or extension-compaction exists, so that users end up interactively and iteratively building the spectral library for each project in tedious steps of adding and removing mineral spectral candidates. This process is also project- and ore-specific. While some automated mineralogy devices provide operating modes for automatically constructing mineral lists throughout a measurement, these commonly offer only limited settings and are not clear about the data processing steps.

The goal of this contribution is to compare the performance of several components of a strategy to automatically construct automated mineralogy mineral lists - making use of several machine learning algorithms, for the specific case of dataset collected with the Mineral Liberation Analyser (MLA). The strategy has five steps: (1) preliminary data transformation, (2) dimension reduction, (3) endmember detection, (4) phase detection, and (5) unmixing.

For each of these steps, several options were tested. These included for data transformation peak extraction and Box-Cox transformations, which at the same time embraces logarithm/log-ratio transformations, square root transformations and the identity transformation. Regarding dimension reduction, principal component analysis and minimum-maximum autocorrelation factors were tested. In step three, we considered QHull convex hull detection, and N-FINDER, a conventional linear endmember detection method. In step four, the goal is to find the groups of spectra that can be identified with the members of the mineral table, not all of them being necessarily endmembers. Algorithms tested here correspond to model-free unsupervised classification algorithms, such as k-means, hyerarchical clustering methods and topological spectral clustering among other. Finally, in step five we tried several sparse and unconstrained linear unmixing algorithms. This unmixing was done within the sample of spectra forming the training data only in order to determine the number of necessary groups (or clusters) to extract from step four, as the actual final phase attribution will be done by the MLA software for the whole project after delivering the mineral table. The strategy presented here offers not only improvements to the workflow of scanning electron microscope-based automated mineralogy systems but also is a step stone for compiling mineral lists in analytical devices such as µX-Ray Fluorescence automated mineralogy, where spectra mixing is a bigger issue.

Electron-phonon interactions, crucial in condensed matter, are rarely seen in Metal-Organic Frameworks (MOFs). Detecting these interactions typically involves analyzing luminescence in lanthanide- or actinide-based compounds. Prior studies on Ln- and Ac-based MOFs at high temperatures revealed additional peaks, but these were too faint for thorough analysis. In our research, we fabricated a high-quality, crystalline uranium-based MOF (KIT-U-1) thin film using a layer-by-layer method. Under UV light, this film showed two distinct 'hot bands,' indicating a strong electron-phonon interaction. At 77 K, these bands were absent, but at 300 K, a new emission band appeared with half the intensity of the main luminescence. Surprisingly, a second hot band emerged above 320 K, deviating from previous findings in rare-earth compounds. We conducted a detailed ab-initio analysis employing time-dependent density function theory to understand this unusual behaviour and to identify the lattice vibration responsible for the strong electron-phonon coupling. The KIT-U-1 film's hot-band emission was then utilized to create a highly sensitive, single-compound optical thermometer. This underscores the potential of high-quality MOF thin films in exploiting the unique luminescence of lanthanides and actinides for advanced applications.

Freshwater shortages causes challenges in mineral processing in Chile, especially in arid regions. As a result, froth flotation; a mineral process, is shifting usage of freshwater to seawater. This has consequences in the consumption of flotation reagents and decreasing the flotation efficiency. Biotechnological developments allow conceptualising the use of bacterial cells and their metabolites as bioreagents in flotation; classified as bioflotation.
In this thesis, 5 halophilic bacteria, namely, Halomonas boliviensis, Marinobacter spp., Halobacillus litoralis Hol-1, Marinococcus halophilus KOR-3 and Halomonas eurihalina P6-1 have been screened for the potential use as pyrite biodepressants at micro- and batch-scale flotation. The effect of bioconditioning minerals with these bacteria was studied using zeta potential, fluorescence microscopy and contact angle.
Experiments measuring zeta potential show the isoelectric point (IEP) of pyrite, chalcopyrite and molybdenite became more acidic post-bioconditioning. Fluorescence microscopy with Nile red; a hydrophobic stain, allowed for a method to visualize bacterial cells or collector potassium isopropyl xanthate (KIPX) on mineral particles of pyrite, chalcopyrite and molybdenite. Additionally contact angle experiments show that strains Halobacillus litoralis Hol-1, Marinococcus halophilus KOR-3 and Halomonas eurihalina P6-1 had an influence on the contact angle of pyrite and chalcopyrite, inducing changes in their hydrophobicity.
Microflotation experiments showed a decreased recovery of pyrite in presence of all strains, but notably, Halobacillus litoralis Hol-1 and Marinococcus halophilus KOR-3, also showed an increased recovery of chalcopyrite, making them ideal candidates as pyrite biodepressants. Halomonas eurihalina P6-1 showed low recoveries of both minerals, but a higher selectivity depressing more pyrite than chalcopyrite. Usage of autoclaved biomass from the three aforementioned strains in batch-flotation experiments resulted in the recovery of chalcopyrite improving, with a small decrease in the recovery of pyrite, overall showing a positive potential but not improving the system.
Halophilic bacteria such as the ones used in this study show an influence on the floatability of pyrite, which could be commercially exploited to substitute lime as a pyrite depressant. Furthermore, the work in this thesis focused on studying the effects of cells in artificial seawater, both at micro and batch-scales which brings the laboratory experiments a step closer to industrially relevant conditions.

Due to their special properties, lanthanides (Ln) are of utmost importance in the current technological era – both in the present and in the future. Besides their indispensable contribution to high-tech products, they are also increasingly used in environmental technology. In recent years, attention has turned to alternative solutions such as the recycling of Ln from end-of-life products or wastewater from industry and mining. However, these contain only low concentrations of rare earth elements (REE), which are additionally very similar in their chemical and physical properties, so that the separation is cost-intensive and an efficient recovery still far away. Research and development of new recycling processes should change this and enable a cost-effective and environmentally friendly separation from electronic scrap and wastewater in order to conserve primary resources and make us independent of them. We are researching a promising approach for such a novel recycling technology and try to solve the separation problem using selective peptides. Immobilized on a suitable carrier material, this kind of biohybrid separation platform can finally be used for REE recovery.
By combining phage surface display technique with next generation sequencing and running parallel biopannings on target ion and immobilization material, we were able to enrich and identify peptide sequences showing an affinity for the europium ion (Eu3+). Most enriched and repetitive peptide variants in several biopannings with different elution types were characterized by time-resolved laser fluorescence spectroscopy and isothermal titration calorimetry with respect to their Eu3+ affinity. Calmodulin’s EF-hand 4 peptide serves as a reference system.

Weight window, a variance reduction tool, is often used to improve the performance of radiation shielding calculations. One common issue with the weight window is determining the optimal set of weight window parameters for solving deep penetration shielding problems. To address this issue, the recursive Monte-Carlo methodology has been used with the in-house TRAWEI code. The program is responsible for generating the optimal weight parameters in a single run with minimum computational time. This paper presents the results of a numerical test conducted using a simple reactor model to evaluate the performance of the developed weight generator program. The findings reveal that MCNP simulations utilizing TRAWEI-generated weight values exhibit significantly higher calculation efficiency compared to both analog simulation and MCNP simulation using weights generated by the existing MCNP weight window generator. Overall, the utilization of the RMC methodology has shown its potential to significantly contribute to deep penetration shielding calculations.

Electronic structure theory calculations offer an understanding of matter at the quantum level, complementing experimental studies in materials science and chemistry. One of the most widely used methods, density functional theory (DFT), maps a set of real interacting electrons to a set of fictitious non-interacting electrons that share the same probability density. Ensuring that the density remains the same depends on the exchange-correlation (XC) energy and, by a derivative, the XC potential. Inversions provide a method to obtain exact XC potentials from target electronic densities, in hopes of gaining insights into accuracy-boosting approximations. Neural networks provide a new avenue to perform inversions by learning the mapping from density to potential. In this work, we learn this mapping using physics-informed machine learning (PIML) methods, namely physics informed neural networks (PINNs) and Fourier neural operators (FNOs). We demonstrate the capabilities of these two methods on a dataset of one-dimensional atomic and molecular models. The capabilities of each approach are discussed in conjunction with this proof-of-concept presentation. The primary finding of our investigation is that the combination of both approaches has the greatest potential for inverting the Kohn-Sham equations at scale.

Improving the sustainability of critical raw
materials extraction

This presentation provides insights into the development of the HZDR's in-house laboratory notebook for the documentation of scientific experiments. A special focus is placed on the integration of a variety of third-party systems in order to optimise the automated enrichment of data in the laboratory notebook and to facilitate documentation for scientists.

The talk addresses critical components of the FAIR data principles by examining the central role of data policies and infrastructure services. On the path to making data findable, accessible, interoperable and reusable (FAIR), the talk provides insights in the fundamental strategies for creating effective data policies and implementing infrastructure services that support these principles. Drawing on real-world experiences at HZDR, this talk will provide actionable insights for advancing FAIR data practices in research domains and highlight the essential cornerstones on this transformative journey.

HELIPORT is a data management solution that aims at making the components and steps of the entire research experiment’s life cycle discoverable, accessible, interoperable and reusable according to the FAIR principles.
Among other information, HELIPORT integrates documentation, scientific workflows, and the final publication of the research results - all via already established solutions for proposal management, electronic lab notebooks, software development and devops tools, and other additional data sources. The integration is accomplished by presenting the researchers with a high-level overview to keep all aspects of the experiment in mind, and automatically exchanging relevant metadata between the experiment’s life cycle steps.
Computational agents can interact with HELIPORT via a REST API that allows access to all components, and landing pages that allow for export of digital objects in various standardized formats and schemas. An overall digital object graph combining the metadata harvested from all sources provides scientists with a visual representation of interactions and relations between their digital objects, as well as their existence in the first place. Through the integrated computational workflow systems, HELIPORT can automate calculations using the collected metadata.
By visualizing all aspects of large-scale research experiments, HELIPORT enables deeper insights into a comprehensible data provenance with the chance of raising awareness for data management.

Non-reciprocal wave propagation arises in systems with broken time-reversal symmetry and is key to the functionality of devices, such as isolators or circulators, in microwave, photonic and acoustic applications. In magnetic systems, collective wave excitations known as magnon quasiparticles so far yielded moderate non-reciprocities, mainly observed by means of incoherent thermal magnon spectra, while their occurrence as coherent spin waves (magnon ensembles with identical phase) is yet to be demonstrated. Here, we report the direct observation of strongly non-reciprocal propagating coherent spin waves in a patterned element of a ferromagnetic bilayer stack with antiparallel magnetic orientations. We use time-resolved scanning transmission x-ray microscopy (TR-STXM) to directly image the layer-collective dynamics of spin waves with wavelengths ranging from 5 µm down to 100 nm emergent at frequencies between 500 MHz and 5 GHz. The experimentally observed non-reciprocity factor of these counter-propagating waves is greater than 10 with respect to both group velocities and specific wavelengths. Our experimental findings are supported by the results from an analytic theory and their peculiarities are further discussed in terms of caustic spin-wave focusing.

The world is witnessing unprecedented advances in the field of renewable energy generation, storage,
electrical mobility, and digital technologies. These developments are necessary to achieve our
ambitions of becoming a green and sustainable society that retains economic prosperity. Behind the
scenes this transition is enabled by a multitude of increasingly complex materials marked by impressive
optoelectronic and/ magnetic properties. Not only does the complexity of materials increase, but also
similar is true for the compositional architecture of machines, gadgets and installations. This is
combined with an ever-increasing speed with which advanced technologies penetrate global markets
and the often very limited life span / planned obsolence of many advanced technologies. Together,
these factors yield a rapidly increasing volume of waste materials of complex composition. Such
complex waste materials do not only contain a vast variety of valuable resources but, if left untreated,
may cause great harm to humans and the environment. It is, therefore, obvious that we need no less
than a paradigm shift. EoL products should be regarded not as waste but as valuable secondary
resource. Technological solutions are urgently needed to drive the transition towards holistic recycling
concepts.
The simple, holistic and yet sustainable answer to all these questions is the adoption of circular
economy strategies. This talk will present the opportunities and challenges in management of
advanced materials with end-of-life perspective. How the fundamental understanding of materials
properties and quantities is necessary in viable circular economy process developments and
implementation. It will be complemented by select examples of technologies developed for the
recycling of relevant materials and its materials safety-related implications.

Efficient sequestration of arsenic from drinking water is a global need. Herein we report eco-friendly porous hybrid adsorbent beads for removal of arsenic, through in situ synthesis of MIL-100(Fe) in the chitosan solvogel. To understand the structural vs. performance correlation, series of hybrid adsorbents were synthesized by modulating synthesis conditions like temperature, crystallization time, and concentration. Adsorbents were investigated using PXRD, FT-IR, SEM, and ICP-OES. Intriguing correlation between crystallinity and adsorption performance was observed as low and high crystalline MIL-100(Fe)-chitosan (ChitFe5 and ChitFe7, respectively) exhibited exceptional adsorption towards As5+ by removing it from water with 99% efficiency, whereas for As3+ species removal of about 85% was afforded. Adsorption isotherms indicated that increase in crystallinity (ChitFe5 -> ChitFe7), adsorption capacities of As5+ and As3+ increased from 23.2 to 64.5, and from 28.1 to 35.3 mg/g, respectively. Selectivity tests of the adsorbents towards As5+ and As3+ over competitive anions in the equimolar competitive systems having nitrates, sulfates, and carbonates demonstrated that the performance of the absorbents was fully maintained, relative to the control system. Through this study a highly selective and efficient adsorbent for arsenic species is designed and a clear insight into the structural tuning and its effect on adsorption performance is provided.

Appropriate waste and resource management are essential for a sustainable circular economy with reduced environmental impact. With critical resources, e-waste may serve as indirect raw material. For example, with NdFeB permanent magnets, Neodymium (Nd) and the co-present Dysprosium (Dy) are critical rare earth elements (REEs). However, there exists no economically viable technology for recycling them from electronic waste (e-waste). Here, a method is presented based on cloud point extraction (CPE). The work involves basic complexation chemistry in a cloud medium with pure REE salts, as well as, with real NdFeB-magnets (nearly 28% REE content by weight) from an old hard disk drive (5.2 g magnet in a 375 g HDD). High extraction efficiency (>95%) was achieved for each REE targeted (Nd, Dy, Praseodymium (Pr)). With the magnet waste, the cloud phase did hardly contain any Nickel (Ni), Cobalt (Co), or Boron (B), but some Aluminium (Al) and Iron (Fe). Dynamic light scattering results indicated aggregation of ligand-surfactant micelles with the cloud phase. The preconcentrated products can be used for new Nd magnet manufacturing or further enriched using established transition metal removal techniques. Reuse of solvent, low chemical inventory demand, and using non-inflammable, non-volatile organic extractants promise safe large-scale operation, low process costs, and less environmental impact than using hydrometallurgical methods used with urban or primary mining.

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

original input and output files to create tables and figures as described in the corresponding paper.

This repository contains all input files and the thereby generated raw data used to generate figures and other results described in the corresponding paper.

dataset to calculate DEED; code of the algorithm to perform the DEED calculation

The need for improved functionalities in extreme environments is fuelling interest
in high-entropy ceramics. Except for the computational discovery of high-entropy
carbides, performed with the entropy-forming-ability descriptor, most innovation
has been slowly driven by experimental means. Hence, advancement in the field
needs more theoretical contributions. Here we introduce disordered enthalpy–
entropy descriptor (DEED), a descriptor that captures the balance between
entropy gains and enthalpy costs, allowing the correct classification of functional
synthesizability of multicomponent ceramics, regardless of chemistry and structure.
To make our calculations possible, we have developed a convolutional algorithm that
drastically reduces computational resources. Moreover, DEED guides the experimental
discovery of new single-phase high-entropy carbonitrides and borides. This work,
integrated into the AFLOW computational ecosystem, provides an array of potential
new candidates, ripe for experimental discoveries.

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The Random-Phase approximation (RPA) provides an appealing framework for semi-local density functional theory. In its Resolution-of-the-Identity (RI) approach it is a very accurate and more cost-effective method than most other wavefunction-based correlation methods. For widespread applications efficient implementations of nuclear gradients for structure optimizations and data sampling of machine learning approaches is required. We report a well scaling implementation of RI-RPA nuclear gradients on massively parallel computers. The approach is applied to two polymorphs of the benzene crystal obtaining very good cohesive and relative energies. Different correction and extrapolation schemes are investigated for further improvement of the results and estimations of error bars.

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Water adsorption and dissociation processes on pristine low-index TiO2 interfaces are important but poorly understood outside the well-studied anatase (101) and rutile (110). To understand these, we construct three sets of machine learning potentials that are simultaneously applicable to various TiO2 surfaces, based on three density-functional-theory approximations. Here we show the water dissociation free energies on seven pristine TiO2 surfaces, and predict that anatase (100), anatase (110), rutile (001), and rutile (011) favor water dissociation, anatase (101) and rutile (100) have mostly molecular adsorption, while the simulations of rutile (110) sensitively depend on the slab thickness and molecular adsorption is preferred with thick slabs. Moreover, using an automated algorithm, we reveal that these surfaces follow different types of atomistic mechanisms for proton transfer and water dissociation: one-step, two-step, or both. These mechanisms can be rationalized based on the arrangements of water molecules on the different surfaces. Our finding thus demonstrates that the different pristine TiO2 surfaces react with water in distinct ways, and cannot be represented using just the low-energy anatase (101) and rutile (110) surfaces.

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Particle-in-cell (PIC) simulations are a widely-used tool to model kinetics-dominated plasmas in ultrarelativistic laser-solid interactions (dimensionless vectorpotential a0 > 1). However, interactions approaching subrelativistic laser intensities (a0 ≲ 1) are governed by correlated and collisional plasma physics, calling for benchmarks of available modeling capabilities and the establishment of standardized testbeds. Here, we propose such a testbed to experimentally benchmark PIC simulations of laser-solid interactions using a laser-irradiated micron-sized cryogenic hydrogen-jet target. Time-resolved optical shadowgraphy of the expanding plasma density, complemented by hydrodynamics and ray-tracing simulations, is used to determine the bulk-electron-temperature evolution after laser irradiation. We showcase our testbed by studying isochoric heating of solid hydrogen induced by laser pulses with a dimensionless vectorpotential of a0 ≈ 1. Our testbed reveals that the initial surface-density gradient of the target is decisive to reach quantitative agreement at 1 ps after the interaction, demonstrating its suitability to benchmark controlled parameter scans at subrelativistic laser intensities.

We present results for direct maskless magnetic patterning of ferromagnetic nanostructures using a special liquid metal alloy ion source for focused ion beam (FIB) systems. We used a Co36Nd64 alloy as the FIB source [1]. A Wien mass filter allows for quick switching between the ion species in the alloy without changing the FIB source. A 5000×1000×50 nm3 permalloy strip served as the sample. Using the FIB we implanted a 300-nm-wide track with Co ions (see Fig.1). We observed the Co-induced changes by measuring the sample with microresonator ferromagnetic resonance before and after the implantation. Structures as small as 30 nm can be implanted up to a concentration of 10 % near the surface. Such lateral resolution is hard to reach for other lithographic methods. This allows for easy magnetic modification of edge-localized spin waves.
In another set of samples, we implanted Dy ions to locally increase the damping in a stripe pattern of ~120-nm-wide strips with 400 nm periodicity on a total area of 1×1 mm². Thus, the Gilbert damping parameter can be easily increased by one order of magnitude with a lateral resolution of about 100 nm.
In contrast to electron beam lithography in combination with broad-beam ion implantation, the maskless FIB process does not require the cumbersome and difficult removal of the ion-hardened resist if optical measurements like BLS or TR-MOKE are needed.

The environmental fate of radiotoxic actinides is controlled by their interactions with feldspars. Here, the sorption of trivalent minor actinides (Am, Cm) and their rare earth analogue Eu onto synthetic pure Ca-feldspar (anorthite) and natural plagioclases of different Ca contents is investigated, covering ranges of [M3+] (52 nM–10 μM), solid-liquid ratios (1–3 g/L), pH (3–9), and ionic strengths (0.01–0.1 M NaCl) under both ambient and CO2-free conditions. The zeta potential shows an unusual increase and charge reversal between pH 4 and 7 with increasing amount of Ca and Al in the feldspar crystal lattice, which is likely connected to adsorption and/or surface precipitation of dissolved Al3+. Streaming potential measurements yield (de)protonation constants for anorthite surface sites of log K- = -6.94 ± 0.38 and log K+ = +6.84 ± 0.38. Batch sorption data shows strong immobilization of M3+ by plagioclases at mildly acidic and basic pH. Time-resolved laser fluorescence spectroscopy using Cm indicates the formation of an inner-sphere complex and its two hydrolyzed forms. The complex reactivity of dissolved Al3+ at the plagioclase-water interface severely complicated the development of a surface complexation model, emphasizing the need for additional research in this area.

summary of metallurgical processes commonly used in the industry from sulfide concentrates to the metal products; based on this, the current technological approaches and emerging challenges in the metal recovery from marine sources will be discussed

Next-generation Radioimmunotherapy using CAR T Cells Combined with Photon vs. Proton vs. Carbon Irradiation

Bone marrow mesenchymal stromal cells (MSCs) have been described as potent regulators of T cell function, though whether they could impede the effectiveness of immunotherapy against acute myeloid leukemia (AML) is still under investigation. We examine whether they could interfere with the activity of leukemia-specific clonal cytotoxic T lymphocytes (CTLs) and chimeric antigen receptor (CAR) T cells, as well as whether the immunomodulatory properties of MSCs could be associated with the induction of T cell senescence. Co-cultures of leukemia-associated Wilm’s tumour protein 1 (WT1)- and Tyrosine-protein kinase transmembrane receptor 1 (ROR1)-reactive CTLs and of CD123-redirected switchable CAR T cells were prepared in the presence of MSCs and assessed for cytotoxic potential, cytokine secretion and proliferation. T cell senescence within functional memory sub-compartments was investigated for the senescence-associated phenotype CD28-CD57+ using unmodified peripheral blood mononuclear cells (PBMCs). We describe inhibition of expansion of AML-redirected switchable CAR T cells by MSCs via indoleamine 2,3-dioxygenase 1 (IDO-1) activity, as well as reduction of interferon gamma (IFNγ) and interleukin 2 (IL-2) release. In addition, MSCs interfered with the secretory potential of leukemia-associated WT1- and ROR1-targeting CTL clones, inhibiting the release of IFNγ, tumour necrosis factor alpha (TNFα), and IL-2. Abrogated T cells were shown to retain their cytolytic activity. Moreover, we demonstrate induction of a CD28loCD27loCD57+KLRG1+ senescent T cell phenotype by MSCs. In summary, we show that MSCs are potent modulators of anti-leukemic T cells, and targeting their modes of action would likely be beneficial in a combinatorial approach with AML-directed immunotherapy.

In recent years, several studies have been conducted to improve the process steps of rare earth elements (REEs) production. Beneficiation & separation stages varies according to type and concentration of impurities. One of the most complex process can be the selective separation of rare earth elements from each other due to their similar physical and chemical properties. At industrial scale,msolvent extraction is the most common separation and enrichment technology for REEs.
The efficiency of solvent extraction depends on several factors. The selection of extractant strongly depends on the composition of the leachate. In sulphate media, carboxylic acids are preferred because of their high extraction rates. Furthermore, primary amines can be used for extraction of rare earths in sulphate media. In amine system, extraction follows a reverse order comparing to cationic extractants.
In the presented study, primary amine Primene 81-R was selected as an alternative extractant in order to investigate its potential for a highly selective separation of REEs. The separation of HREEs from LREEs was determined in dependence on pH and concentration of the extractant using a model solution consisting mainly of LREES (97% of the total REE content). In the extraction experiment, approximately 40-50% of LREE were extracted into the organic phase, while the extraction of HREEs was obtained to be only between 5-30% under these conditions. However, for further development of the solvent extraction process, optimization studies are ongoing.

A brief summary of user operation experiences with SRF-Gun II at ELBE (since 2014) with an emphasis on most recent results and an oulook.

An update on activities of ELBE SRF-Gun group

Spin systems with honeycomb structures have recently attracted a great deal of attention in connection with the Kitaev quantum spin liquid state (QSL) predicted theoretically. One possible Kitaev QSL candidate is Na₂Co₂TeO₆ realizing a honeycomb lattice of pseudospin 1/2. Field-dependent single-crystal neutron diffraction technique allows us to determine the microscopic spin-spin correlations across the field-induced phase transitions for H II a and H II a∗ in plane field directions. Our results reveal phase transitions, initially to a canted zigzag antiferromagnetic state at approximately 60 kOe, followed by a possible transition to a partially polarized state over the range 90–120 kOe, and finally to a field-induced fully polarized state above 120 kOe. We observe distinct field dependencies of the magnetic peak intensities for H II a and H II a∗. In addition, low-temperature electron spin resonance in magnetic fields H _ c yields a complete softening for one of the antiferromagnetic resonances at ∼40 kOe, revealing a field-induced phase transition. The present work thus provides insights into the field evolution of the important Kitaev-Heisenberg spin system Na₂Co₂TeO₆.

The dwindling agricultural earnings and decrease in crop yield in recent years due to improper crop selection and fluctuation/ uncertainty in weather necessitate proper machine learning-based analysis. Machine learning methods can potentially alleviate the predicament caused by the lack of appropriate soil testing, consultation, and bias in manual suggestion. This work attempted to comprehend the agricultural sensor data and weather conditions and formulated the task in terms of supervised classification. The work obtained accurate suggestions in the presence of missing data, noise, etc. by using advanced machine learning methods. But recommendation alone is insufficient to convince farmers and other stakeholders to adopt this approach. Hence, this paper introduced explainable machine learning to completely comprehend the decision-making process. This work quantified the importance of features, explained individual prediction outcomes, and uncovered the rationale for decisions. The work employed state-of-the-art local interpretable model-agnostic, post-hoc explanation methods to provide in-depth insights. The insights obtained from the explanations can help the farmers develop a knowledge base and assist the farmers in choosing the appropriate sensors for the task. The human interpretable analysis enables the farmers to obtain satisfactory yields in these ever-changing and extreme weather conditions and environmental degradation.

We report the experimental observation of dielectric relaxation by quantum critical magnons. Complex capacitance measurements reveal a dissipative feature with a temperature-dependent amplitude due to lowenergy lattice excitations and an activation behavior of the relaxation time. The activation energy softens close to a field-tuned magnetic quantum critical point at H = H_c and follows single-magnon energy for H > H_c, showing its magnetic origin. Our study demonstrates the electrical activity of coupled low-energy spin and lattice excitations, an example of quantum multiferroic behavior.

Doping allows us to modify semiconductor materials for desired electrical, optical and magnetic properties. The solubility limit is a fundamental barrier for dopants incorporated into a specific semiconductor. Hyperdoping refers to doping a semiconductor much beyond the corresponding solid solubility limit and often results in exotic properties. For example, B hyperdoped diamond reveals superconductivity and Mn hyperdoped GaAs represents a typical ferromagnetic semiconductor. Ion implantation followed by annealing is a well-established method to dope Si and Ge. This approach has been maturely integrated with the IC industry production line. However, being applied to hyperdoping, the annealing duration has to be shortened to millisecond or even nanosecond. The intrinsic physical parameters related to dopants and semiconductors (e.g. Solubility, diffusivity, melting point and thermal conductivity) have to be considered to choose the right annealing time regime. In this talk, we propose that ion implantation combined with flash lamp annealing in millisecond and pulsed laser melting in nanosecond can be a versatile approach to fabricate hyperdoped semiconductors. The examples include magnetic semiconductors [1-5] and chalcogen doped Si [6-10].

[1] M. Khalid, et al., Phys. Rev. B 89, 121301(R) (2014).

[2] S. Zhou, J. Phys. D: Appl. Phys. 48, 263001(2015).

[3] S. Prucnal, et al., Phys. Rev. B 92, 222407 (2015).

[4] Y. Yuan, et al., ACS Appl. Mater. Interfaces, 8, 3912 (2016).

[5] Y. Yuan, et al., Phys. Rev. Mater. 1, 054401 (2017).

[6] S. Zhou, et al., Sci. Reports 5, 8329(2015).

[7] M. Wang, et al., Phys. Rev. Applied. 10, 024054 (2018).

[8] M. Wang, et al., Phys. Rev. Applied. 11, 054039 (2019).

[9] M. Wang, et al., Phys. Rev. B 102, 085204 (2020)

[10] M. Wang, et al., Adv. Optical Mater. 9, 2001546 (2021).

Ion implantation followed by thermal annealing is a well-established method to dope semiconductors, e.g. Si and Ge. This approach has been maturely integrated with the integrated circuit (IC) industry production line for area- and depth-selective n/p doping as well as for lifetime engineering [1]. As a national lab in Germany, our center is running an Ion Beam Center for materials research [2]. It is open free to the international community for fundamental research based on a proposal system. Within the research department “Semiconductor Materials”, we are running unique annealing methods, including millisecond flash lamp annealing and nanosecond pulsed laser melting, to repair the ion beam induced damage and to activate the dopants [3, 4]. I will show diverse research examples by using ion beam to modify semiconductor materials. They include pushing the doping limits in semiconductors well above the solubility limits [5-7], functionalizing 2D materials [8] and creating color centers for quantum technologies [9, 10].

[1] Ye Yuan, S. Zhou and X. Wang, Modulating properties by light ion irradiation: From novel functional materials to semiconductor power devices, J. Semicond. 43 063101 (2022).
[2] https://www.hzdr.de/db/Cms?pNid=1984
[3] S. Zhou, Dilute ferromagnetic semiconductors prepared by the combination of ion implantation with pulse laser melting, J. Phys. D: Appl. Phys. 48, 263001 (2015) (Topical Review)
[4] L. Rebohle, S. Prucnal, Y. Berencén, V. Begeza, S. Zhou, A snapshot review on flash lamp annealing of semiconductor materials, MRS Advances 7, 1301–1309 (2022)
[5] M. Wang et al, Breaking the doping limit in silicon by deep impurities, Phys. Rev. Appl. 11, 054039 (2019)
[6] S. Prucnal, et al., Dissolution of donor-vacancy clusters in heavily doped n-type germanium, New J. Phys. 22, 123036 (2020)
[7] M. Hoesch, Active sites of Te-hyperdoped silicon by hard x-ray photoelectron spectroscopy, Appl. Phys. Lett. 122, 252108 (2023)
[8] F. Long, Ferromagnetic interlayer coupling in CrSBr crystals irradiated by ions, arXiv:2305.18791 (2023)
[9] C. Kasper, et al, Influence of irradiation on defect spin coherence in silicon carbide, Phys. Rev. Appl. 13, 044054 (2020)
[10] Z. Shang, et al, Microwave-assisted spectroscopy of vacancy-related spin centers in hexagonal SiC, Phys. Rev. Appl. 15, 034059 (2021)

Ion implantation followed by thermal annealing is a well-established method to dope semiconductors, e.g. Si and Ge. This approach has been maturely integrated with the integrated circuit (IC) industry production line for area- and depth-selective n/p doping as well as for lifetime engineering [1]. As a national lab in Germany, our center is running an Ion Beam Center for materials research [2]. It is open free to the international community for fundamental research based on a proposal system. With my research department “Semiconductor Materials”, we are running unique annealing methods, including millisecond flash lamp annealing and nanosecond pulsed laser melting, to repair the ion beam induced damage and to activate the dopants [3, 4]. I will show diverse research examples by using ion beam. They include pushing the doping limits in semiconductors well above the solubility limits [5-7], functionalizing 2D materials [8] and creating color centers for quantum technologies [9, 10].

[1] Ye Yuan, S. Zhou and X. Wang, Modulating properties by light ion irradiation: From novel functional materials to semiconductor power devices, J. Semicond. 43 063101 (2022).
[2] https://www.hzdr.de/db/Cms?pNid=1984
[3] S. Zhou, Dilute ferromagnetic semiconductors prepared by the combination of ion implantation with pulse laser melting, J. Phys. D: Appl. Phys. 48, 263001 (2015) (Topical Review)
[4] L. Rebohle, S. Prucnal, Y. Berencén, V. Begeza, S. Zhou, A snapshot review on flash lamp annealing of semiconductor materials, MRS Advances 7, 1301–1309 (2022)
[5] M. Wang et al, Breaking the doping limit in silicon by deep impurities, Phys. Rev. Appl. 11, 054039 (2019)
[6] S. Prucnal, et al., Dissolution of donor-vacancy clusters in heavily doped n-type germanium, New J. Phys. 22, 123036 (2020)
[7] M. Hoesch, Active sites of Te-hyperdoped silicon by hard x-ray photoelectron spectroscopy, Appl. Phys. Lett. 122, 252108 (2023)
[8] F. Long, Ferromagnetic interlayer coupling in CrSBr crystals irradiated by ions, arXiv:2305.18791 (2023)
[9] C. Kasper, et al, Influence of irradiation on defect spin coherence in silicon carbide, Phys. Rev. Appl. 13, 044054 (2020)
[10] Z. Shang, et al, Microwave-assisted spectroscopy of vacancy-related spin centers in hexagonal SiC, Phys. Rev. Appl. 15, 034059 (2021)

Tellurium is one of the deep-level impurities in Si, leading to states of 200-400 meV below the conduction band. Non-equilibrium methods allow for doping deep-level impurities in Si well above the solubility limit, referred as hyperdoping, that can result in exotic properties, such as extrinsic photo-absorption well below the Si bandgap [1]. In this talk, we will present an overview about Te hyperdoped Si. The hyperdoping is realized by ion implantation and pulsed laser melting. We will present the resulting optical, electrical properties and the perspective applications as infrared photodetectors. With increasing the Te concentration, the samples undergo an insulator to metal transition [2, 3]. Surprisingly, the electron concentration obtained in Te-hyperdoped Si is approaching 1021 cm-3 and does not show saturation [4]. It is even high than that of P or As doped Si and potentially meets the criteria of source/drain applications in future nanoelectronics. The infrared optical absorptance is found to increase with increasing dopant concentration [2]. We demonstrate the room-temperature operation of a mid-infrared photodetector based on Te-hyperdoped Si. The key parameters, such as the detectivity, the bandwidth and the rise/fall time, show competitiveness with the commercial products [5]. To understand the microscopic picture, we have performed Rutherford backscattering angular scans and first-principles calculations [4]. The Te-dimer complex sitting on adjacent Si lattice sites has the smallest formation energy and is thus the preferred configuration at high doping concentration. Those substitutional Te-dimers are effective donors, leading to the insulator-to-metal transition, the non-saturating carrier concentration as well as the sub-band photoresponse. Moreover, the Te-hyperdoped Si layers exhibit thermal stability up to 400 °C with a duration of at least 10 minutes [6]. Therefore, Te-hyperdoped Si presents a test-bed for electrical and optical applications utilizing deep-level impurities.
[1] J. M. Warrender, Laser hyperdoping silicon for enhanced infrared optoelectronic properties, Appl. Phys. Rev. 3, 031104 (2016).
[2] M. Wang, et al., Extended Infrared Photoresponse in Te-Hyperdoped Si at Room Temperature, Phys. Rev. Appl. 10, 024054 (2018).
[3] M. Wang, et al., Critical behavior of the insulator-to-metal transition in Te-hyperdoped Si, Phys. Rev. B 102, 085204 (2020).
[4] M. Wang, et al., Breaking the doping limit in silicon by deep impurities, Phys. Rev. Appl. 11, 054039 (2019).
[5] M. Wang, et al., Silicon-Based Intermediate-Band Infrared Photodetector Realized by Te Hyperdoping, Adv. Opt. Mater. 9, 2001546, (2020).
[6] M. Wang, et al., Thermal stability of Te-hyperdoped Si: Atomic-scale correlation of the structural, electrical, and optical properties, Phys. Rev. Mater. 3, 044606 (2019).

Complex oxides host a multitude of novel phenomena in condensed matter physics, such as various forms of multiferroicity, colossal magnetoresistance, quantum magnetism, and superconductivity. This is largely due to the strong correlation between charge, spin, orbital, and lattice parameters. Specifically, tilting the delicate energy balance in lattice interactions and kinetics, achieved by temperature, strain, or chemical doping, can result in significant modifications in these materials. In this context, defect engineering by ion irradiation, which can introduce strain and electronic disorder, has emerged as a powerful technique to fine-tune complex phases of oxide thin films. The induced uniaxial strain, manifested as the elongation of the out-of-plane lattice spacing, is not limited to available substrates, the conventional and well-known strain engineering approach. In this contribution, we will introduce the tailoring of oxide thin films by ion irradiation, with examples including the modification of magnetic and magneto-transport properties of NiCo2O4 [1] and SrRuO3 [2,3], and ferroelectric properties of BiFeO3, KTN (KTaNbO3), and PbZrO3 [4-6]. The irradiated SrRuO3 films exhibit a pronounced topological Hall effect in a wide temperature range from 5 to 80 K, which can be attributed to the emergence of Dzyaloshinskii–Moriya interaction resulting from artificial inversion symmetry breaking associated with lattice defect engineering. In BiFeO3, we have obtained a super-tetragonal phase with the largest c/a ratio (~1.3) ever experimentally achieved [2]. For both KTN and PbZrO3, ion irradiation induces the formation of polar nanoregions [5, 7]. In PbZrO3, both the energy storage density and the breakdown strength are effectively increased. We show that ion irradiation is a very versatile pathway for tailoring oxide functionalities, analogous to ion-implantation doping for conventional semiconductors. It is worth noting that ion beam technology has been well-developed for microelectronics. Once the principle of concept is approved, the approach can be easily scaled up and integrated into the industry production line.
References:
[1] P. Pandey, et al., APL Materials 6 (2018) 066109.
[2] C. Wang, et al., ACS Appl. Mater. Interfaces 10 (2018) 27472.
[3] C. Wang, et al., Adv. Electron. Mater. 6 (2020) 2000184.
[4] C. Chen, et al., Nanoscale 11 (2019) 8110.
[5] Q. Yang, et al., Acta Mater. 221 (2021) 117376.
[6] Y. Luo, et al, Appl. Phys. Rev. 10 (2023) 011403.

Attrition of employees is vital for any organization as it significantly influences productivity and hampers the long-term growth strategies of the organization. Since employee attrition leads to loss of skills and experiences any organization always try to find a way to retain their employees to reduce training and recruiting cost as well as to achieve their business goal smoothly. Machine learning approaches, which predict the possibility of attrition based on the employee attributes avoid the tedious, and biased manual prediction, and help the organization take preventive measures. This paper presents a framework for attrition prediction that emphasizes imbalance classification and the adoption of genetic algorithms to optimize the model. First, we have adopted different oversampling methods like Synthetic Minority Over-sampling Technique (SMOTE), Adaptive Synthetic (ADASYN), and Borderline Synthetic Minority Over-sampling Technique to balance our data set. We have used XGBoost classifiers for classification with the data that are obtained from different over-sampling techniques. As the XGBoost classifier has many hyperparameter a genetic algorithm is used to optimize our model where the accuracy is chosen as the fitness function. The comparative performance analysis of different over-sampling methods as well as hyper-parameter tuning (Amongst Genetic algorithm, GridSearchCV, and with the default value of different hyper-parameter) on the real dataset suggests that SMOTE for oversampling techniques and genetic algorithm for optimization attains improved performance.

The hyperspectral unmixing process is central to identifying the objects in a ground scene and quantifying their fractional abundance in each pixel. However, the high spatial resolution and the intrinsic interactions pose a challenge in object identification from hyperspectral images by non-linear unmixing. Typically the data points are generated due to non-linear, intimate mixing from non-linear subspaces. In this work, we propose a deep subspace clustering framework to identify the underlying non-linear subspaces in the initial stage and perform non-linear unmixing on the local clusters. To this aim, we proposed a deep auto-encoder network with additional total variation and spatial consistency regularization to determine the underlying non-linear mixing process from each cluster separately. Next, we identify the pixels which contain a dominant source from the latent representation obtained after the encoding stage. Subsequently, we carried out unmixing on local clusters using a linear algebraic based on the low-rank structure of the data. A detailed comparative analysis of the unmixing algorithms on three real hyperspectral images exhibits that our proposed algorithm achieves improved performance.

FET PET is a valuable tool for managing brain tumors. Quantitative image analysis is of obvious relevance in this context. One clinically useful image derived measure is the maximal tumor-to-background SUV ratio which can be used for therapy response assessment as well
as for discrimination between tumor recurrence and treatment-related changes. Computation of this ratio requires determination of the background SUV (bSUV) from a suitable ROI defined within healthy brain tissue. Currently, the standard procedure requires manual definition of the background ROI by an experienced human observer while adhering to a set of somewhat loosely defined rules. This process is time consuming and prone to inter- and intra-observer variability. The goal of this study, therefore, was development of a reliable automated method for bSUV derivation in FET PET of brain tumor patients.

Automated delineation of the healthy brain regions was performed with a residual 3D U-Net convolutional neural network (CNN). 561 FET PET scans were used for network training (N=448) and testing (N=113). In these data, reference brain regions were manually delineated by an experienced observer. The network was trained to reproduce the corresponding manual bSUVs by identifying a suitable brain ROI (rather than aiming at reproducing the manual ROI delineation). Performance of the trained network model was assessed in the test data using the fractional difference between automatically and manually derived bSUVs.

The trained U-Net was able to accurately reproduce the manually derived bSUVs in the test data: the fractional bSUV difference was (mean +/- SD)=(-0.9 +/- 5.3)% with a 95% confidence interval of [-10.9, 8.4]%.

The achieved concordance of the network's results with the given ground truth bSUV is in line with typical achievable levels of inter- and intra-observer concordance for this task. It thus might be considered for supervised routine use to reduce user workload and improve reproducibility.

Eine für die numerische Simulation von Strömungen sehr beliebte und erfolgreiche Software ist die quelloffene Software der OpenFOAM Foundation, welche sowohl in der Industrie als auch im akademischen Umfeld Anwendung findet. Forschungsgruppen, die keine reine Inhouse-Entwicklung leisten können oder anstreben, gewährt sie eine optimale Basis um eigene Ideen und Konzepte in einer transparenten Umgebung effizient testen zu können. Obwohl der Wartungsaufwand im Vergleich zu einer Eigenentwicklung insgesamt erheblich geringer ist, müssen Erweiterungen dennoch gepflegt werden um diese mit dem jeweils aktuellen Stand des Hauptrelease kompatibel zu halten. Die damit verbundene Arbeit erlangt umso größere Bedeutung, wenn Erweiterungen im Sinne der FAIR-Prinzipien zusammen mit wissenschaftlichen Publikationen bereitgestellt werden. Als agil entwickelte und intensiv gewartete Software stellt die Software der OpenFOAM Foundation in dieser Hinsicht besondere Anforderungen an die nachgelagerten Entwickler.
Das Helmholtz-Zentrum Dresden – Rossendorf e.V. (HZDR) verfolgt hierbei einen möglichst nachhaltigen Ansatz. Abgeschlossene und zitierfähige Entwicklungen werden entweder in einer eigenen Softwarepublikation veröffentlicht, oder, in enger Abstimmung mit den Kernentwicklern der OpenFOAM Foundation, in das Hauptrelease integriert. Die für die Arbeit an der Erweiterung (Multiphase Code Repository by HZDR for OpenFOAM Foundation Software) geschaffene IT-Infrastruktur zeichnet sich durch einen hohen Automatisierungsgrad aus und bietet Anwendern innerhalb und außerhalb des HZDR eine nützliche Plattform für die Erforschung von numerischen Methoden und Modellen.
Rückgrat der Arbeiten ist die über die Helmholtz Cloud bereitgestellte GitLab-Instanz (Helmholtz Codebase). Darin werden zwei Repositorien gepflegt: Eines für die Codeerweiterung und eines für Setups zur Simulation konkreter Anwendungen (Multiphase Cases Repository by HZDR for OpenFOAM Foundation Software). Zur Sicherung der Qualität und Funktionalität wird die Arbeit in der GitLab-Umgebung von Continuous-Integration-Pipelines (CI) begleitet, in deren Rahmen unter anderem statische Code-Checks, Build-Tests und Testläufe automatisiert vorgenommen werden. Für die Verwendung in CI-Pipelines sowie die lokale Entwicklung der Erweiterung wird die Installation als Container (Docker) bereitgestellt. Reine Anwender können auf die Installation per Debian-Paket zurückgreifen. Die zitierfähige Veröffentlichung des Quellcodes erfolgt mit jeder wissenschaftlichen Publikation im Rossendorf Data Repository (RODARE). Die Verwendung des Workflowmanagementsystems Snakemake ermöglicht skalierbare Validierungsläufe. Um die Portierbarkeit der Entwicklungen zu verbessern konzentrieren sich jüngere Arbeiten auf die Bereitstellung der Software als HPC-Container (Apptainer) für die Anwendung auf Hochleistungsrechnern. Dieser Beitrag gibt einen Überblick über die genannten Elemente der Umgebung und deren Zusammenspiel.

Because of its high interfacial area density and mixing efficiency bubbly flow are utilized in diverse technical applications to enhance the interfacial mass and heat transfer rate. However, due to the superposition of complex shape variation as well as bubble-bubble interaction, many aspects concerning the effect of bubbles on the bulk flow remain unclear, and bubble-induced turbulence (BIT) is one of them. In the past great effort has been made towards the BIT modelling in the framework of two-equation turbulence models, but the understanding of physics is still far from satisfactory. This work revisits the model proposed by Ma et al. [Phys. Rev. Fluids 2, 034301 (2017)], which considers the BIT with an additional source term in the k- and epsilon" (or omega)- equation, respectively, and has been widely adopted in the simulations of bubbly flows.
Recent experiments show that contamination of the carrier phase plays a considerable role in BIT: although the bubbles rise slower with adding surfactants, the BIT increases. This trend cannot be reproduced by any current BIT models, including Ma et al. (2017). We have further investigated the reason for this and discuss the new possibility for the prefactor in the source term of the "epsilon-equation that may improve the results.

Efficient compression is pertinent for the convenient storage, transmission, and processing of modern high-resolution hyperspectral images (HSI). This paper proposes a new high-performance HSI compression method using library-based spectral unmixing and tensor decomposition. Unlike the existing approaches, our proposed work incorporates unmixing in the compression framework and achieves significantly higher compression performance with negligible loss. The proposed library-based unmixing method includes a new index for accurate endmember number estimation, followed by exact library pruning and a novel sparsity regularized formulation with norm-smoothing to compute the abundance maps. As the spectral library is available at the reconstruction (decoder) side also; compressing the abundance maps is as good as compressing the original HSI data. Since the abundance constraints used for the unmixing indicate the correlation of the abundance maps, compressing all abundance maps seems to cause redundant computation. A metric using the image smoothness and information measures is used here to identify the abundance map hardest to compress and the remaining part is left uncompressed. Subsequently, the work compresses the abundance map tensor using orthogonal Parallel Factorisation (PARAFAC) decomposition with optimal rank determination. The orthogonalization process ensures that the factors span independent subspaces and reduces redundancy, while the rank selection prevents noisy or insignificant components. Extensive experiments are carried out to demonstrate that the unmixing workflow leads to negligible loss due to accurate endmember number estimation, exact library pruning, and accurate physically meaningful sparse inversion. Comparative assessments of compression efficacy suggest that the proposed work corresponds to better compression performance and higher classification accuracy.

In the past, many geochemical reference materials have been characterised either by the compilation of data published in the research literature, or by relatively informal ‘round-robin’ type of collaborative analysis programme. Neither approach complies with the most recent recommendations in ISO-REMCO Guide 35:2017. In order to develop a more rigorous approach that would lead to the full certification of such materials, Potts et al. (2019) published a certification protocol based on the well established GeoPT proficiency testing programme designed for laboratories that routinely analyse silicate rocks and related materials. In developing this certification protocol, a full assessment of compliance with the most recent version of ISO-REMCO Guide 35 was undertaken.
This protocol has now been applied to the certification of a leucomonzogranite (GMN-1), based on round 51 of the GeoPT programme that included participation by 112 laboratories from 43 countries. This exercise has led to the certification of 9 major and 39 trace elements.
In the development of this protocol, a number of issues remain that are not fully resolved in Guide 35. One is the potential clash between the requirements of proficiency testing in relation to procedures recommended for certification, perhaps the most important being the way in which well characterized consensus values derived from an assessment of data contributed to the proficiency testing programme effectively demonstrate the property of traceability.

Potts P J, Webb P C and Thompson M (2019). The GeoPT proficiency testing programme as a scheme for the certification of geological reference materials. Geostandards and Geoanalytical Research, 43, 409-418, doi: 10.1111/ggr.12261.

Nuclear energy is a crucial source of energy supply worldwide and is essential for achieving carbon neutrality. This is particularly true for advanced nuclear energy systems. In these systems, the complexity of flow and the efficiency and stability of heat transfer present ongoing challenges that necessitate further research efforts. In this specialized issue entitled "Complex Flow and Heat Transfer in Advanced Nuclear Energy Systems", a collection of related research works, including experimental research and numerical simulation works were gathered.Li Yong and colleagues conducted research focusing on condensation and acoustic characteristics of steam condensation. They experimentally studied the complex twophase flow regimes and acoustic characteristics of direct contact condensation when steam is injected into water.Mengmeng Liu, et al. carried out numerical simulations on heat transfer of supercritical pressure water in a helical tube. This process occurs in a supercritical steam generator, which may potentially be used for future high-temperature gas-cooled reactors.In the research carried out by Ji Wang, et al., an intriguing method was intruded to study

Curvilinear magnetism is a framework, which helps understanding the impact of geometrical curvature on complex magnetic responses of curved 1D wires and 2D shells [1,2]. In this talk, we will address fundamentals of curvature-induced effects in magnetism and review current application scenarios. In particular, we will demonstrate that curvature allows tailoring fundamental anisotropic and chiral magnetic interactions and enables fundamentally new nonlocal chiral symmetry breaking effect [3], which is responsible for the coexistence and coupling of multiple magnetochiral properties within the same magnetic object [4]. We will discuss the application potential of geometrically curved magnetic thin films as mechanically reshapeable magnetic field sensors for automotive applications, memory, spin-wave filters, high-speed racetrack memory devices, magnetic soft robotics as well as on-skin interactive electronics.
[1] D. Makarov et al., Curvilinear micromagnetism: from fundamentals to applications (Springer, Zurich, 2022).
[2] D. Makarov et al., New dimension in magnetism and superconductivity: 3D and curvilinear nanoarchitectures. Adv. Mat. 34, 2101758 (2022).
[3] D. D. Sheka et al., Nonlocal chiral symmetry breaking in curvilinear magnetic shells. Comm. Phys. 3, 128 (2020).
[4] O. M. Volkov et al., Chirality coupling in topological magnetic textures with multiple magnetochiral parameters. Nat. Comm. 14, 1491 (2023).

Curvilinear magnetism is a framework, which helps understanding the impact of geometric curvature on complex magnetic responses of curved 1D wires and 2D shells [1-3]. The lack of the inversion symmetry and the emergence of a curvature induced anisotropy and Dzyaloshinskii-Moriya interaction (DMI) stemming from the exchange interaction [4,5] are characteristic of curved surfaces. Magnetochiral responses of any curvilinear magnetic nanosystem are governed by the mesoscale DMI [6], which is determined via both the material and geometric parameters and governs the stabilization of skyrmion and skyrmionium states as well as skyrmion lattices [7-9]. Recently, a novel nonlocal chiral symmetry breaking effect was discovered in curvilinear magnetic nanoshells [10], which is responsible for the coexistence and coupling of multiple magnetochiral properties within the same magnetic object [11].
The field of curvilinear magnetism is extended towards curvilinear antiferromagnets. Pylypovskyi et al. demonstrated that intrinsically achiral one-dimensional curvilinear antiferromagnets behave as a chiral helimagnet with geometrically tunable DMI, orientation of the Neel vector and the helimagnetic phase transition [12-14]. This positions curvilinear antiferromagnets as a novel platform for the realization of geometrically tunable chiral antiferromagnets for antiferromagnetic spinorbitronics.
Application potential of geometrically curved magnetic architectures is explored as memory, spin-wave filters, high-speed racetrack memory devices as well as mechanically reshapeable magnetic field sensors for automotive applications, soft robotics [15] on-skin interactive electronics relying on thin films [16,17] as well as printed magnetic composites [18] with appealing self-healing performance [19].
These fundamental discoveries and application-oriented activities will be covered in this tutorial.

[1] D. Makarov et al., Curvilinear micromagnetism: from fundamentals to applications (Springer, Zurich, 2022).
[2] D. Makarov et al., Advanced Materials (Review) 34, 2101758 (2022).
[3] D. D. Sheka et al., Small (Review) 18, 2105219 (2022).
[4] Y. Gaididei et al., Phys. Rev. Lett. 112, 257203 (2014).
[5] O. Volkov et al., Phys. Rev. Lett. 123, 077201 (2019).
[6] O. Volkov et al., Scientific Reports 8, 866 (2018).
[7] V. Kravchuk et al., Phys. Rev. B 94, 144402 (2016).
[8] V. Kravchuk et al., Phys. Rev. Lett. 120, 067201 (2018).
[9] O. Pylypovskyi et al., Phys. Rev. Appl. 10, 064057 (2018).
[10] D. Sheka et al., Communications Physics 3, 128 (2020).
[11] O. Volkov et al., Nature Communications 14, 1491 (2023).
[12] O. Pylypovskyi et al., Nano Letters 20, 8157 (2020).
[13] O. Pylypovskyi et al., Appl. Phys. Lett. 118, 182405 (2021).
[14] Y. A. Borysenko et al., Phys. Rev. B 106, 174426 (2022).
[15] M. Ha et al., Advanced Materials 33, 2008751 (2021).
[16] J. Ge et al., Nature Communications 10, 4405 (2019).
[17] G. S. Canon Bermudez et al., Nature Electronics 1, 589 (2018).
[18] M. Ha et al., Advanced Materials 33, 2005521 (2021).
[19] R. Xu et al., Nature Communications 13, 6587 (2022).

The Dresden Advanced Light Infrastructure is a future infrastructure under consideration at the Helmholtz-Zentrum Dresden-Rossendorf. In the current conceptional design phase, we are surveying different control system options. To benefit as much as possible from community experiences with different control systems, in 2023 a survey was conducted and participants from accelerator and light source facilities world-wide were invited. The results of that survey are presented and conclusions for our center are drawn.

In this manuscript, we will discuss the notion of curved momentum space, as it arises in the discussion of noncommutative or doubly special relativity theories.We will illustrate it with two simple examples, the Casimir effect in anti-Snyder space and the introduction of fermions in doubly special relativity.We will point out the existence of intriguing results, which suggest nontrivial connections with spectral geometry and Hopf algebras.

We review recent discussions regarding the parity-odd contribution to the trace anomaly of a chiral fermion. We pay special attention to the perturbative approach in terms of Feynman diagrams, comparing in detail the results obtained using dimensional regularization and the Breitenlohner–Maison prescription with other approaches.

We show that there exists a generalized, universal notion of the trace anomaly for theories which are not conformally invariant at the classical level. The definition is suitable for any regularization scheme and clearly states to what extent the classical equations of motion should be used, thus resolving existing controversies surrounding previous proposals. Additionally, we exhibit the link between our definition of the anomaly and the functional Jacobian arising from a Weyl transformation.

The Ruwai Pb-Zn-Ag skarn deposit is located within the Schwaner Mountain Complex in Central Kalimantan, Indonesia. It is the largest polymetallic skarn deposit in Kalimantan with the resources is estimated up to 14.43 Mt. at 4.94 wt.% Zn, 3.28 wt.% Pb, 108.11 g/t Ag which hosted by Jurassic limestones of the Ketapang Complex and Cretaceous granitoids of Sukadana Complex. In order to study the complex mineralogy and deportment of critical-elements (Ag, Bi, Sb, In, Te, Cd) pulp samples from the main stages of the processing plant (Ball mill/feed, Pb concentrate, Zn concentrate, Pb scavenger, Zn scavenger, Fe screw, and tailings) as well as 66 core samples of Pb-Zn-Ag mineralization were obtained.
Preliminary results on the pulp samples from X-ray diffraction (XRD), X-ray fluorescence (XRF) and mineral liberation analysis (MLA) agree within analytical uncertainties. The data allows a preliminary assessment of the deportment and distribution of Ag and Bi in the skarn ores and processing products. Particularly, acanthite (Ag2S) and freibergite ((Ag,Cu,Fe)12(Sb,As)4S13) are likely to be important hosts of Ag, while Bi occurs within bismuthinite (Bi2S3) and native bismuth (Bi). For the core samples, µ-XRF measurements of slabs have so far provided a broad overview of elemental distribution within the samples, while XRD results indicate more complex mineralogical compositions than the pulp samples.
Further analytical work including electron probe microanalysis (EPMA) and laser ablation ICP-MS are planned for all samples to be also able to evaluate the resource potential of other critical elements of interest such as Sb, In, Te, Cd.

The flow past a clean spherical bubble translating steadily parallel to a no-slip wall in a stagnant fluid is studied numerically over a wide range of moderate to high Reynolds numbers. We focus on situations where the distance separating the bubble from the wall is smaller than the size of the bubble in order to explore the competition between viscous and inertial effects in the gap. More precisely, the range of the wall distance considered is $1.1\leq \LR \leq 2$ ($\LR$ being the distance from the bubble center to the wall normalized by the bubble radius), and that of the Reynolds number is $50\leq \Rey \leq 1000$ ($\Rey$ being based on the bubble diameter and the slip velocity). In contrast to predictions based on potential flow theory, the numerical results reveal that, when the gap is smaller than a critical value that depends on the Reynolds number, the transverse force starts to decrease with decreasing separation and may finally reverse, changing from attractive to repulsive. This effect is found to be due to the strong shear generated in the gap, which, combined with the local transverse gradient of the streamwise velocity, results in a system of two counter-rotating streamwise vortices and, consequently, a shear-induced lift pointing away from the wall. Computational results together with available high-Reynolds-number theory provide empirical expressions for the drag and transverse forces in the steady-state limit. Then the competition between the various transverse forces on a bubble bouncing close to the wall is examined, based on previously measured data for bubble trajectory. The central role of the history effects due to the misalignment between the wake and the instantaneous angle of the bubble path is confirmed. Computational results also reveal that, depending on the initial separation, a freely moving bubble may either reach a stable equilibrium position close to the wall or depart from the wall up to infinity.

The Spremberg-Graustein-Schleife Kupferschiefer deposit is a sediment-hosted stratabound copper (SSC) deposit located in eastern Germany. The Cu mineralization occurs at depths of 980 to 1,580 m below surface, predominantly in a Permian carbon-rich black shale unit, commonly known as the Kupferschiefer. Mineralization is not only restricted to this unit and can extend into the overlying Zechstein carbonates, as well as the underlying Redbed sandstones. Recent studies have confirmed 91.7 Mt of inferred mineral resource at an average grade of 1.5% Cu and 24.0 g/t Ag.

In addition to Cu and Ag, elevated levels of Co, Ni, and Re are also found in Kupferschiefer ores. This contribution provides the first detailed evaluation of the mineralogy of the complete mineralization interval of the Spremberg-Graustein-Schleife deposit, including the mineralogical deportment of Cu. Mineral chemistry work constraining the deportments of Ag and Re is planned.

Fifty-three individual samples were collected from three drill cores. The samples were crushed, milled, and composited into 19 composite samples. These were then subjected to multi-element analytical methods (XRF, ICP-OES, ICP-MS) for bulk-ore geochemistry, X-ray diffractometry (XRD), and mineral liberation analysis (MLA) for mineralogy. Electron probe micro-analysis (EPMA) and laser ablation ICP-MS (LA-ICP-MS) for trace element geochemistry are currently planned. Mineralogical results reveal that major Cu-bearing minerals vary both spatially between the three different drill cores and vertically between lithological units. For example, chalcocite and covellite (and to a lesser extent bornite) are the dominant carriers of Cu in the most mineralized core (80% of contained Cu), whereas chalcopyrite is the most prominent carrier of Cu in the Pb-Zn Kupferschiefer facies (75% of contained Cu). By combining different analytical results, we aim to develop a quantitative predictive model to describe the mineralogical distribution of the copper and potential by-products that will be usable for mineral processing and mine-planning purposes

The sediment-hosted Spremberg-Graustein-Schleife deposit is located in Lusatia, eastern Germany. Mineralization occurs in the lower Zechstein units, extending from the Grauliegend conglomerates and sandstones into the overlying organic-rich Kupferschiefer black shales and Zechstein carbonates. Around 100 Mt of Cu-Ag ore is present within the deposit. The ore is also enriched in Pb, Zn, Co, Ni, Au, Bi, Se, Re, and Ge (in addition to Cu and Ag). Despite the metal endowment, detailed quantitative metal deportment studies have not been carried out for this deposit, or indeed any other Kupferschiefer deposit. This study aims to bridge the gap. Core samples representing the complete mineralization interval (31 m in total) at three different sites within the deposit were mineralogically and geochemically analyzed. To ensure a comprehensive, high-quality and internally consistent dataset, various analytical methods including X-ray fluorescence (XRF), ICP-OES, ICP-MS, X-ray diffraction (XRD), Mineral Liberation Analysis (MLA), electron probe micro-analysis (EPMA) and laser ablation ICP-MS (LA-ICP-MS) were performed. The results reveal that the concentration and main hosts of copper and potential by-products vary vertically between the stratigraphical units, and spatially at different locations of the deposit. Such information will eventually help to predict deportments across the deposit, track each element within the minerals processing plants and also to get an idea of expected recoveries and thus optimizing the procedure.

Orbital-free density functional theory constitutes a computationally highly effective tool for modeling electronic structures of systems ranging from room-temperature materials to warm dense matter. Its accuracy critically depends on the employed kinetic energy (KE) density functional, which has to be supplied as an external input. In this work we consider several nonlocal and Laplacian-level KE functionals and use an external harmonic perturbation to compute the static density response at T=0 K in the linear and beyond-linear response regimes. We test for the satisfaction of exact conditions in the limit of uniform densities and for how approximate KE functionals reproduce the density response of realistic materials (e.g., Al and Si) against the Kohn-Sham DFT reference, which employs the exact KE. The results illustrate that several functionals violate exact conditions in the uniform electron gas (UEG) limit. We find a strong correlation between the accuracy of the KE functionals in the UEG limit and in the strongly inhomogeneous case. This empirically demonstrates the importance of imposing the limit of UEG response for uniform densities and validates the use of the Lindhard function in the formulation of kernels for nonlocal functionals. This conclusion is substantiated by additional calculations for bulk aluminum (Al) with a face-centered cubic (fcc) lattice and silicon (Si) with an fcc lattice, body-centered cubic (bcc) lattice, and semiconducting crystal diamond state. The analysis of fcc Al, and fcc as well as bcc Si data follows closely the conclusions drawn for the UEG, allowing us to extend our conclusions to realistic systems that are subject to density inhomogeneities induced by ions.