Publikationsrepositorium - Helmholtz-Zentrum Dresden-Rossendorf

We present an atomically precise technique to create sulfur vacancies and control their atomic configurations in single-layer MoS2. It involves adsorbed Fe atoms and the tip of a scanning tunneling microscope, which enables single sulfur removal from the top sulfur layer at the initial position of Fe. Using scanning tunneling spectroscopy, we show that the STM tip can also induce two Jahn-Teller distorted states with reduced orbital symmetry in the sulfur vacancies. Density functional theory calculations rationalize our experimental results. Additionally, we provide evidence for molecule-like hybrid orbitals in artificially created sulfur vacancy dimers, which illustrates the potential of our technique for the development of extended defect lattices and tailored electronic band structures.

Electric fields operating at THz frequencies hold significant promise for inducing ultrafast coherent excitations in magnetic heterostructures. Through the utilization of ferromagnetic/heavy metal (FM/HM) heterostructures, we have demonstrated that THz radiation (0.1 – 30 THz) exhibits combined functionality of microwaves and visible light. 1) Similar to microwaves, THz fields can effectively generate spin currents through the spin-Hall effect (SHE), resulting in an excitation of THz-frequency magnon modes. 2) Akin to visible light excitation, THz fields deposit heat, leading to the demagnetization of FM layers. Harnessing the THz-induced demagnetization as a spin current source within FM/HM heterostructures, we exploit the half-cycle THz electric field to incite spin currents, which subsequently transformed into picosecond charge currents through the inverse SHE within the HM layer. This conversion process results in the emission of a THz second harmonic signal, offering the THz spintronic frequency conversion.

We will present our ongoing efforts to support physics research with
machine learning at HZDR. We will summarize our academic efforts in our
Young Investigator Group as well as the projects handled by our
consultant team. In this manner, we will highlight our approach to ML
based research and support at HZDR as well as the Helmholtz association
in Germany. In detail, our YIG is working on surrogate models for laser
and plasma physics problems, like laser wakefield acceleration,
providing fast estimates experimental or computational results to guide
parameter optimization or accelerate inverse parameter estimation and
ML-based approaches to solve inverse phase problems. In addition to this
aspects of trustworthiness and uncertainty play a key role in our work,
which are a specialty of our consultants team, also in connection with
further topics like segmentation and natural language processing.

I will introduce the Helmholtz-Zentrum Dresden-Rossendorf (HZDR) with its two accelerator-based THz sources, FELBE and TELBE [1]. Then I will discuss two examples of nonlinear spectroscopy of excitons: the first one is the observation of the Autler-Townes splitting of an intra-excitonic 1s-2p transition in InGaAs quantum wells, an experiment more than a decade old, but still one of my favorites [2]. The second deals with the very recent observation of the THz induced photodetachment of trions in the 2D material MoSe2, i.e. the conversion of a trion (a charged exciton) into an exciton plus an electron [3]. Finally I will discuss the shortcomings of our present THz facilities, leading to the ideas for a successor facility, the Dresden Advanced Light Infrastructure DALI.

[1] M. Helm et al., Eur. Phys. J. Plus 138, 158 (2023).
[2] M. Wagner et al., Phys. Rev. Lett. 105, 167401 (2010); M. Teich et al., New J. Phys. 15, 065007 (2013); M. Teich et al., Phys. Rev. B 89, 115311 (2014).
[3] T. Venanzi et al., Nature Photonics, accepted for publication (2024).

A personal journey through four decades of THz sources, or how I didn’t invent the QCL

The ESFR SMART project, which took place from 2017 to 2022, made it possible to define a Sodium Fast Reactor (SFR) design based on past SFR experimental feedbacks and intended to meet post-Fukushima safety criteria. The main options retained are recalled here: a heterogeneous core with low sodium void reactivity effect and mitigation measures (corium transfer tubes), a sodiumresistant pit well, a metallic thick slab, and finally comprehensive set of measures allowing decay heat removal by natural convection. These studies were carried out during this project with a power of 3600 MWth which was the power of the initial EFR project initiated during the operation of Superphenix. The new ESFR-SIMPLE project, starting at the end of 2022, uses the same technical options but with reduced power. This choice could more easily allow the construction of a SFR prototype in Europe. Design options were chosen so that the reactor could be assembled off-site, then shipped by rail or ship to the construction site, which requires a vessel diameter limit of around 10 m. The paper presents the first design studies with a particular attention to the core and primary circuit sizing. The proposed ESFR-SMR results in a 360 MWth reactor. This power reduction may also allow some simplifications compared to the initial high-power concept, particularly in terms of passive evacuation of residual power. This last point will be more deeply investigated by the ESFRSIMPLE project in the next years

The current ESFR (European Sodium Fast Reactor) design was proposed and in-depth evaluated in the frame of the past ESFR-SMART project. As a follow-up project, the ESFRSIMPLE has been launched with the aim of challenging the current commercial-size ESFR design in terms of safety features and economic performance. Among the new safety measures to be developed and assessed in ESFR-SIMPLE, the current oxide fuel ESFR design will be challenged by a modified version of the core with metallic fuel. This intends to conclude on what types of benefits can be obtained with high-density fuel, under similar safety and design constraints. In this paper, the designing approach for enabling the use of metallic fuel in the current ESFR core is described and a preliminary neutronic evaluation is carried out. The optimal configuration is established through the optimization of key neutronic parameters aiming at the potential reduction of the plutonium inventory. The resulting core configuration serves as a basis for further safety assessment analyses, which will provide insight into the advantages and drawbacks of the two types of fuels.

This repository contains the modules developed as part of Data Science Education Community of Practice program of the American Physical Society. These open source modules are to be used for incorporating machine learning/data science concepts in undergraduate physics curriculum.

Surface terminations profoundly influence the intrinsic properties of MXenes, but existing terminations are limited to monoatomic layers or simple groups, showing disordered arrangements and inferior stability. Here we present the synthesis of MXenes with triatomic-layer borate polyanion terminations (OBO terminations) through a flux-assisted eutectic molten etching approach. During the synthesis, Lewis acidic salts act as the etching agent to obtain the MXene backbone, while borax generates BO2− species, which cap the MXene surface with an O–B–O configuration. In contrast to conventional chlorine/oxygen-terminated Nb2C with localized charge transport, OBO-terminated Nb2C features band transport described by the Drude model, exhibiting a 15-fold increase in electrical conductivity and a 10-fold improvement in charge mobility at the d.c. limit. This transition is attributed to surface ordering that effectively mitigates charge carrier backscattering and trapping. Additionally, OBO terminations provide Ti3C2 MXene with substantially enriched Li+-hosting sites and thereby a large charge-storage capacity of 420 mAh g−1. Our findings illustrate the potential of intricate termination configurations in MXenes and their applications for (opto)electronics and energy storage.

In the ever-expanding landscape of data management, navigating the diverse array of metadata catalogs such as SciCat, data publications on Invenio derivatives, and internal archives presents a formidable challenge. However, with the right strategies, this mosaic of data can be effectively combined and represented to unlock its full potential. In this talk, we delve into the intricacies of data fusion, exploring innovative approaches to harmonize metadata catalogs, data publications, and archives seamlessly.

We will discuss the importance of interoperability and standardization in facilitating the integration process, enabling disparate data sources to coalesce into a cohesive ecosystem. Through conceptional examples and case studies, we will provide insights into the practical application of strategies.

Optical femtosecond pump-probe experiments allow to measure the dynamics of ultrafast heating of metals with high accuracy. However, the theoretical analysis of such experiments is often complicated because of the indirect connection of the measured signal and the desired temperature transients. Establishing such a connection requires an accurate model of the optical constants of a metal, depending on both the electron temperature Te and the lattice temperature Tl. In this paper, we present first-principles simulations of the two-temperature scenario with Te ≫ Tl, showing the optical response of hot electrons to laser irradiation in gold and ruthenium. Comparing our simulations with the Kubo-Greenwood approach, we discuss the influence of electron-phonon and electron-electron scattering on the intraband contribution to optical constants. Applying the simulated optical constants to the analysis of ultrafast heating of ruthenium thin films we highlight the importance of the latter scattering channel to understand the measured heating dynamics.

The interaction of energetic electrons with the specimen during imaging in a transmission electron microscope (TEM) can give rise to the formation of defects or even complete destruction of the sample. This is particularly relevant to atomically thin two-dimensional (2D) materials. Depending on electron energy and material type, different mechanisms such as knock-on (ballistic) damage, inelastic interactions including ionization and excitations, as well as beam-mediated chemical etching can govern defect production. Using first-principles calculations combined with the McKinley-Feshbach formalism, we investigate damage creation in two representative 2D materials, MoS2 and hexagonal boron nitride (hBN) with adsorbed single adatoms (H, C, N, O, etc.), which can originate from molecules always present in the TEM column. We assess the ballistic displacement threshold energies T for the host atoms in 2D materials when adatoms are present and demonstrate that T can be reduced, as chemical bonds are locally weakened due to the formation of new bonds with the adatom. We further calculate the partial and total cross sections for atom displacement from MoS2 and hBN, compare our results to the available experimental data, and conclude that adatoms should play a role in damage creation in MoS2 and hBN sheets at electron energies below the knock-on threshold of the pristine system, thus mediating the buildup of electron beam-induced damage.

.log Dateien der durchgeführten DFT Kalkulationen, welche die geometrieoptimierten Strukturen der Siderophore beinhalten. Desweiteren Excel files mit den Rohdaten zu Bindungsversuchen und Berechnungen der Reaktionsenergien.

Siderophores are promising ligands for application in novel recycling and bioremediation technologies, as they can selectively complex a variety of metals. However, with over 250 known siderophores, the selection of suiting complexant in the wet lab is impractical. Thus, this study established a density functional theory (DFT) based approach to efficiently identify siderophores with increased selectivity towards target metals on the example of germanium and indium. Considering 239 structures, chemically similar siderophores were clustered, and their complexation reactions modeled utilizing DFT. The calculations revealed siderophores with, compared to the reference siderophore desferrioxamine B (DFOB), up to 128 % or 48 % higher selectivity for indium or germanium, respectively. Experimental validation of the method was conducted with fimsbactin A and agrobactin, demonstrating up to 40% more selective indium binding and at least sevenfold better germanium binding than DFOB, respectively. The results generated in this study open the door for the utilization of siderophores in eco-friendly technologies for the recovery of many different critical metals from various industry waters and leachates or bioremediation approaches. This endeavor is greatly facilitated by applying the herein-created database of geometry-optimized siderophore structures as de novo modeling of the molecules can be omitted.

Instabilities in relativistic magnetized jets are thought to be deeply connected to their energy dissipation properties and to the consequent acceleration of the non-thermal emitting relativistic particles. Instabilities lead to the development of small-scale dissipative structures, in which magnetic energy is converted in other forms. In this paper we present three-dimensional numerical simulations of the instability evolution in highly magnetized plasma columns, considering different kinds of equilibria. In fact, the hoop stresses related to the azimuthal component of magnetic field can be balanced either by the magnetic pressure gradient (force-free equilibria, FF) or by the thermal pressure gradient (pressure-balanced equilibria, PB) or by a combination of the two. FF equilibria are prone to current-driven instabilities (CDI), while PB equilibria are prone to pressure-driven instabilities (PDI). We perform a global linear stability analysis, from which we derive the different instability properties in the two regimes, showing that PDI have larger growth rates and are also unstable for high wavenumbers. The numerical simulations of the non-linear instability evolution show similar phases of evolution in which the formation of strong current sheets is followed by a turbulent quasi-steady state. PDI are however characterized by a faster evolution, by the formation of smaller scale dissipative structures and larger magnetic energy dissipation.

Background: The Editorial Board of EJNMMI Radiopharmacy and Chemistry releases a biannual highlight commentary to update the readership on trends in the field of radiopharmaceutical development.
Main Body: This selection of highlights provides commentary on 19 different topics selected by each coauthoring Editorial Board member addressing a variety of aspects ranging from novel radiochemistry to first-in-human application of novel radiopharmaceuticals.
Conclusion: Trends in radiochemistry and radiopharmacy are highlighted. Hot topics cover the entire scope of EJNMMI Radiopharmacy and Chemistry, demonstrating the progress in the research field in many aspects.

Robot Operating System (ROS) has proven itself as a viable framework for developing robot-related applications. It offers features such as hardware abstraction, low-level device support, inter-process communication, and useful libraries for autonomous robot systems. Concerning aerial robots, commonly called unmanned aerial vehicles (UAV) or drones, ROS provides unfortunately very basic functions. Moreover, it does not guarantee real-time operation, as it runs under Linux. Consequently, it is difficult to implement advanced ROS applications that involve a swarm of drones that need to communicate with each other to carry out a common mission. This paper proposes an extended version of the ROS framework called autotarget*, which provides a set of efficient functions designed for distributed operation on multiple UAVs flying at the same time. autotarget* relies on a multi-tier architecture with a decentralized communication layer, enabling intra-UAV messaging as well as the scalability of swarm UAVs. It has a set of daemons whose feature is to regulate the swarm's consensus control and failover policy to ensure convergence towards a common goal. Experiments with real-world swarms revealed that autotarget* is portable and satisfies the performance requirements for collaborative mission applications. We further conducted a coverage planning mission using the parallel back-and-forth algorithm, which demonstrated the efficiency of the framework in terms of time and energy. Our work should pave the way for an open-source environment dedicated to simplifying collaborative ROS application development, particularly for multi-UAV systems.

"Spin" has been recently reported as an important degree of electronic freedom to promote catalysis, yet how it influences electronic structure remains unexplored. This work reports the spin-induced orbital hybridization in Ir-Fe bimetallic aerogels, where the electronic structure of Ir sites is effectively regulated by tuning the spin property of Fe atoms. The spin-optimized electronic structure boosts oxygen evolution reaction (OER) electrocatalysis in acidic media, resulting in a largely improved catalytic performance with an overpotential of as low as 236 mV at 10 mA cm^-2. Furthermore, the gelation kinetics for the aerogel synthesis is improved by an order of magnitude based on the introduction of a magnetic field. Density functional theory calculation reveals that the increased magnetic moment of Fe (3d orbital) changes the d-band structure (i.e., the d-band center and bandwidth) of Ir (5d orbital) via orbital hybridization, resulting in optimized binding of reaction intermediates. This strategy builds the bridge between the electron spin theory with the d-band theory and provides a new way for the design of high-performance electrocatalysts by using spin-induced orbital interaction.

There is an urgent need to increase the global data storage capacity, as current approaches lag behind the exponential growth of data generation driven by the Internet, social media and cloud technologies. In addition to increasing storage density, new solutions should provide long-term data archiving that goes far beyond traditional magnetic memory, optical disks and solid-state drives. We propose a concept of energy-efficient, ultralong, high-density data archiving based on optically active atomic-size defects in a radiation resistance material, silicon carbide (SiC) [1]. The information is written in these defects by focused ion beams and read using photoluminescence or cathodoluminescence. The temperature-dependent deactivation of these defects suggests a retention time minimum over a few generations under ambient conditions. With near-infrared laser excitation, grayscale encoding and multi-layer data storage, the areal density corresponds to that of Blu-ray discs. Furthermore, we demonstrate that the areal density limitation of conventional optical data storage media due to the light diffraction can be overcome by focused electron-beam excitation.

Using miniature compact tension (mini-C(T)) (4mm thick, 0.16T) specimens to determine
toughness in reactor pressure vessel (RPV) steels permits the ductile-to-brittle transition
temperature to be derived from small amounts of material and allows more effective use of
surveillance specimens. However, questions have been raised as to whether the failure
mechanisms are the same in miniature and large specimens, something that must be ensured
when transferring fracture results obtained in mini-C(T) specimens to larger components.
This work, performed within the FRACTESUS project, presents toughness measurements
and detailed fractography on both a homogeneously brittle base metal and a relatively
ductile, inhomogeneous weld to assess the transferability of fracture data. The fractography
shows that brittle fracture initiates within the part of specimen experiencing small-scale
yielding (SSY), so long as the toughness measurement is valid. Similarly, although the
precrack front asymmetry appears more marked in smaller specimens, as long as the
deviation from planarity is within the American Society for Testing and Materials (ASTM)
E1921 limits, the asymmetry does not affect the location of the initiation site. For materials
showing a variety of fracture modes, the fracture modes observed at the initiation sites are
consistent with those observed in larger specimens. Where data are available, the stress and
strain conditions at the initiation sites are also found to be consistent in mini-C(T) and larger
specimens. These observations support the thesis that toughness measurements made on
mini-C(T) specimens reflect the same material characteristics and failure mechanisms as
those made on larger specimens.

The Helmholtz Association is a pioneer in the establishment of research software guidelines and policies in the German research landscape. The roots go back to one of the first German RSE focused workshops, which took place in Dresden in 2016. Since then, the field of RSE has been successively expanded at various levels through the provision of training and support services, technical platforms and, last but not least, the development of guidelines and policies. In context of research data management, a similar process has been driven with a strong focus on research data policies and data management plans. Guidelines for software development are just as important in modern research, but have hardly been established to date.

The talk is a progress report on the activities and results that have been achieved in the Helmholtz Centers in recent years. We present concrete examples with facts, statistics and user experience reports. In addition, we also share our experiences on how to actively stimulate this process, for example, through awards and visible indicators.The policy implementation at Helmholtz is ongoing and is actively supported in regular Helmholtz-wide research software forums organized by the Helmholtz Incubator Platform HIFIS and the Task Group Research Software of the Helmholtz Open Science Working Group.

We develop a Transformer-based model enhanced with a Channel Attention Module (CAM) to capture the inter-channel dependencies in 3D hyperspectral point cloud data for geological applications. We hypothesize that specific channels of hyperspectral data correspond to distinct mineral types, and therefore, exploiting the relationships among these channels is beneficial for our analysis. We evaluate our method using the newly released Tinto dataset, which consists of 3D hyperspectral point clouds featuring three different spectral ranges: LongWave Infrared (LWIR), ShortWave Infrared (SWIR), and Visible-Near Infrared (VNIR).We explore four different CAMs from various networks—SENet, ECANet, CBAM, and DANet—and successfully integrate them into a CNN-based model to enhance feature representation. We specifically tailor the channel attention to our use of 3D hyperspectral point cloud data. Our experiments demonstrate significant improvements in performance after incorporating the CAM into our backbone model, which draws inspiration from the Point Cloud Transformer architecture and Vector Self-Attention mechanism. These results highlight the potential for further research into enhancing classification accuracy using hyperspectral data in geological applications. The code will be released on https://github.com/aldinorizaldy/CAM-Transformer.

Transformer-based models have achieved state-of-the-art results in point cloud segmentation. However, their evaluation has been limited to benchmark data with natural objects. In this study, we present the first investigation of Transformers for hyperspectral point clouds, comparing different attention modules. We utilize the Tinto dataset, which provides extensive hyperspectral features for geological applications, offering diverse benchmarking settings. Our experiments demonstrate that the Transformer with vector attention surpasses the commonly-used dot-product scalar attention. Moreover, this model achieves significantly higher accuracy scores than the well-known point cloud models, PointNet and PointNet++, across three hyperspectral sensors.

Recently, MnTe was established as an altermagnetic material that hosts spin-polarized electronic bands as well as anomalous transport effects like the anomalous Hall effect. In addition to these effects arising from altermagnetism, MnTe also hosts other magnetoresistance effects. Here, we study the manipulation of the magnetic order by an applied magnetic field and its impact on the electrical resistivity. In particular, we establish which components of anisotropic magnetoresistance are present when the magnetic order is rotated within the hexagonal basal plane. Our experimental results, which are in agreement with our symmetry analysis of the magnetotransport components, showcase the existence of an anisotropic magnetoresistance linked to both the relative orientation of current and magnetic order, as well as crystal and magnetic order. Altermagnetism is manifested as a three-fold component in the transverse magnetoresistance which arises due to the anomalous Hall effect.

We report on a quantum critical behavior in the quasi-1D spin-1/2 zigzag frustrated chain antiferromagnet CaCoV₂O₇, induced by an applied magnetic field. Below T_N = 3.3 K our zero-field neutron diffraction studies revealed the up-up-down-down spin structure, stabilized by an order-by-disorder phenomenon. At base temperature, the magnetic order is suppressed by an applied magnetic field (B), inducing a transition into a quantum paramagnetic state at B_c = 3 T, as revealed by both neutron diffraction and ESR data. The transition exhibits an unusually sharp phase boundary with the critical exponent φ = 0.164(3) ≈ 1/6, in contrast to the earlier experimental observations for uniform spin-1/2 chain systems. Such a sharp QPT is anticipated due to a rare combination of spin-orbit coupling and competing NN and NNN exchange interactions J₁ and J₂ of the zigzag spin chain.

Purpose: 68Ga-labeled fibroblast activation protein inhibitor (FAPI) is a novel PET tracer with great potential for staging pancreatic cancer. Data on locally advanced or recurrent disease is sparse, especially on tracer uptake before and after high dose chemoradiotherapy (CRT). The aim of this study was to evaluate [68Ga]Ga-FAPI-46 PET/CT staging in this setting.

Methods: Twenty-seven patients with locally recurrent or locally advanced pancreatic adenocarcinoma (LRPAC n = 15, LAPAC n = 12) in stable disease or partial remission after chemotherapy underwent FAPI PET/CT and received consolidation CRT in stage M0 with follow-up FAPI PET/CT every three months until systemic progression. Quantitative PET parameters SUVmax, SUVmean, FAPI-derived tumor volume and total lesion FAPI-uptake were measured in baseline and follow-up PET/CT scans. Contrast-enhanced CT (ceCT) and PET/CT data were evaluated blinded and staged according to TNM classification.

Results: FAPI PET/CT modified staging compared to ceCT alone in 23 of 27 patients in baseline, resulting in major treatment alterations in 52% of all patients (30%: target volume adjustment due to N downstaging, 15%: switch to palliative systemic chemotherapy only due to diffuse metastases, 7%: abortion of radiotherapy due to other reasons). Regarding follow-up scans, major treatment alterations after performing FAPI PET/CT were noted in eleven of 24 follow-up scans (46%) with switch to systemic chemotherapy or best supportive care due to M upstaging and ablative radiotherapy of distant lymph node and oligometastasis. Unexpectedly, in more than 90 % of the follow-up scans, radiotherapy did not induce local fibrosis related FAPI uptake.

During the first follow-up, all quantitative PET metrics decreased, and irradiated lesions showed significantly lower FAPI uptake in locally controlled disease (SUVmax p = 0.047, SUVmean p = 0.0092) compared to local failure.

Conclusion: Compared to ceCT, FAPI PET/CT led to major therapeutic alterations in patients with LRPAC and LAPAC prior to and after radiotherapy, which might help identify patients benefiting from adjustments in every treatment stage. FAPI PET/CT should be considered a useful diagnostic tool in LRPAC or LAPAC before and after CRT.

Background

PSMA-PET is increasingly used for staging prostate cancer (PCA) patients. However, it is not clear if quantitative imaging parameters of positron emission tomography (PET) have an impact on disease progression and are thus important for the prognosis of localized PCA.

Methods

This is a monocenter retrospective analysis of 86 consecutive patients with localized intermediate or high-risk PCA and PSMA-PET before treatment The quantitative PET parameters maximum standardized uptake value (SUVmax), tumor asphericity (ASP), PSMA tumor volume (PSMA-TV), and PSMA total lesion uptake (PSMA-TLU = PSMA-TV × SUVmean) were assessed for their prognostic significance in patients with radiotherapy or surgery. Cox regression analyses were performed for biochemical recurrence-free survival, overall survival (OS), local control, and loco-regional control (LRC).

Results

67% of patients had high-risk disease, 51 patients were treated with radiotherapy, and 35 with surgery. Analysis of metric PET parameters in the whole cohort revealed a significant association of PSMA-TV (p = 0.003), PSMA-TLU (p = 0.004), and ASP (p < 0.001) with OS. Upon binarization of PET parameters, several other parameters showed a significant association with clinical outcome. When analyzing high-risk patients according to the primary treatment approach, a previously published cut-off for SUVmax (8.6) showed a significant association with LRC in surgically treated (p = 0.048), but not in primary irradiated (p = 0.34) patients. In addition, PSMA-TLU (p = 0.016) seemed to be a very promising biomarker to stratify surgical patients.

Conclusion

Our data confirm one previous publication on the prognostic impact of SUVmax in surgically treated patients with high-risk PCA. Our exploratory analysis indicates that PSMA-TLU might be even better suited. The missing association with primary irradiated patients needs prospective validation with a larger sample size to conclude a predictive potential.

The spin degree of freedom in magnetically ordered materials is an important aspect for a variety of research directions. Antiferromagnets represent a broad class of systems with compensated or almost compensated net magnetization. On one side, it is a factor in the complications of their experimental investigation. However, on the other side, they offer unique features on ultrafast dynamics, strong robustness regarding external magnetic fields and delicate symmetry-driven phenomena in spin torques and multiferroicity. Specific research attention is paid to the properties of antiferromagnetic solitons as potential information carriers and the surface properties at which the readout of the magnetic state is performed. Here, we focus on the seminal magnetoelectric antiferromagnet Cr2O3 (chromia) with the easy-axis magnetic anisotropy.

In bulk single crystal chromia, the multidomain state is not favorable due to thermodynamic reasons, thus the stabilization of domain walls is possible on the defects. In particular, the litographically partterned surface topography of the sample can serve as the pinning landscape for the domain wall. The spatial inhomogeneity of this landscape allows to uncover the mechanical properties of the magnetic textures such as elastic deformation of the domain wall plane governed by the exchange boundary conditions [1]. Extension of this model onto chiral antiferromagnets with an inhomogeneous Dzyaloshinskii-Moriya interaction (DMI) shows that the domain walls and skyrmions possess a substantial modification of their shape approaching surface and side faces of the sample. These modifications limit the minimal size of racetracks to keep the bulk-like properties of magnetic solitons [2].

The surface of an antiferromagnet itself can substantially change its magnetic state. Chromia possesses two nominally compensated high-symmetry planes with an experimental evidence of a finite magnetization. The latter can be understood in terms of the surface magnetic symmetry group which supports a homogeneous DMI and can even change the bulk collinear antiferromagnetic ordering to a canted ferrimagnetic one [3].

In contrast to bulk, the chromia thin films are commonly in the multidomain state, which is determined by their granular structure. The domain wall pinning at the defects depends on the defect properties. Therefore, the visual analysis of the domain picture obtained, e.g., via Nitrogen vacancy magnetometry can be used as a source of quantification of the inter-grain coupling in the thin film [4] and, even quantification of such exotic phenomena like thermally driven flexomagnetism [5].

The spin degree of freedom in magnetically ordered materials is an important aspect for a variety of research directions. Antiferromagnets represent a broad class of systems with compensated or almost compensated net magnetization. On one side, it is a factor in the complications of their experimental investigation. However, on the other side, they offer unique features on ultrafast dynamics, strong robustness regarding external magnetic fields and delicate symmetry-driven phenomena in spin torques and multiferroicity. Specific research attention is paid to the properties of antiferromagnetic solitons as potential information carriers and the surface properties at which the readout of the magnetic state is performed. Here, we focus on the seminal magnetoelectric antiferromagnet Cr2O3 (chromia) with the easy-axis magnetic anisotropy.

In bulk single crystal chromia, the multidomain state is not favorable due to thermodynamic reasons, thus the stabilization of domain walls is possible on the defects. In particular, the litographically partterned surface topography of the sample can serve as the pinning landscape for the domain wall. The spatial inhomogeneity of this landscape allows to uncover the mechanical properties of the magnetic textures such as elastic deformation of the domain wall plane governed by the exchange boundary conditions [1]. In contrast, the chromia thin films are commonly in the multidomain state, which is determined by their granular structure. The domain wall pinning at the defects depends on the defect properties. Therefore, the visual analysis of the domain picture obtained, e.g., via Nitrogen vacancy magnetometry can be used as a source of quantification of the inter-grain coupling in the thin film [2]. Furthermore, in the case of the high-quality chromia samples epitaxially grown at sapphire substrate, the presence of domain walls allows to reveal a new temperature-driven source of the flexomagnetism in thin antiferromagnetic films [3].

Even in absence of specific processing like litography or design of exchange bias multilayers, the surface of an antiferromagnet can alter its magnetic state by its specific magnetic symmetry. Chromia possesses two nominally compensated high-symmetry planes with an experimental evidence of finite magnetization. It can be understood by the surface magnetic point symmetry group, which renders the m and a planes of chromia to be canted ferrimagnet and antiferromagnet, respectively [4].

We report terahertz (THz)-pump/mid-infrared probe near-field studies on Si-doped GaAs–InGaAs core–shell nanowires utilizing THz radiation from the free-electron laser FELBE. Upon THz excitation of free carriers, we observe a red shift of the plasma resonance in both amplitude and phase spectra, which we attribute to the heating of electrons in the conduction band. The simulation of heated electron distributions anticipates a significant electron population in both the L- and X-valleys. The two-temperature model is utilized for quantitative analysis of the dynamics of the electron gas temperature under THz pumping at various power levels.

Background: MR-integrated proton therapy is under development. It consists
of the unique challenge of integrating a proton pencil beam scanning (PBS)
beam line nozzle with an magnetic resonance imaging (MRI) scanner.The magnetic
interaction between these two components is deemed high risk as the
MR images can be degraded if there is cross-talk during beam delivery and
image acquisition.
Purpose: To create and benchmark a self -consistent proton PBS nozzle model
for empowering the next stages of MR-integrated proton therapy development,
namely exploring and de-risking complete integrated prototype system designs
including magnetic shielding of the PBS nozzle.
Materials and Methods: Magnetic field (COMSOL Multiphysics) and radiation
transport (Geant4) models of a proton PBS nozzle located at OncoRay (Dresden,
Germany) were developed according to the manufacturers specifications.
Geant4 simulations of the PBS process were performed by using magnetic field
data generated by the COMSOL Multiphysics simulations. In total 315 spots
were simulated which consisted of a 40 × 30cm2 scan pattern with 5 cm spot
spacings and for proton energies of 70, 100, 150, 200, and 220 MeV. Analysis
of the simulated deflection at the beam isocenter plane was performed to
determine the self -consistency of the model. The magnetic fringe field from a
sub selection of 24 of the 315 spot simulations were directly compared with high
precision magnetometer measurements.These focused on the maximum scanning
setting of ± 20 cm beam deflection as generated from the second scanning
magnet in the PBS for a proton beam energy of 220 MeV. Locations along the
beam line central axis (CAX) were measured at beam isocenter and downstream
of 22, 47, 72, 97, and 122 cm. Horizontal off -axis positions were measured
at 22 cm downstream of isocenter (± 50,± 100,and ± 150 cm from CAX).
Results: The proton PBS simulations had good spatial agreement to the theoretical
values in all 315 spots examined at the beam line isocenter plane
(0–2.9 mm differences or within 1.5 % of the local spot deflection amount).
Careful analysis of the experimental measurements were able to isolate
the changes in magnetic fields due solely to the scanning magnet contribution,
and showed 1.9 ± 1.2 uT–9.4 ± 1.2 uT changes over the range
of measurement locations. Direct comparison with the equivalent simulations
matched within the measurement apparatus and setup uncertainty in all but
one measurement point.
Conclusions: For the first time a robust, accurate and self -consistent model
of a proton PBS nozzle assembly has been created and successfully
benchmarked for the purposes of advancing MR-integrated proton therapy
research. The model will enable confidence in further simulation based work
on fully integrated designs including MRI scanners and PBS nozzle magnetic
shielding in order to de-risk and realize the full potential of MR-integrated proton
therapy.

The analysis of particle–bubble collisions in turbulent flow is a fundamental problem of high technological relevance, e.g., for the separation of valuable mineral particles by froth flotation. This relevance contrasts with an apparent lack of experimental data and understanding of this collision process. To this end, a periodic bubble chain was used to study the collision of millimeter-sized bubbles with polystyrene particles. The collision process between these entities was measured using 4D particle tracking velocimetry (PTV). By analyzing the collision data as a function of the polar angle along the bubble surface, we show that the collision took place not only at the leading edge but also at the trailing edge of the bubble. To understand the underlying mechanisms of the trailing edge collision, the flow field around a rising bubble chain was measured with Tomographic Particle Image Velocimetry (TPIV). The vortex formed in the bubble wake led to a velocity in the direction of the bubble surface that enabled trailing edge collisions. This effect is amplified by an increase in the turbulent kinetic energy and dissipation rate in the bubble wake. Overall, the investigation reveals different collision mechanisms and advances our understanding of the role of the wake in the bubble–particle collision.

Improvement in resolving hydrodynamic variables in multiphase flows is key to optimizing flotation performance. However, due to equipment complexity and opacity of three-phase systems, in situ measurements become challenging. Therefore, by using a novel multi-sensor approach, the aim of this study is to spatially resolve key hydrodynamic and gas dispersion parameters in a mechanical flotation cell such as superficial gas velocity (Jg), gas holdup (εg), bubble size distribution (BSD), and bubble surface area flux (Sb). A high-resolution inline endoscope (SOPAT), Jg and εg sensors were fixed at multiple axial positions in a 6L nextSTEP™ flotation cell. This multi-sensor concept has been applied to a simplified benchmark flotation scenario, as part of a binary (pyrite-quartz) flotation test campaign (30 % solid load). Varying operating conditions include tip speed (4.7 – 5.5 m/s), air flow (0.4 – 0.5 cm/s), frother (MIBC: 30 – 60 g/ton), and collector concentrations (PAX: 30 – 60 g/ton). Sb is a good indicator of gas dispersion efficiency in flotation, and local measurements indicated that there are significant differences in the local superficial gas velocities which can be measured with our adapted sensor. Real-time bubble size measurements reflected the high shear rates near the rotor–stator region. Overall, the gas flow rate and frother concentration were shown to have the most significant effect on the gas dispersion in the benchmark flotation tests.

Background and Purpose: To develop and test a decision tree for predicting contrast enhancement quality and shape using pre-contrast MRI sequences in a large adult-type diffuse glioma cohort.
Methods: Preoperative MRI scans (development/optimization/test sets: n=31/38/303, male=17/22/189, mean age=52/59/56.7 years, high-grade glioma=22/33/249) were retrospectively evaluated, including pre-and post-contrast T1-weighted, T2-weighted, fluid-attenuated inversion recovery, and diffusion-weighted imaging sequences. Enhancement prediction decision tree (EPDT) was developed using development and optimization sets, incorporating four imaging features: necrosis, diffusion restriction, T2 inhomogeneity, and nonenhancing tumor margins. EPDT accuracy was assessed on a test set by three raters of variable experience. True enhancement features (gold standard) were evaluated using pre- and post-contrast T1-weighted images. Statistical analysis used confusion matrices, Cohen’s/Fleiss’ kappa, and Kendall’s W. Significance threshold was P < 0.05.
Results: Raters 1, 2, and 3 achieved overall accuracies of 0.86 [95%-confidence interval (CI): 0.81-0.90], 0.89 (95%-CI: 0.85-0.92), and 0.92 (95%-CI: 0.89-0.95), respectively, in predicting enhancement quality (marked, mild, or no enhancement). Regarding shape, defined as the thickness of enhancing margin (solid, rim, or no enhancement), accuracies were 0.84 (95%-CI: 0.79-0.88), 0.88 (95%-CI: 0.84-0.92), and 0.89 (95%-CI: 0.85-0.92). Intra-rater inter-group agreement comparing predicted and true enhancement features consistently reached substantial levels [≥0.68 (95%-CI: 0.61-0.75). Inter-rater comparison showed at least moderate agreement (group: ≥0.42 (95%-CI: 0.36-0.48), pairwise: ≥0.61 (95%-CI: 0.50-0.72)]. Among the imaging features in the EPDT, necrosis assessment displayed the highest intra- and inter-rater consistency [≥0.80 (95%-CI: 0.73-0.88)].
Conclusion: The proposed enhancement prediction decision tree has high accuracy in predicting enhancement patterns of gliomas irrespective of rater experience.

Theory questions the persistence of non-reciprocal interactions in which one plant has a positive net effect on a neighbor that, in return, has a negative net impact on its benefactor—a phenomenon known as antagonistic facilitation. We develop a spatially explicit consumer-resource model for below-ground plant competition between ecosystem engineers, plants able to mine resources and make them available for any other plant in the community, and exploiters. We use the model to determine in what environmental conditions antagonistic facilitation via soil resource engineering emerges as an optimal strategy. Antagonistic facilitation emerges in stressful environments where ecosystem engineers’ self-benefits from mining resources outweigh the competition with opportunistic neighbors. Among all potential causes of stress considered in the model, the key environmental parameter driving changes in the interaction between plants is the proportion of the resource that becomes readily available for plant consumption in the absence of any mining activity. Our results align with theories of primary succession and the stress gradient hypothesis. However, we find that the total root biomass and its spatial allocation through the root system, often used to measure the sign of the interaction between plants, do not predict facilitation reliably.

Magnonics is a research field that has gained an increasing interest in both the fundamental and applied sciences in recent years. This field aims to explore and functionalize collective spin excitations in magnetically ordered materials for modern information technologies, sensing applications and advanced computational schemes. Spin waves, also known as magnons, carry spin angular momenta that allow for the transmission, storage and processing of information without moving charges. In integrated circuits, magnons enable on-chip data processing at ultrahigh frequencies without the Joule heating, which currently limits clock frequencies in conventional data processors to a few GHz. Recent developments in the field indicate that functional magnonic building blocks for in-memory computation, neural networks and Ising machines are within reach. At the same time, the miniaturization of magnonic circuits advances continuously as the synergy of materials science, electrical engineering and nanotechnology allows for novel on-chip excitation and detection schemes. Such circuits can already enable magnon wavelengths of 50 nm at microwave frequencies in a 5G frequency band. Research into non-charge-based technologies is urgently needed in view of the rapid growth of machine learning and artificial intelligence applications, which consume substantial energy when implemented on conventional data processing units. In its first part, the 2024 Magnonics Roadmap provides an update on the recent developments and achievements in the field of nano-magnonics while defining its future avenues and challenges. In its second part, the Roadmap addresses the rapidly growing research endeavors on hybrid structures and magnonics-enabled quantum engineering. We anticipate that these directions will continue to attract researchers to the field and, in addition to showcasing intriguing science, will enable unprecedented functionalities that enhance the efficiency of alternative information technologies and computational schemes.

Introduction The standard treatment for patients with focal drug-resistant epilepsy (DRE) who are not eligible for
open brain surgery is the continuation of anti-seizure medication (ASM) and neuromodulation. This treatment does not cure epilepsy but only decreases severity. The PRECISION trial offers a non-invasive, possibly curative intervention for these patients, which consist of a single stereotactic radiotherapy (SRT) treatment. Previous studies have shown promising results of SRT in this patient population. Nevertheless, this intervention is not yet available and reimbursed in the Netherlands. We hypothesize that: SRT is a superior treatment option compared to palliative standard of care, for patients with focal DRE, not eligible for open surgery, resulting in a higher reduction of seizure frequency (with 50% of the patients reaching a 75% seizure frequency reduction at 2 years follow-up).
Methods In this waitlist-controlled phase 3 clinical trial, participants are randomly assigned in a 1:1 ratio to either
receive SRT as the intervention, while the standard treatments consist of ASM continuation and neuromodulation.
After 2-year follow-up, patients randomized for the standard treatment (waitlist-control group) are offered SRT.
Patients aged ≥ 18 years with focal DRE and a pretreatment defined epileptogenic zone (EZ) not eligible for open
surgery will be included. The intervention is a LINAC-based single fraction (24 Gy) SRT treatment. The target volume is defined as the epileptogenic zone (EZ) on all (non) invasive examinations. The seizure frequency will be monitored on a daily basis using an electronic diary and an automatic seizure detection system during the night. Potential side effects are evaluated using advanced MRI, cognitive evaluation, Common Toxicity Criteria, and patient-reported outcome questionnaires. In addition, the cost-effectiveness of the SRT treatment will be evaluated.
Discussion This is the first randomized trial comparing SRT with standard of care in patients with DRE, non-eligible for open surgery. The primary objective is to determine whether SRT significantly reduces the seizure frequency 2 years after treatment. The results of this trial can influence the current clinical practice and medical cost reimbursement in the Netherlands for patients with focal DRE who are not eligible for open surgery, providing a non-invasive curative treatment option.

Purpose: Radio(chemo)therapy (RCT) as part of the standard treatment of glioma patients, inevitably leads to
radiation exposure of the tumor-surrounding normal-appearing (NA) tissues. The effect of radiotherapy on the
brain microstructure can be assessed by magnetic resonance imaging (MRI) using diffusion tensor imaging (DTI).
The aim of this study was to analyze regional DTI changes of white matter (WM) structures and to determine
their dose- and time-dependency.
Methods: As part of a longitudinal prospective clinical study (NCT02824731), MRI data of 23 glioma patients
treated with proton or photon beam therapy were acquired at three-monthly intervals until 36 months following
irradiation. Mean, radial and axial diffusivity (MD, RD, AD) as well as fractional anisotropy (FA) were investi-
gated in the NA tissue of 15 WM structures and their dependence on radiation dose, follow-up time and distance
to the clinical target volume (CTV) was analyzed in a multivariate linear regression model. Due to the small and
non-comparable patient numbers for proton and photon beam irradiation, a separate assessment of the findings
per treatment modality was not performed.
Results: Four WM structures (i.e., internal capsule, corona radiata, posterior thalamic radiation, and superior
longitudinal fasciculus) showed statistically significantly decreased RD and MD after RT, whereas AD decrease
and FA increase occurred less frequently. The posterior thalamic radiation showed the most pronounced changes
after RCT [i.e., ΔRD = −8.51 % (p = 0.012), ΔMD = −6.14 % (p = 0.012)]. The DTI changes depended
significantly on mean dose and time.
Conclusion: Significant changes in DTI for WM substructures were found even at low radiation doses. These
findings may prompt new radiation dose constraints sparing the vulnerable structures from damage and sub-
sequent side-effects.

Objective In the era of image-guided adaptive radiotherapy, definition of the clinical target volume (CTV) is a challenge in various solid tumors, including esophageal cancer (EC). Many tumor microenvironmental factors, e.g., tumor cell proliferation or cancer stem cells, are hypothesized to be involved in microscopic tumor extension (MTE). Therefore, this study assessed the expression of FAK, ILK, CD44, HIF-1α, and Ki67 in EC patients after neoadjuvant radiochemotherapy followed by tumor resection (NRCHT+R) and correlated these markers with the MTE.
Methods Formalin-fixed paraffin-embedded tumor resection specimens of ten EC patients were analyzed using multiplex immunofluorescence staining. Since gold fiducial markers had been endoscopically implanted at the proximal and distal tumor borders prior to NRCHT+R, correlation of the markers with the MTE was feasible.
Results In tumor resection specimens of EC patients, the overall percentages of FAK+, CD44+, HIF-1α+, and Ki67+ cells were higher in tumor nests than in the tumor stroma, with the outcome for Ki67+ cells reaching statistical significance (p< 0.001). Conversely, expression of ILK+ cells was higher in tumor stroma, albeit not statistically significantly. In three patients, MTE beyond the fiducial markers was found, reaching up to 31mm.
Conclusion Our findings indicate that the overall expression of FAK, HIF-1α, Ki67, and CD44 was higher in tumor nests, whereas that of ILK was higher in tumor stroma. Differences in the TME between patients with residual tumor cells in the original CTV compared to those without were not found. Thus, there is insufficient evidence that the TME influences the required CTV margin on an individual patient basis.

The evidence for the value of particle therapy (PT) is still sparse. While randomized trials remain a cornerstone for robust comparisons with photon-based radiotherapy, data registries collecting real-world data can play a crucial role in building evidence for new developments. This Perspective describes how the European Particle Therapy Network (EPTN) is actively working on establishing a prospective data registry encompassing all patients undergoing PT in European centers. Several obstacles and hurdles are discussed, for instance harmonization of nomenclature and structure of technical and dosimetric data and data protection issues. A preferred approach is the adoption of a federated data registry model with transparent and agile governance to meet European requirements for data protection, transfer, and processing. Funding of the registry, especially for operation after the initial setup process, remains a major challenge.

Antiferromagnetic materials have unique properties due to their alternating spin arrangements. Their compensated magnetic order, robust against external magnetic fields, prevents long-distance crosstalk from stray fields. Furthermore, antiferromagnets with combined parity and time-reversal symmetry enable electrical control and detection of ultrafast exchange-field enhanced spin manipulation up to THz frequencies. Here we report the experimental realization of a nonvolatile antiferromagnetic memory mimicking an artificial synapse, in which the reconfigurable synaptic weight is encoded in the ratio between reversed antiferromagnetic domains. The non-volatile memory is “written” by spin-orbit torque-driven antiferromagnetic domain wall motion and “read” by nonlinear magnetotransport. We show that the absence of long-range interacting stray magnetic fields leads to very reproducible electrical pulse-driven variations of the synaptic weights.

The present work reports a systematic study of the potential degradation of metals and dielectric thin films in different space environments. The mono- and bilayers selected are made of materials commonly used for the realization of optical components, such as reflective mirrors or building blocks of interferential filters. More than 400 samples were fabricated and irradiated with protons at different energies on ground-based facilities. The fluences were selected as a result of simulations of the doses delivered within a long-term space mission considering different orbits (Sun close, Jovian, and Geostationary orbits). In order to stress the samples at different depths and layer interfaces, experiments were carried out with a range of proton energies within 1 and 10 MeV values. An estimate of a safe maximum fluence has been provided for each type of sample at each energy. The damage mechanism, when present, has been investigated with different optical and structural techniques.

Electric power systems during transient states are extensively investigated using variations of the Kuramoto model to analyze their dynamic behavior. However, the majority of current models fail to capture the physics of power flows and the heterogeneity of the grids under study. This study addresses this gap by comparing the levels of heterogeneity in continent-sized power grids in Europe and North America to reveal the underlying universality and heterogeneity of grid frequencies, electrical parameters, and topological structures. Empirical data analysis of grid frequencies from the Hungarian grid indicates that q-Gaussian distributions best fit simulations, with spatio-temporally correlated noise evident in the frequency spectrum. Comparing European and North American power grids reveals that employing homogeneous transmission capacities to represent power lines can lead to misleading results on stability, and nodal behavior is heterogeneous. Community structures of the continent-sized grids are detected, demonstrating that Chimera states are more likely to occur when studying only subsystems. A topographical analysis of the grids is presented to assist in selecting such subsystems. Finally, synchronization calculations are provided to illustrate the occurrence of Chimera states. The findings underscore the necessity of heterogeneous grid models for dynamic stability analysis of power systems.

Time-dependent density functional theory (TDDFT) is a widely used method to investigate electron dynamics under various external perturbations such as laser fields. In this work, we present a novel approach to accelerate real time TDDFT based electron dynamics simulations using autoregressive neural operators as time-propagators for the electron density. By leveraging physics-informed constraints and high-resolution training data, our model achieves superior accuracy and computational speed compared to traditional numerical solvers. We demonstrate the effectiveness of our model on a class of one-dimensional diatomic molecules. This method has potential in enabling real-time, on-the-fly modeling of laser-irradiated molecules and materials with varying experimental parameters.

Ternary nitrides are rapidly emerging as promising compounds for optoelectronic and energy conversion applications, yet comparatively little of this vast composition space has been explored. Furthermore, the crystal structures of these compounds can exhibit a significant amount of disorder, the consequences of which are not yet well understood. Here, the deposition of bixbyite-type ZrTaN3 thin films is demonstrated by reactive magnetron co-sputtering and observed semiconducting character, with a strong optical absorption onset at 1.8 eV and significant photoactivity, with prospective application as functional photoanodes. It is found that Wyckoff-site occupancy of cations is a critical factor in determining these beneficial optoelectronic properties. First-principles calculations show that cation disorder leads to minor deviations in the total energy but modulates the bandgap by 0.5 eV, changing orbital hybridization of valence and conduction band states. In addition to demonstrating that ZrTaN3 is a promising visible light-absorbing semiconductor and active photoanode material, the findings provide important insights regarding the role of cation ordering on the electronic structure of ternary semiconductors. In particular, it is shown that not only cation order, but also the cationic Wyckoff site occupancy has a substantial impact on key optoelectronic properties, which can guide future design and synthesis of advanced semiconductors.

In today's era of digitalization, managing the lifecycle of research projects demands efficient navigation through a myriad of data sources and services. This presentation delves into the pivotal role of HELIPORT, a web browser-based guidance system, in streamlining research project lifecycle management. HELIPORT serves as a comprehensive platform, seamlessly connecting disparate services and systems to facilitate the smooth flow of digital data throughout the entire research process. By harnessing HELIPORT's capabilities, researchers can effectively track, organise, and share data and workflows with colleagues, thereby enhancing collaboration. The embedding of computational workflows to automate processes and provide comprehensible and reproducable workloads on HPC clusters is an essential part of this process. In the talk, we explore how HELIPORT is expanding the digital horizon and empowering researchers to push new boundaries in scientific exploration.

This repository entails the data and Pythoncode for the publication "Dynamics of Lagrangian Sensor Particles: The Effect of Non-Homogeneous Mass Distribution" in the journal "Processes".

In the following a brief introduction and guide based on the folders in the repository is laid out. More code specific instructions can be found in the respective codes.

01 --> The tracking always begins with the same 01_milti[...] folder in which the python code with OpenCV algorithm is located. For tracking the tracking to work certain directories are required in which the raw images are to be stored (separate from anything else) as well as a directory in which the results are to be save (not the same directory as the raw data).

After tracking is completed for all respective experiments and the results directories are adequately labelled and stored any of the other code files can be used for respective analyses. The order of folders beyond the first 01 directory has no relevance to the order of evaluation however can ease the understanding of evaluated data if followed.

02 --> Evaluation of amount of circulations and respective circulation time in experimental vat. (code can be extended to calculate the circulation time based on the various plains that are artificially set)

03 --> Code for the calculation of the amount of contacts with the vat floor. Code requires certain visual evaluations based on the LP trajectories, as the plain/barrier for the contact evaluation has to be manually set.

04 --> Contains two codes that can be applied to results data to combine individual results into larger more processable arrays within python

05 --> Contains the code to plot the trajectory of single experiments of Lagrangian particles based on their positional results and velocity at respective position, highlighting the trajectory over the experiment.

06 --> Condes to create 1D histograms based on the probability density distribution and velocity distributions in cumulative experiments.

07 --> Codes for plotting the 2D probability density distribution (2D Histograms) of Lagrangian Particles based on the cumulative experiments. Code provides values for the 2D grid, plotting is conducted in Origin Lab or similar graphing tools, graphing can also be conducted in python whereby the seaborn (matplotlib) library is suggested.

08 --> Contain the code for the dimensionless evaluation of the results based on the respective Stokes number approaches and weighted averages. 2D histograms are also vital to this evaluation, whereby the plotting is again conducted in Origin Lab as values are only calculated in code.

09 --> Directory does not contain any python codes but instead contains the respective Origin Lab files for the graphing, plotting and evaluation of results calculated via python is given. Respective tables, histograms and heat maps are hereby given to be used as templates if necessary.

The project used the Origin 2023 (64-bit) version, if no Origin license is available then Origin Lab provides a free Origin Viewer with which the projects can be opened and viewed. (https://www.originlab.com/viewer/)

The diameter distribution of bubbles in foam is one of the most important features in foam-based separation processes like foam fractionation and froth flotation. In this study the bubble size at different radial positions of pneumatically produced foams without coalescence and coarsening of bubbles is investigated in a cylindrical column by employing an invasive sampling probe. It is shown that pronounced differences of the local Sauter-mean diameter of the bubbles can appear in radial direction. Oftentimes a parabolic profile with the largest mean bubble diameter in the center of the column is found. The difference of the Sauter-mean diameter between wall- and center region is in the order of up to 60%. Experiments on foams produced with different spargers, gas flow rates and liquid filling levels reveal that the actual degree of the inhomogeniety depends on the specific bubble size distribution that is produced by the sparger, and becomes more pronounced if the range of bubble diameters in the foam increases. As an explanation for the observations, hydrodynamic interactions in the liquid phase, as well as the behavior of different sized bubbles close to the liquid/foam interface are proposed. The observed existence of local differences of the bubble diameters can have a strong influence the dynamic behavior, like liquid drainage, and measurement methods of pneumatic foams. In particular it can limit the applicability of surface-based bubble size measurements.

In this lecture I will show how neural networks can be used to solve differential equations. We will consider the basic example of the quantum harmonic oscillator. After reviewing some basic concepts, we will implement two machine learning methods to solve the time-dependent Schrödinger equation for the harmonic oscillator. First, we will consider a data-driven approach where a fully connected neural network is used to learn the solutions of the differential equation based on input labels. In the second approach, we will consider physics-informed neural networks. In contrast to the data-driven approach, the solution of the differential equation is not learned by mapping input features to outputs, but by minimizing a loss term related to the form of the differential equation. The lecture will be both formal and interactive using Jupyter notebooks.

In this lecture I will introduce the concept of neural networks. We will begin with a brief overview of the development of artificial neural networks. We will look at the basic perceptron model from a mathematical point of view and implement it to solve a simple classification problem. In the last part of the lecture, I will provide a gentle interactive introduction to deep learning using a simple toy problem about digital colors. We will learn how to build neural network pipelines and develop a qualitative understanding. The lecture will be both formal and interactive using Jupyter notebooks.

Here we report the synthesis of the 6-(6-methyl-1,2,4,5-tetrazine-3-yl)-2,2‘-bipyridine (MTB) ligand, that has been developed for lanthanide/actinide separation. A multi-method study of the
complexation of MTB with trivalent actinide and lanthanide ions is presented. Single crystal X-ray diffraction measurements reveal the formation of [Ce(MTB)2(NO3)3], [Pr(MTB)NO3)3H2O], and [Ln(MTB)(NO3)3MeCN] (Ln = Nd, Sm, Eu, Gd). In addition, the complexation of Cm(III) with MTB in solution was studied by time-resolved laser fluorescence spectroscopy. The results show the formation of [Cm(MTB)1-3] 3+ complexes, which occurs in two different isomers. Quantum chemical calculations reveal an energy difference between these isomers of 12 kJ mol-1, clarifying the initial observations made by TRLFS. Furthermore, QTAIM analysis of the Cm(III) and Ln(III) complexes was performed, indicating a stronger covalent contribution in the Cm-N interaction compared to the respective Ln-N interaction. These findings align well with extraction data showing a preferred extraction of Am and Cm over lanthanides (e.g., max. SFAm/Eu = 8.3) at nitric acid concentrations < 0.1 mol L-1 HNO3.
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I will talk about two recent efforts to apply advanced machine learning methods to the electronic structure problem at the density functional theory (DFT) level. First, I will present a machine learning approach based on physics-informed neural networks and neural operators for inverting the Kohn-Sham equations for the exchange-correlation (XC) potential; neural networks provide a new way to perform DFT inversions at scale by learning the mapping from density to potential [1]. Second, I will present a very recent development in which we use neural operators to predict the electron dynamics of systems driven by a laser field. This approach complements conventional numerical solvers and has the potential to enable real-time, on-the-fly modeling of laser-irradiated molecules and materials with varying experimental parameters [2]. Both methods are illustrated on a conceptual level using one-dimensional models of diatomic molecules, but the approach can be readily applied to realistic systems in three dimensions.

[1] V. Martinetto, K. Shah, A. Cangi, A. Pribram-Jones, Mach. Learn.: Sci. Technol. 5, 015050 (2024).
[2] K. Shah, P. Stiller, N. Hoffmann, A. Cangi, arXiv:2210.12522 (2022).

I will present our recent progress in significantly scaling up density functional theory calculations with machine learning [1], for which we have developed the Materials Learning Algorithms (MALA) framework [2]. We have demonstrated the transferability of our machine learning model across phase boundaries, such as metals at their melting point [3] and electronic temperature [4]. In addition, our use of automated machine learning has led to a significant reduction in the computational resources required to identify optimal neural network architectures [5]. Most importantly, I will present our recent breakthrough in enabling fast neural-network driven electronic structure calculations for ultra-large systems unattainable by conventional density functional theory calculations [6]. I will mention in passing our other efforts in solving the Kohn-Sham equations of time-dependent density functional theory in terms of physics-informed neural networks [7], and in developing a robust framework for inverting the Kohn-Sham equations in terms of Fourier neural operators [8].

[1] L. Fiedler, K. Shah, M. Bussmann, A. Cangi, Phys. Rev. Materials, 6, 040301 (2022).
[2] A. Cangi, S. Rajamanickam, B. Brzoza, T. J. Callow, J. A. Ellis, O. Faruk, L. Fiedler, J. Fox, N. Hoffmann, K. D. Miller, D. Kotik, S. Kulkarni, N. Modine, P. Mohammed, V. Oles, G. A. Popoola, F. Pöschel, J. Romero, S. Schmerler, J. A. Stephens, H. Tahmasbi, A. P. Thompson, S. Verma, D. J. Vogel, Materials Learning Algorithms (MALA), doi.org/10.5281/zenodo.5557254, (2023).
[3] J. Ellis, L. Fiedler, G. Popoola, N. Modine, J. Stephens, A. Thompson, A. Cangi, S. Rajamanickam, Phys. Rev. B, 104, 035120 (2021).
[4] L. Fiedler, N. A. Modine, K. D. Miller, A. Cangi, Phys. Rev. B 108, 125146 (2023).
[5] L. Fiedler, N. Hoffmann, P. Mohammed, G. Popoola, T. Yovell, V. Oles, J. Austin Ellis, S. Rajamanickam, A. Cangi, Mach. Learn.: Sci. Technol., 3, 045008 (2022).
[6] L. Fiedler, N. Modine, S. Schmerler, D. Vogel, G. Popoola, A. Thompson, S. Rajamanickam, A. Cangi, npj. Comput. Mater., 9, 115 (2023).
[7] K. Shah, P. Stiller, N. Hoffmann, A. Cangi, Physics-Informed Neural Networks as Solvers for the Time-Dependent Schrödinger Equation, NeurIPS Workshop Machine Learning and the Physical Sciences, arXiv:2210.12522 (2022).
[8] V. Martinetto, K. Shah, A. Cangi, A. Pribram-Jones, Inverting the Kohn-Sham equations with physics-informed machine learning, arXiv:2312.15301 (2023).

The computational design of ionic materials such as ceramics relies on accurate enthalpies. While standard electronic structure approaches based on density functional theory can provide quantitatively accurate results for intermetallic compounds, they fail to yield a proper description of the thermodynamics of ionic materials such as oxides with mean absolute errors for formation enthalipies on the order of several hundred meV/atom. This hinders the materials design of for instance high-entropy ceramics or lower dimensional systems such as 2D oxides.
To address this pressing issue, we have recently developed the coordination corrected enthalpies (CCE) method based on the number of cation-anion bonds and the cation oxidation states. This correction scheme founded on the bonding topology decreases the prediction errors by almost an order of magnitude down to the room temperature thermal energy scale of ~25 meV/atom for oxides, halides, and nitrides. It is also capable of correcting the relative stability of crystal polymorphs. The efficient implementation of this scheme into the AFLOW framework for materials design in the form of the AFLOW-CCE module enables now the correction of enthalpies in large materials databases as well as for the construction of convex hull phase diagrams. These computational advances are thus an important enabler for the design of novel high-entropy ceramics.

Radiotherapy treatment-response of cancer patients can vary considerably, even in patients sharing the same diagnosis. Enhancing the degree of treatment personalization might offer a way towards improving curation rates. The recent advancements in the field of deep neural networks provide new directions for the non-invasive extraction of patient-individual biomarkers when applied on diagnostic imaging data.
Within this thesis, we explored the potential of image-based deep learning as an enabler for individualized therapy.
In a cohort of head and neck cancer patients, we first assessed the suitability of applying convolutional neural networks (CNNs) on pre-treatment computed tomography imaging data for the prediction of loco-regional tumor control in the presence of censored outcomes.
We further investigated whether the predictive performance can be improved through the adoption of multitask learning strategies that combine multiple outcome prediction models and a tumor segmentation task, both for CNNs and the recently emerged vision transformer-based network architectures.
Subsequently, we applied neural networks on multimodal and longitudinal imaging data collected during the course of radiotherapy and evaluated their potential to further improve outcome models.
Finally, in the context of proton-beam radiotherapy of primary brain tumor patients, we applied CNNs for the prediction of the linear energy transfer and examined the feasibility of this approach for estimating treatment-related side-effects considering a variable biological effectiveness of protons.

In order to improve energy and carbon dioxide efficiency of energy intensive industrial processes
the required design optimisations demand simulation tools for reliable predictions of dynamics in gas-
liquid flows. Appropriate modelling strategies always come with a trade-off between precision and
computational cost. In order to account for that, several individual numerical approaches are combined
in hybrid models, one of which is the MultiMorph model [1]. The latter comprises a Volume-of-Fluid
like treatment of large-scale interfaces united with an Euler-Euler model for small-scale dispersed
multiphase structures. The goal is to obtain consistent results across a wide range of spatial resolutions.
In that context, gas-liquid interfaces, being characterised by a shear boundary layer at each of both
sides, inevitably have to be depicted on computational grids with coarse resolution. This requires
adaptive modelling of the momentum exchange across the interface. Coste [2] proposes a model for
interfacial momentum exchange with the interface being smeared across exactly three grid cells by
definition. We propose an extension of the former approach and apply it to the MultiMorph model, in
which the smearing of the interface is not limited to a certain number of grid cells a-priori. The necessary
information from each side of the interface is transported across the interfacial region by means of the
interface transport algorithm of Meller et al. [3]. Results are assessed in several co-current horizontal
channel flows of Fabre et al. [4]. This contributes to numerical modelling with an enhanced predictive
power of gas-liquid interface dynamics in general and of interfacial momentum exchange on coarse
computational grids in particular.

In this presentation, we will discuss on our activities on magnetic soft robots. The focus will be on the possibility to actuate these objects using on-board magnetic coils and sense their state using on-board skin-conformal magnetic field sensors.

The design of novel materials for various scientific and technological purposes has in recent years benefitted from the introduction of data-driven methods. Here, this will be demonstrated for two exemplary materials classes.
While two-dimensional (2D) materials are traditionally derived from bulk layered compounds bonded by weak van der Waals (vdW) forces, the recent surprising experimental realization of non-vdW 2D compounds obtained from non-layered crystals [1] foreshadows a new direction in 2D systems research. We present several dozens of candidates of this novel materials class derived from applying data-driven research methodologies in conjunction with autonomous ab initio calculations [2,3]. Surface passivation of these systems can be used to control their magnetic state and eventually even to induce ferromagnetism [4]. The candidates thus exhibit a wide range of appealing electronic, optical, and magnetic properties making them an attractive platform for fundamental and applied nanoscience.
Also high-entropy materials have recently attracted significant interest due to their favorable mechanical, catalytic, and electronic properties. For the actual design of high-entropy materials, predictive synthesizability descriptors such as the disordered enthalpy-entropy descriptor (DEED) [5] are crucial prerequisites. We present an extensive validation of the predictive power of this approach and its prospective combination with enthalpy corrections for ionic materials [6]. These findings might thus pave the way towards an efficient computational design of high-entropy compounds for extreme conditions.

[1] A. Puthirath Balan et al., Nat. Nanotechnol. 13, 602 (2018).
[2] R. Friedrich et al., Nano Lett. 22, 989 (2022).
[3] T. Barnowsky et al., Adv. Electron. Mater. 9, 2201112 (2023).
[4] T. Barnowsky et al., Nano Lett. 24, 3874 (2024).
[5] S. Divilov et al., Nature 625, 66 (2024).
[6] R. Friedrich et al., npj Comput. Mater. 5, 59 (2019).

The design of novel materials for various scientific and technological applications has in recent years benefitted from the introduction of data-driven methods. Here, this will be demonstrated for two exemplary materials classes.

While two-dimensional (2D) materials are traditionally derived from bulk layered compounds bonded by weak van der Waals (vdW) forces, the recent surprising experimental realization of non-vdW 2D compounds obtained from non-layered crystals [1] foreshadows a new direction in 2D systems research. We present several dozens of candidates of this novel materials class derived from applying data-driven research methodologies in conjunction with autonomous ab initio calculations [2,3]. Surface passivation of these systems can be used to control their magnetic state and eventually even to induce ferromagnetism [4]. The candidates thus exhibit a wide range of appealing electronic, optical and magnetic properties making them an attractive platform for fundamental and applied nanoscience.

Also high entropy materials have recently attracted significant interest due to their favorable mechanical, catalytic, and electronic properties. High-entropy ceramics consist of an ordered anion sublattice of carbon, nitrogen or oxygen and a disordered cation sublattice maximizing configurational entropy by randomly occupying it by five or more cation species (transition metal elements). The reliable computational modelling of such systems can be realized by expanding it into a large ensemble of ordered structures [5]. For the actual realization of high-entropy materials, predictive synthesizability descriptors such as the entropy-forming ability (EFA) [6] and the disordered enthalpy-entropy descriptor (DEED) [7] are crucial prerequisites. We present here extensive results validating the predictive power of these approaches. These findings thus pave the way towards an efficient computational design of high-entropy compounds for extreme conditions.

[1] A. Puthirath Balan et al., Nat. Nanotechnol. 13, 602 (2018).
[2] R. Friedrich et al., Nano Lett. 22, 989 (2022).
[3] T. Barnowsky et al., Adv. Electron. Mater. 9, 2201112 (2023).
[4] T. Barnowsky et al., Nano Lett. 24, 3874 (2024).
[5] K. Yang et al., Chem. Mater. 28, 6484 (2016).
[6] P. Sarker et al., Nat. Commun. 9, 4980 (2018).
[7] S. Divilov et al., Nature 625, 66 (2024).

Mineral dissolution is an important process that occurs in both natural as well as anthropogenic processes. The kinetics of such dissolution processes are influenced not only by the characteristics of the solution but also by the characteristics of the minerals, such as crystal defects on the microscopic scale or macroscopic features such as the intersection of crystal planes to form edges and corners. Macroscopic features are known to increase the population of steps and kinks that may, in turn, affect the dissolution rate over time. Hence, this study presents a 3D empirical dissolution model aimed at examining the time-series evolution of macroscopic features together with the corresponding changes in the dissolution rate under far from equilibrium batch reactor conditions. The developed empirical model is based on the mineral geometry (surface topography and volume) derived from X-ray computed tomography (CT) measurements. The macroscopic features are identified using surface curvature which are then used to generate reactivity maps for dissolution model. As a study case, the dissolution of monomineralic galena (PbS) in ethaline and iodine as oxidizing agent is experimentally observed and then modelled. The model is then applied to seven particles of various shapes and sizes. The finding suggests that the surface reactivity increases over time as the particle shrinks and the macroscale steps and edges become dominant over the initial terraces. This implies that the persistent highly reactive surface sites defined by a particle’s geometry may play a dominant role in the overall particle dissolution in addition to the dissolution mechanisms typically studied on near atomic-flat surfaces. The model developed in this investigation offers the opportunity to be extended providing the possibility of simulating the dissolution of multi-mineral particles during batch dissolution experiments.

This contribution will demonstrate an interactive open-access GUI that aims to standardize a protocol to plan and to assess the feasibility of CT experiments. This standardization promotes quality assurance and improves comparability of laboratory source CT images obtained in different facilities.
The planning of a CT experiment consists of converging the preliminary knowledge about the sample with the technique requirements in order to answer specific scientific questions. This often involves combining the expertise of a “User” and a “CT expert”. The User is an expert in a specific field of science related to the sample and has formulated specific scientific questions or hypothesis that may be answered using CT. The CT expert is a person with advanced knowledge of CT, who does not necessarily have an in-depth knowledge about the specific field of science related to the experiment.

In 1889 the German poet and novelist Theodor Fontane wrote the popular literary ballad “Herr von Ribbeck auf Ribbeck im Havelland.” The Squire von Ribbeck is described as a gentle and generous person, who often gives away pears from his pear trees to children passing by and continued donating pears after his death. Now, 135 years later the rock called Ribbeck is giving us insight into processes that happened 4.5 billion years ago.
The meteorite Ribbeck (official find location: 52°37’15"N, 12°45’40"E) fell January 21, 2024, and has been classified as a brecciated aubrite. This meteoroid actually entered the Earth's atmosphere at 00:32:38 UTC over Brandenburg, west of Berlin, and the corresponding fireball was recorded by professional all sky and video cameras. More than 200 pieces (two proved by radionuclide analysis to belong to this fresh fall) were recovered totaling about 1.8 kg. Long-lived radionuclide and noble gas data are consistent with long cosmic ray exposure (55-62 Ma) and a preatmospheric radius of Ribbeck between 10 and 30 cm.
The heavily brecciated aubrite consists of major (76±3 vol%) coarse-grained FeO-free enstatite (En99.1Fs<0.04Wo0.9), with a significant abundance (15.0±2.5 vol%) of albitic plagioclase (Ab95.3 An2.0Or2.7), minor forsterite (5.5±1.5 vol%; Fo99.9) and 3.5±1.0 vol% of opaque phases (mainly sulfides and metals) with traces of nearly FeO-free diopside (En53.2Wo46.8) and K-feldspar (Ab4.6Or95.4). The rock has a shock degree of S3 (U-S3), and terrestrial weathering has affected metals and sulfides, resulting in the brownish appearance of rock pieces and the partial destruction of certain sulfides already within days after the fall.
The bulk chemical data confirm the feldspar-bearing aubritic composition. Ribbeck is closely related to the aubrite Bishopville. Ribbeck does not contain solar wind implanted gases and is a fragmental breccia. Concerning the Ti- and O-isotope compositions, the data are similar to those of other aubrites. They are also similar to E chondrites and fall close to the data point for the bulk silicate Earth (BSE).
Before the Ribbeck meteoroid entered Earth’s atmosphere, it was observed in space as asteroid 2024 BX1. The aphelion distance of 2024 BX1’s orbit lies in the innermost region of the asteroid belt, which is populated by the Hungaria family of minor planets characterized by their E/X-type taxonomy and considered as the likely source of aubrites. The spectral comparison of an average large-scale emission spectrum of Mercury converted into reflectance and of the Ribbeck meteorite spectrum does not show any meaningful similarities.

Using advanced in situ transmission electron microscopy, we study the lithiation and delithiation processes into graphene sheets and detect significant differences in the structural evolution of the system. Thin fcc lithium crystals with faceted shapes are formed between
graphene sheets during lithiation, but are transformed into irregular patches during delithiation. We find that defects such as vacancies in graphene and impurity atoms play the key role in these processes. Specifically, during intercalation the lithium crystals nucleate at vacancies in graphene, while upon delithiation the impurity oxygen atoms initially embedded at octahedral interstitial positions inside the lithium crystals agglomerate at the edges of the crystals, thus giving rise to the formation of amorphous lithium oxide patches, where lithium ions are trapped.

Femtosecond laser-induced ultrafast magnetization dynamics are all-optically probed for different remanent magnetic domain states of a [Co/Pt]22 multilayer sample, thus revealing the tunability of the direct transport of spin angular momentum across domain walls. A variety of different magnetic domain configurations (domain wall origami) at remanence achieved by applying different magnetic field histories are investigated by time-resolved magneto-optical Kerr effect magnetometry to probe the ultrafast magnetization dynamics. Depending on the underlying domain landscape, the spin-transport-driven magnetization dynamics show a transition from typical ultrafast demagnetization to being fully dominated by an anomalous transient magnetization enhancement (TME) via a state in which both TME and demagnetization coexist in the system. Thereby, the study reveals an extrinsic channel for the modulation of spin transport, which introduces a route for the development of magnetic spin-texture-driven ultrafast spintronic devices.

Perpendicular magnetic anisotropy thin film systems are well known for their periodic magnetic stripe domain structures. In this study, we focus on investigating the behavior of [Co(3.0 nm)/Pt(0.6 nm)]X multilayers within the transitional regime from preferred in-plane to out-of-plane magnetization orientation. Particularly, we examine the sample with X = 11 repetitions, which exhibits a remanent state characterized by a significant presence of both out-of-plane (OOP) and in-plane (IP) magnetization components, here referred to as the “tilted” stripe domain state. Vector vibrating sample magnetometry and magnetic force microscopy are used to investigate this specific sample and its unusual out-of-plane reversal behavior. Through experimental data analysis and micromagnetic simulations of the tilted magnetization system, we identify a single point of irreversibility during an out-of-plane external magnetic field sweep. This behavior is qualitatively similar to the reversal of a Stoner-Wohlfarth particle or of an IP magnetized disk with remanent vortex structure, since both show distinct points of irreversibility as well. Such a collective response to an external field is typically not observed in conventional OOP or IP systems, where the reversal process often involves independent nucleation, propagation, and annihilation of individual domains. Finally, we show that our findings are not at all restricted to Co/Pt multilayers, but are a quite general feature of transitional in-plane to out-of-plane magnetization systems.

2D magnetic materials hold substantial promise in information storage and neuromorphic device applications. However, achieving a 2D material with high Curie temperature (T_C), environmental stability, and multi-level magnetic states remains a challenge. This is particularly relevant for spintronic devices, which require multi-level resistance states to enhance memory density and fulfil low power consumption and multi-functionality. Here, the synthesis of 2D non-layered triangular and hexagonal magnetite (Fe₃O₄) nanosheets are proposed with high T_C and environmental stability, and demonstrate that the ultrathin triangular nanosheets show broad antiphase boundaries (bAPBs) and sharp antiphase boundaries (sAPBs), which induce multiple spin precession modes and multi-level resistance. Conversely, the hexagonal nanosheets display slip bands with sAPBs associated with pinning effects, resulting in magnetic-field-driven spin texture reversal reminiscent of “0” and “1” switching signals. In support of the micromagnetic simulation, direct explanation is offer to the variation in multi-level resistance under a microwave field, which is ascribed to the multi-spin texture magnetization structure and the randomly distributed APBs within the material. These novel 2D magnetite nanosheets with unique spin textures and spin dynamics provide an exciting platform for constructing real multi-level storage devices catering to emerging information storage and neuromorphic computing requirements.

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

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

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

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

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

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

Detecting near-infrared (NIR) light with high efficiency is crucial for photodetectors that are applied in optical communication systems. Si hyperdoped with deep-level impurities provides a monolithic platform for infrared optoelectronics with room-temperature operation at telecommunication wavelengths. In this work, we present strongly enhanced NIR absorption via the hybridization between plasmon resonance and mid-gap states in Au-hyperdoped Si layers, prepared by ion implantation and pulsed laser melting. The Au-hyperdoped Si layers exhibit high-quality recrystallization with the substitution of Au atoms into the Si matrix and the formation of Au nanoclusters on the surface. Surprisingly, the Au-hyperdoped Si layers exhibit a NIR absorption with spectral response extending up to 1650 nm and maximum absorptance up to 30%. According to the electromagnetic simulation, the enhanced infrared photoresponse can be attributed to the mid-gap states induced by substitutional Au atoms and the localized surface plasmon resonance associated with the Au nanoclusters. This work presents a simplified one-step process to gain significant enhancement of NIR absorption, which paves a way for the realization of Si-based photodetectors with room-temperature operation and outstanding performance.

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

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

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

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

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

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

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

The first Sino-German workshop on "Deep-sea mining of massive sulfides: balancing impacts
on biodiversity and ecosystem, technological challenges and law of the sea" took place from
September 17 to September 23, 2023 in Changsha, Hunan Province, China. Four themes were
covered by 20 impulse talks, (1) seabed resources and mineralization systems, marine geology
and geochemistry, (2) microbiology and marine ecology, (3) deep-sea mining technology,
mineral processing and extractive metallurgy, and (4) law of the sea and international law
applicable to the marine environment in Areas Beyond National Jurisdiction, respectively.
In round table discussions, the interdisciplinary understanding deepened regarding (i) the
distribution of submarine massive sulfides (SMS), their formation mechanisms and the
abundance of SMS resources, (ii) the biodiversity linked to SMS and hydrothermal vents and
the environmental protection requirements, (iii) the challenges of mining technology and
processing of SMS, as well as (iv) the legal framework, the regulatory challenges, the
international environmental liability regime and due diligence obligations for commercial
seabed mining.
The participants covered all four themes and are affiliated with various universities, research
institutions, and governmental geoscientific authorities from China (seven) and Germany (six).
During the workshop, a number of recommendations to ISA were defined regarding
environmental, methodological, technical, and legal issues.

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

Siderophores, a group of small, yet diverse biomolecules secreted by a variety of microorganisms, are a promising compound group for the selective recovery of metals. Although their primary role is in the sequestration of iron, their chemical nature allows for the chelation of other metals. To this date, more than 500 structurally different siderophores have been identified. Based on this diversity, siderophores typically exhibit varying affinities for target metals.

Germanium represents a critical element used in various high-tech applications, such as thin films, fiber optics, or optical lenses. The wastewaters generated in the production process of germanium-containing technologies often still contain small amounts of the metal, which due to low concentrations present typically cannot be reclaimed utilizing conventional recycling technologies. The application of siderophores in a bio-based recycling approach might pose a viable solution to this challenge.

This work applied density functional theory to screen the compound group of siderophores for biomolecules exhibiting high selectivity towards germanium. Applying this approach, agrobactin, a catecholate-type siderophore, has been identified as a promising complexing agent for the selective recovery of germanium. The production of the siderophore by A. radiobacter B6 has been optimized, followed by solid phase extraction and purification of the biomolecule. The selectivity of agrobactin towards Ge was tested utilizing HPLC. Subsequently, the selective extraction of the metal from a complex solution was attempted.

Showing the suitability of agrobactin for the selective recovery of germanium opens the way to the application of siderophores for the selective recycling of a wide array of further critical metals, thus aiding in securing their future supply.

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