Publications Repository - Helmholtz-Zentrum Dresden-Rossendorf

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.

Partial disordering of Fe60Al40 thin films was achieved during neon ion irradiation through nanosphere shadow masks or by adjusting the ion energy for near-surface penetration only. Both approaches lead to adjacent chemically disordered and ordered areas. The magnetic behaviour of the films reveals a low-magnetization and high-coercive chemically ordered phase (non-irradiated ferromagnetic area, NIFM), as well as a high-magnetization and low-coercive chemically disordered phase (irradiated ferromagnetic area, IMF). It was shown that the modulated films of coexisting magnetic phases do not lead to an exchange coupling in most cases. Evidence for exchange-spring behaviour, however, was found. Moreover, both magneto-structural phases show at low temperatures spin-glass like properties.

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.

MOTIVATION:

Patients with locally advanced non-small-cell lung cancer (NSCLC) have
a high risk of developing distant metastases. It was shown that
immunotherapy after radiochemotherapy significantly improves the
prognosis. Therefore, biomarkers to identify such patients are
urgently needed. Here, we investigated the prognostic utility of total
tumor burden (TTB) in NSCLC for prediction of distant metastases.

METHODS:

Altogether, 165 patients (65+/-9)y, 100m) with newly diagnosed NSCLC
were included. All patients received FDG-PET/CT prior to definitive
radiochemotherapy. In the PET images, the metabolically active volume
(MTV) of the primary tumor and of all FDG avid lymph nodes was
delineated with an adaptive threshold method. TTB was computed as the
cumulative volume of primary tumor and lymph nodes. Survival analysis
with respect to freedom from distant metastases (FFDM) was performed.
RESULTS:

Survival analysis revealed MTV and TTB as prognostic factors for FFDM
(P=0.004 and P<0.001, respectively). Hazard ratio (HR) for TTB was
significantly higher than HR for MTV (1.9 vs. 2.5, P=0.007).

CONCLUSIONS:

In the investigated group of patients, the inclusion of lymph nodes
into MTV computation significantly increased the prognostic value of
FDG-PET. Further investigations are necessary to confirm these
preliminary results.

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.

Magnetic properties of the crystal are determined by its magnetic symmetry group. A large number of antiferromagnets (AFMs) provides a variety of such symmetry-driven features as magnetoelectricity, spin canting, staggered spin-orbit torques and others [1]. Recent advances in experimental techniques, such as magnetotransport [2] or Nitrogen vacancy magnetometry [3] open a possibility of exploring the surface properties of AFMs. Still, many properties of AFM surfaces remain to be understood.

Here, we study the nominally compensated side crystallographic cuts (m and a planes) of Cr2O3. We show that a finite magnetic moment per unit area at these surfaces is caused by the surface magnetic point symmetry of these cuts and can be explained in terms of the homogeneous Dzyaloshinskii-Moriya interaction (DMI) corresponding to this symmetry. We found, that the m-plane Cr2O3 surface behaves as a canted ferrimagnet with finite out-of-surface magnetization caused by the spin canting and in-plane magnetization along the c axis due to inequivalent magnetic sublattices. The a-plane Cr2O3 surface behaves as a canted 4-lattice sublattice AFM with out-of-plane magnetization [4].

By means of ab initio calculations, we study the change of the magnetic properties from the surface to bulk and quantify the surface-symmetry-driven DMI at Cr2O3 surface cuts to be of order of 1 mJ/m2. The respective spin canting is about 0.5°. The finite out-of-plane magnetization is detected by means of magnetotransport. We found the non-trivial dependency of the magnetotransport response on temperature, which indicates the thermodynamic properties of the surface-symmetry-driven DMI due to contributions of the single-ion anisotropy and antisymmetric exchange [4]. Our findings could be further applied for studies of the surface magnetic responses in other types of AFMs [5] and be used for the electric readout of the collinear AFM states.

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.

Understanding spin-lattice interactions in antiferromagnets is a critical element of the fields of antiferromagnetic spintronics and magnonics. Recently, coherent nonlinear phonon dynamics mediated by a magnon state were discovered in an antiferromagnet. Here, we suggest that a strongly coupled two-magnon-one phonon state in this prototypical system opens a novel pathway to coherently control magnon-phonon dynamics. Utilizing intense narrow-band terahertz (THz) pulses and tunable magnetic fields up to μ_0 H_ext = 7 T, we experimentally realize the conditions of magnon-phonon Fermi resonance in antiferromagnetic CoF2. These conditions imply that both the spin and the lattice anharmonicities harvest energy from the transfer between the subsystems if the magnon eigenfrequency f_m is half the frequency of the phonon 2f_m = f_ph. Performing THz pump-infrared probe spectroscopy in conjunction with simulations, we explore the coupled magnon-phonon dynamics in the vicinity of the Fermi-resonance and reveal the corresponding fingerprints of nonlinear interaction facilitating energy exchange between these subsystems.

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.

An emerging biomarker of blood-brain barrier (BBB) permeability is the time of exchange (Tex) of water from the blood to tissue, as measured by multi-echo arterial spin labeling (ASL) MRI. This new non-invasive sequence, already tested in mice, has recently been adapted to humans and optimized for clinical scanning time. In this study, we studied the normal variability of Tex over age and sex, which needs to be established as a reference for studying changes in neurological disease. We evaluated Tex and cerebral blood flow (CBF) in 209 healthy adults between 26 and 87 years, over age and sex, using general linear models in gray matter, white matter, and regionally in cerebral lobes. Results demonstrated that both gray matter (GM) and white matter (WM) BBB permeability was higher with higher age (Tex lower by 0.42 ms per year in GM, p=0.025, and by 0.49 ms in WM, p=0.009, corrected for sex), with the largest Tex difference in the frontal lobes (0.64 ms decrease per year, p=0.011). CBF was lower with higher age in the GM (0.72 ml/min/100g per year, p<0.001). The CBF findings of this study are in line with previous studies, demonstrating the validity of the new sequence. The BBB water permeability variation over age and sex described in this study provides a reference for future BBB research.

Optimization of large-scale multiphase processes requires adequate and efficient CFD-tools.

Large scales flow behavior depend on sub-grid physical phenomena that have to be described by closure models.
Different models necessary for dispersed particles and separated continuous phases (interfacial drag etc.)
Applications: Flow patterns in horizontal pipes, separation processes in rectification columns, stirred tank reactors etc.

Industrial wastewaters are secondary sources of many critical and base metals. Recovering these metals from such waste streams helps in resource recycling and reduce the environmental burden. Low concentration of target metals and high concentration of unwanted metals makes such a recovery challenging. Ion flotation is a promising separation and recovery process in this regards. The use of various flotation agents is well documented, yet there is a high demand for new flotation agents. The new ion flotation agents need to be highly selective, efficient, and environmentally friendly. Microbial biomolecules are an attractive alternative and we are exploring various biomolecules in this regards. The critical metal complexing ability and interfacial properties of these biomolecules are unknown, which needs to be deciphered to fill the knowledge gap and develop the fundamental understanding required to develop the process and improve efficiency. This perception will allow to fully embrace the potential of novel bio-ion collectors in developing a highly synergistic process of bioionflotation for recovery of critical metals.

Industrial wastewaters are secondary sources of many critical and base metals. Recovering these metals from such waste streams helps in resource recycling and reduce the environmental burden. Low concentration of target metals and high concentration of unwanted metals makes such a recovery challenging. Ion flotation is a promising separation and recovery process in this regards. The use of various flotation agents is well documented, yet there is a high demand for new flotation agents. The new ion flotation agents need to be highly selective, efficient, and environmentally friendly. Microbial biomolecules are an attractive alternative and we are exploring various biomolecules in this regards. The critical metal complexing ability and interfacial properties of these biomolecules are unknown, which needs to be deciphered to fill the knowledge gap and develop the fundamental understanding required to develop the process and improve efficiency. This perception will allow to fully embrace the potential of novel bio-ion collectors in developing a highly synergistic process of bioionflotation for recovery of critical metals.

In this study, we provide an insight on the use of biosurfactants and amphiphilic siderophores as green flotation reagents with a focus on the dynamic surface tension, foamability and foam characterization as well as influence of metal ions on these properties followed by flotation studies for selective separation of metals. The results provide the basis for application of these biomolecules as green flotation reagents in bioionflotation for recovery of critical metals from wide range of secondary sources such as industrial wastewaters, leachates, mine waters, etc. Moreover, the resulting eco-friendly technology will boost resource efficiency, increase recycling rate, reduce waste, reduce critical metal dependency on non-EU countries and proliferate circular economy in EU.

Mining activities and the processing of ores have left a legacy of contamination of the environment. Soluble uranium(VI) species can migrate into surrounding aquifers and soils, thus represent a significant human health risk. Conventional technologies based on physicochemical treatments are traditionally used to remediate these contaminated environments. However, these approaches are cost-intensive and ineffective for low uranium concentrations. A promising method to support and outperform chemical treatments is the bioremediation with the help of magnetotactic bacteria, like Magnetospirillum magneticum AMB-1. A combination of transmission electron and fluorescence microscopy as well as various spectroscopic techniques, e.g. cryo-time resolved laser-induced fluorescence (TRLFS) and in-situ attenuated total reflection Fourier-transform infrared (ATR FT-IR) spectroscopy, revealed that Magnetospirillum magneticum AMB-1 cells are able to bind high amounts of uranium. Already in the first hours of exposure uranium is bound in the cell wall over a wide pH range showing a stable immobilization of uranium. Parallel factor analysis of the TRLFS spectra highlights that peptidoglycan, as one of the cell wall´s ligands, plays the main role in absorbing uranium. The formation of three characteristic species were proved. This insights about magnetotactic bacteria are new and unexpected in this type of Gram-negative bacteria.
A further outstanding feature is the formation of nanoscopic magnetic crystals within the cell of magnetotactic bacteria, which makes them suitable for simple mechanical separation processes. In combination with the magnetic properties of these bacteria, a simple technical water purification process could be realized not only for uranium, but probably also for other heavy metals with the objective of potential industrial applications in the field of microbiological purification of water.

Ion flotation process offers a sustainable way to separate and recycle critical metals from industrial wastewaters that often have low concentrations of target metals. There is a high demand for new flotation reagents which are preferentially environmentally friendly. Microbial biomolecules are an attractive alternative and we are exploring various biomolecules in this regards. The use of these biomolecules as flotation reagents in the ion flotation process can be termed as ‘bioionflotation’. This biotechnological approach for metal recovery from low concentrated waters is still dawning and more research is required to improve the selectivity and process efficiency. In this work, marinobactin (a suite of amphiphilic siderophores) was investigated as a flotation reagent for the separation of Gallium (Ga) from synthetic solutions. Amphiphilic nature of these siderophores and metal complexation ability make them an interesting molecule for an application in the flotation process. Single metal flotation test suggested the Ga recovery and marinobactin-Ga complexation in the collected concentrates was confirmed by HPLC. Further, effects of various operating parameters on the metal recovery and selectivity were studied. The flotation results of the mixed metal solutions (containing Ga and As at 1 mM concentration), showed 88% of Ga recovery and 11% of As recovery, at 0.25 mM marinobactin concentration at pH 4 and air flow rate of 20 ml/min. These results provide the basis to fully embrace the potential of novel bio-ion collectors in developing a highly synergistic process of bioionflotation for recovery of critical metals from low concentrated wastewater.

Graphene and its derivatives such as graphene oxide (GO) are looked upon as the next wonder material due to its unique physiochemical properties - transparency, density, electric and thermal conductivity, elasticity, flexibility, hardness, and capacity to generate chemical reactions with other substances. This has allowed potential applications of graphene in electronics, aviation, medicine, and much more. The findings were of such high impact that the discovery of the material also paved the way for the Nobel Prize. GO is particularly popular among graphene-based materials (GBMs) for its easier and inexpensive manufacture. The consumption of GBM is expected to increase in the future due to its integration into various technical products. In this context, we acknowledge the useful properties of new material, but we should also consider life cycle analysis, the fate, and safety assessment of the environment and human health of GBM before over-exploitation. The over-exploitation of wonder material of the 19th century, plastic and now dealing with hazardous effects, should be the case in point. Thus, the biodegradation of GBMs is a relevant topic to study further for maximizing the societal beneficiary use of this novel material.
Many environmental bacterial strains have been isolated and characterized from hydrocarbon and metal-contaminated sites. These bacterial strains seem to thrive in toxic environments. We hoped to utilize such strains to break down GBMs and transform them into less harmful biodegradable by-products.

In recent decades, sustainability has emerged as a central theme in addressing future uncertainties, intertwined with discourses on ecology, conservation, resilience and socio-ecological justice. While much scholarly attention has focused on sustainability in industrial production, design, global development and lifestyles, the relationship between sustainability and basic research remains underexplored. This paper addresses this gap by examining how sustainability concerns are integrated into scientific practice, specifically within basic research in science and engineering. Through a collaborative ethnographic research process within an interdisciplinary initiative at the University of Technology Dresden, we explore how sustainability and basic research can inform one another. Our analysis draws on qualitative methods, including interviews and group discussions and is grounded in perspectives from sociology, anthropology and Science and Technology Studies (STS), particularly valuation studies. We investigate the various meanings of sustainability as invoked in the appraisal and evaluation of basic research, pursuing the question: What is valued when basic research is deemed ‘sustainable’? Our findings are organized around four central themes: sustainability as efficiency, sustainability through flexibility, sustainability assessment as estimation and sustainability assessment as finding leverage. These themes reveal the complexities and challenges of appraising basic research in terms of sustainability.

Numerous natural substances have anti-cancer properties. Especially indigenous people use aqueous plant extracts for tea or ointments including Dioscorea sansibarensis Pax to treat various diseases. The aim of this study was to evaluate the cytotoxic and radiosensitizing potential of aqueous extracts from Dioscorea sansibarensis Pax collected from Kenya in a panel of HPV-negative and -positive head and neck squamous cell carcinoma (HNSCC) cells grown in three-dimensional laminin-rich extracellular matrix (3D lrECM). The results show cytotoxicity, radiosensitization and increased levels of residual double strand breaks (DBS) by Dioscorea sansibarensis Pax extracts in HPV-negative and -positive HNSCC models in a concentration- and cell model-dependent manner. Application of ROS scavengers indicated an association between ROS-induced DSB and radiosensitization through Dioscorea sansibarensis Pax pretreatment. High-performance liquid chromatography-tandem mass spectrometry (HPLC-MS/MS) based characterization of Dioscorea sansibarensis Pax identified the main components of the extract including camptothecin. Overall, Dioscorea sansibarensis Pax aqueous extracts alone and in combination with X-ray irradiation showed effective anticancer properties, which are worthy of further mechanistic investigation.

Pancreatic stellate cells (PSCs) in pancreatic adenocarcinoma (PDAC) are producing extracellular matrix, which promotes the formation of a dense fibrotic microenvironment. This makes PDAC a highly heterogeneous tumor-stroma driven entity, associated with reduced perfusion, limited oxygen supply, high interstitial fluid pressure, and limited bioavailability of therapeutic agents. In this study, spheroid and tumor xenograft co-culture models of human PSCs and PanC-1 cells were characterized radiopharmacologically using a combined positron emission tomography (PET) radiotracer approach. [18F]FDG, [18F]FMISO, and [18F]FAPI-74 were employed to monitor metabolic activity, hypoxic metabolic state, and functional expression of fibroblast activation protein alpha (FAPalpha), a marker of activated PSCs. In vitro, PanC-1 and co-culture spheroids demonstrated comparable glucose uptake and hypoxia, whereas FAPalpha expression was signifi-cantly higher in PSC spheroids. In vivo, glucose uptake as well as the transition to hypoxia was comparable in PanC-1 and co-culture xenograft models. In mice injected with PSCs FAPalpha ex-pression decreased over a period of four weeks post-injection, which was attributed to the suc-cessive death of PSCs. In contrast, FAPalpha expression increased in both PanC-1 and co-culture xenograft models over time due to invasion of mouse fibroblasts. The presented models are suitable for subsequently characterizing stromal cell-induced metabolic changes in tumors using noninvasive molecular imaging techniques.

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.

Tetravalent actinides (An(IV)) widely occurs in the nuclear fuel cycle. For example, Pu(IV) and Th(IV) are the main species of these elements there, while U(IV) is also employed to reduce extractable Pu(IV) to unextractable Pu(III) in the PUREX process [1]. Therefore, the An(IV) chemistry needs to be understood in depth.
Previously, we have reported that An(IV) (An = Th, U, Np) commonly form sparingly soluble compounds with double-headed 2-pyrrolidone derivatives (L), (HL)2[An(NO3)6] (L = 14Cy and 12Cy, Fig. 1) in 3 M HNO3(aq) [2-3]. Based on these results, we have proposed an advanced principle for nuclear fuel reprocessing, namely NUuclear fuel MAterials selective Precipitation (NUMAP). In connection with this, we have preliminarily studied Ce(IV) as an inactive simulant of Pu(IV). However, Ce(IV) shows much different chemistry from that of An(IV), where [Ce2(μ-O)(NO3)6(14Cy)2]n including a [Ce-O-Ce]6+ motif is formed despite high acidic system with 3 M HNO3(aq) due to its strong hydrolysis tendency (Table 1) [4-5]. Up to now, Pu(IV) is known to exhibit both possibilities to form [Pu(NO3)6]2− and [Pu-O-Pu]6+ in crystal structures [6-7]. Therefore, we wonder which (HL)2[Pu(NO3)6] or [Pu2(μ-O)(NO3)6(L)2]n is preferred to be taken by Pu(IV) under presence of L in 3 M HNO3(aq). This makes critical difference in chemical stoichiometry of the Pu(IV) deposit for its recovery in the NUMAP reprocessing; the Pu:L mole ratio is 1:2 in (HL)2[Pu(NO3)6], while 1:1 in [Pu2(μ-O)(NO3)6(L)2]n. To answer this question, we have prepared Pu(IV)-nitrato complexes with L from HNO3(aq), and determined molecular and crystal structures of them as well as those of M(IV) analogues (M = Ce, Th, U).

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.

In some locations around the globe, the U concentrations may exceed WHO standards by 2-folds therefore, effective yet environmentally wise solutions to purify radioactive waters are of significant importance. Here, the optimized and fully controlled coal-fly-ash based Na-P1 zeolite functionalization by employing novel, biodegradable biosurfactant molecule - cocamidopropyl betaine (CAPB) is showcased. The zeolite’s surface decoration renders three composites with varying amounts of introduced CAPB molecule (Na-P1 @ CAPB), with 0.44, 0.88, and 1.59-times External Cation Exchange Capacity (ECEC). Wet-chemistry experiments revealed extremely high U adsorption capacity (qmax = 137.1 mg U/g) unveiling preferential interactions of uranyl dimers with CAPB molecules coupled with ion-exchange between Na+ ions. Multimodal spectroscopic analyses, including FourierTransformed Infra-Red (FT-IR), X-ray Photoelectron (XPS), and X-ray Absorption Fine Structure (XAFS), showed the hexavalent oxidation state of U, and no secondary release of the CAPB molecule from the composite. The EXAFS signals fingerprint changes in the interatomic distances of adsorbed U, showing the impact of the O and N, heteroatoms present in the CAPB molecule on U binding mechanism. The presented research outcomes showcase the easy, scalable, optimized, and environmentally friendly synthesis of biofunctional zeolite effectively purifying the real-life U-bearing wastewaters from the vicinity of the Pribram deposit (Czech Republic).

The impulse of the Fourth Industrial Revolution is triggering the demand for few specific metals. These include copper, silver, gold, and platinum group metals (PGMs), with important applications in renewable energies, green hydrogen, and electronic products. However, the continuous extraction of these metals is leading to a rapid decline in their ore grades and, consequently, increasing the environmental impact of extraction. Hence, obtaining metals from secondary sources, such as waste electrical and electronic equipment (WEEE), becomes imperative for both environmental sustainability and ensuring availability. This recovery entails few problems such as allocation due to the simultaneous production of several metals, the use of non-renewable resources, and the exergy destruction during the life cycle of the metals. Therefore, this work analyses the waste printed circuit boards (PCBs) recycling process by proposing different exergy-based cost allocations for the mentioned metals, disaggregating the exergy cost into non-renewable and renewable, and considering the complete life cycle of metals with the Circular Thermoeconomics methodology. The results show a significant saving of non-renewable energy by using renewable energies in primary extraction (67-87%), recycling (97.6-98.5%), and renewable energies in recycling (98.7%, 99.0%), compared to conventional primary extraction. However, when considering the entire life cycle, between 47% and 53% of the non-renewable exergy is destroyed during recycling. Therefore, delaying recycling as much as possible would be the most desirable option for maximizing the use of non-renewable resources, which nature cannot replace in a short time.

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.

Personalized treatment strategies based on non‑invasive biomarkers have potential to improve
patient management in patients with newly diagnosed glioblastoma (GBM). The residual tumour
burden after surgery in GBM patients is a prognostic imaging biomarker. However, in clinical patient
management, its assessment is a manual and time‑consuming process that is at risk of inter‑rater
variability. Furthermore, the prediction of patient outcome prior to radiotherapy may identify
patient subgroups that could benefit from escalated radiotherapy doses. Therefore, in this study,
we investigate the capabilities of traditional radiomics and 3D convolutional neural networks for
automatic detection of the residual tumour status and to prognosticate time‑to‑recurrence (TTR)
and overall survival (OS) in GBM using postoperative [11C] methionine positron emission tomography
(MET‑PET) and gadolinium‑enhanced T1‑w magnetic resonance imaging (MRI). On the independent
test data, the 3D‑DenseNet model based on MET‑PET achieved the best performance for residual
tumour detection, while the logistic regression model with conventional radiomics features performed
best for T1c‑w MRI (AUC: MET‑PET 0.95, T1c‑w MRI 0.78). For the prognosis of TTR and OS, the
3D‑DenseNet model based on MET‑PET integrated with age and MGMT status achieved the best
performance (Concordance‑Index: TTR 0.68, OS 0.65). In conclusion, we showed that both deep‑
learning and conventional radiomics have potential value for supporting image‑based assessment
and prognosis in GBM. After prospective validation, these models may be considered for treatment
personalization.

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.

The Puga valley, in Ladakh, contains one of India’s most prospective geothermal systems. Substantial geophysical and geochemical research has been conducted to characterise this system, though uncertainties regarding the subsurface reservoir’s geometry and permeability structure remain a barrier to its development. In this contribution, we aim to fill some of these knowledge gaps by integrating new geological data and structural analyses with previously published geochemical and geophysical interpretations, and derive an integrated conceptual model of the geothermal system. Using digital outcrop techniques and field mapping, we identify and characterise several important structures (faults and foliations) that facilitate fluid flow in the otherwise impermeable Tso Morari gneiss. Petrological and field evidence for outcropping hydrothermally altered lithologies, that may have formed in a geothermal system analogous to the active one, are also presented. Based on these observations, and a simplified finite-element model, we suggest that tectonic and topographic stresses likely control reservoir architecture and connectivity. Lastly, we caution that geomorphological evidence for neotectonic movement on faults at Puga indicate the need for seismic hazard assessment prior to exploitation of the geothermal system, and identify potential parallels between Puga and the Yangbajing geothermal field in China.

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.

The application of shape memory materials is based on a reversible martensitic transformation, which changes structure and microstructure. All applications like high stroke actuation, sensing, energy-efficient ferroic cooling, and energy harvesting, benefit from a high cycle frequency, as this allows for high power density. For this, thin films are of particular interest as their high surface-to-volume ratio enables fast heating and cooling. However, up to now the influence of fast heating and cooling on the martensitic microstructure is unknown. Here we examine the influence of flash lamp annealing on epitaxial Ni-Mn-Ga films. Single-crystalline films are suitable as a model system since they allow for an undisturbed, well-ordered hierarchical martensitic microstructure after slow cooling. We examine all levels of this twin-within-twins microstructure by a combination of XRD, (FIB-) SEM and FIB-TEM before and after flash lamp annealing with a duration of 3 ms at different energy densities. We observe substantial changes at all levels of twinning, which we attribute to the finite time available to form a hierarchical microstructure and the thermal stress between film and substrate.

Shape memory alloys have a wide range of applications, including high stroke actuation, energy-efficient ferroic cooling, and energy harvesting. The use of these alloys is based on a reversible martensitic transformation, which leads to a complex microstructure in the martensitic state. Understanding the formation of this microstructure after fast heating and cooling is crucial, since all above mentioned applications benefit from a high cycle frequency, as it allows a high power density. Here, to study the formation of the martensitic microstructure after fast heating and cooling, we use epitaxial Ni-Mn-Ga film as a model system, since the high surface-to-volume ratio of thin films enables rapid heating and cooling. Furthermore, the formation of a multi-level hierarchical microstructure after slow cooling of this material system is well understood. We apply a millisecond flash lamp pulse on Ni-Mn-Ga films and analyse the hierarchical martensitic microstructure after the flash lamp pulse at different energy densities. We observe substantial changes compared to slow cooling, which we attribute to the limited time available for the microstructure to form and to the thermal stress between film and substrate during rapid temperature changes.

The magnetic damping of Ni80Fe20 (Permalloy, Py) thin films is studied via frequency-dependent ferromagnetic resonance (FMR) experiments. The thickness of the Py films is kept constant and they are all protected from oxidation by an identical 5-nm-thick Al cap layer. To separate the Py film from the oxidic sapphire substrates a systematic variation of the thickness of an additional Al spacer layer was carried out. Py sandwiched in Al exhibits a low, purely Gilbert-like magnetic damping when the Al spacer layer thickness is kept below 3 nm. Above this thickness the magnetic damping is strongly increased due to a pronounced two-magnon contribution. A detailed investigation of the temperature dependence as well as full angular dependence of the FMR allows for correlating the magnetic properties of the Py with the microscopic structural properties of the films as studied by x-ray reflectivity and transmission electron microscopy. It turns out that the detrimental twomagnon processes are activated by an island-like growth of the Al spacer layers, which leads to rough, wavy interfaces with characteristic length scales of the order of ten nanometers. Nevertheless, for Al spacer layers with a thickness below 3 nm a low, purely Gilbert-like magnetic damping can be observed.

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.

Various concepts for the final disposal of spent nuclear fuel are under discussion. In addition to the direct disposal of spent fuel, there are reprocessing concepts in which separated spent fuel components such as fission products and actinides require a suitable host matrix. Options for the immobilization of specific radionuclides are vitrification into a glass material or embedding into a ceramic matrix [1]. We have examined various ceramic materials (zirconia, (ZrO2 and YSZ), zircon (ZrSiO4), monazite (LaPO4) and pyrochlore (Gd2Zr2O7)) with regard to their suitability as host materials for actinides and lanthanides. Th(IV), U(IV), Eu(III) and Ce(IV) were incorpo-rated into the host lattices. The host material must fulfill various requirements. (1) There must be a sufficiently high solubility of actinides and lanthanides in the host lattice without causing phase separation. (2) The host material must have a high temperature stability (up to 1200K) without phase transitions, as this could result in mechanical stresses and fractures which may re-duce the resistance to leaching. (3) The material must be able to withstand the pressure in the ge-ological formation and also the pressure that can be generated by He gas due to alpha decay (up to 10 GPa). (4) The structure of the host lattice must be able to withstand the recoil effects of al-pha decay. Systematic investigations of these aspects were carried out in the frame of an inter-disciplinary project by using synchrotron diffraction techniques available at the Rossendorf Beamline (ROBL) at ESRF. The following is an overview of the main results.
ZrO2 with low dopant concentrations shows a phase transition from the monoclinic (m-ZrO2) to the tetragonal (t-ZrO2) phase both at elevated temperatures and upon irradiation, which characterize it as less suitable as a host material. If the t-ZrO2 and the cubic (c-ZrO2) phases are stabilized for ambient conditions, e.g. by doping with yttrium (YSZ) [2], the ceramic becomes resistant in presence of Th(IV) to high temperature and pressure [3]. The structure also maintains its integrity under irradiation [4]. Synthetic monazite shows remarkable amorphization of the structure under irradiation [5], but has the tendency to recrystallize easily [6]. This is also ob-served in U(IV) and Th(IV) containing natural monazites. A solid solution of Th(IV) pyrochlore results in the formation of Gd2-xThxZr2O7+x/2. Th(IV) replaces Gd(III) due to the similar ionic ra-dius and thus requires charge compensation. The pyrochlore structure retains its integrity under high temperature and pressure conditions [7]. Zircon, ZrSiO4, with incorporated Th(IV), shows excellent stability at high pressure and temperature [8]. However, the synthesis is complicated because a phase separation of (Th,Zr)SiO4 and ThO2 easily occurs.
Based on these studies we can classify the suitability of these ceramics as host materials. We have further developed diffraction techniques for the targeted analysis under the above mentioned conditions. This project is fully supported by BMBF grant 02NUK060 (AcE).
[1] R. C. Ewing, W. J. Weber, F. W. Clinard, Progress in Nuclear Energy 29, 63-127 (1995).
[2] V. Svitlyk, S. Weiss, S., C. Hennig, J Am Ceram Soc. 105, 5975-5983 (2022).
[3] V. Svitlyk, S. Weiss, S., C. Hennig, J Am Ceram Soc. 105, 7831-7839 (2022).
[4] V. Svitlyk, L. Braga Ferreira dos Santos, J. Niessen, S. Gilson, J. Marquardt, S. Findeisen, S. Richter, S. Akhmadaliev, N. Huittinen, C. Hennig, J. Synchrotron Rad. 31, 355-362 (2004).
[5] S. E. Gilson, V. Svitlyk, A. A. Bukaemskiy, J. Niessen, T. Lender, G. L. Murphy, M. Henkes, H. Lippold, J. Marquardt, S. Akhmadaliev, C. Hennig, B. Winkler, T. Tonnesen, L. Peters, C. Fischer, N. Huittinen, npj Mat. Degr. Submitted.
[6] T. Lender, G. Murphy, E. Bazarkina, A. Bukaemskiy, S. Gilson,M. Henkes, C. Hennig, A. Kaspor, M. Klinkenberg, K. Kvashnina, J. Marquardt, J. Nießen, L. Peters, J. Poonoosamy, A. Rossberg, V. Svitlyk, N. Huittinen, npj Mat. Degr. Submit-ted.
[7] V. Svitlyk, S. Weiss, G. Garbarino, R. Huebner, A. Worbs, N. Huittinen, C. Hennig, Z. Krist. In press.
[8] V. Svitlyk, S. Weiss, G. Garbarino, S. Shams Aldin Azzam, R. Huebner, A. Worbs, N. Huittinen, C. Hennig, Acta Materi-alia, Submitted.

Electrochemical cells employing Sodium (Na) and Zinc (Zn) electrodes and a chloride salt electrolyte have been imaged by neutron radiography during cycling. The use of such abundant raw materials confers a very low energy-normalised cost to the Na-Zn system, but its operation requires them to be entirely molten, and therefore to be operated at 600 °C. To suppress the self-discharge that results from this all-molten configuration, porous ceramic diaphragms are used to partition the electrolyte and thereby impede the movement of the Zn2+ ions responsible towards the Na electrode. Neutron images reveal large gas bubbles trapped beneath these diaphragms, formed during the cell fabrication process due to the large volume change that accompanies melting/solidifying of the electrolyte. Cycling data confirm that these bubbles interfere with cell operation by substantially increasing ohmic resistance. They indicate the need for either a new diaphragm design, or a cell fabrication process that prevents their formation in the first instance.

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/)

Glutamine (Gln) is a nonessential amino acid that is involved in the development and progression of several malignancies, including prostate cancer (PCa). While Gln is nonessential for normal prostate epithelial cells, PCa cells become highly dependent on an exogenous source of Gln. The Gln metabolism in PCa is tightly controlled by well-described oncogenes such as MYC, AR, and mTOR. These oncogenes contribute to therapy resistance and progression to the aggressive castration-resistant PCa. Inhibition of Gln catabolism impedes PCa growth, survival, and tumor-initiating potential while sensitizing the cells to radiotherapy. Therefore, given its significant role in tumor growth, targeting Gln metabolism is promising for developing new therapeutic strategies. Ongoing clinical trials evaluate the safety and efficacy of Gln catabolism inhibitors in combination with conventional and targeted therapies in patients with various solid tumors, including PCa. Therefore, understanding how tumor cells interact with their microenvironment will facilitate the clinical translation of Gln inhibitors and help improve therapeutic outcomes. This review focuses on the respective roles of Gln in PCa progression and therapy resistance and provides insights into current clinical trials.

This paper shown that millisecond annealing effectively suppresses the B diffusion in Germanium after ion implantation, and provides much higher activation efficiency of acceptors compared to conventional annealing methods.

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.

Bubble column reactor consisting of a vertical vessel filled with liquid and a gas distributor belongs to the widely-used multiphase reactors. Despite the simple arrangement, the hydrodynamics of bubble columns is very complex due to the interaction and exchange between liquid and gas phases. The mechanism of interphase interaction is affected largely by the flow regime prevailing in the reactor, which may vary from homogeneous-bubbly flow regime, via slug, churn-heterogeneous to annular flow regime. In the homogeneous regime, the interaction between bubbles as well as coalescence and breakup is negligible, which provides well-defined conditions for the investigation of the momentum and turbulence transfer between the bubbles and the liquid. This study discusses the effects of surfactants based on experimental investigations and Computational Fluid Dynamics (CFD) simulations of a homogeneous bubble column, where the bubbles are injected from the column bottom through multiple uniformly distributed orifices.

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.

Semiconducting ternary nitrides are a promising class of materials that have received increasing attention in recent years, but often show high free electron concentrations due to the low defect formation energies of nitrogen vacancies and substitutional oxygen, leading to degenerate n-type doping. To achieve non-degenerate behavior, we now investigate a family of amorphous calcium–zinc nitride (Ca–Zn–N) thin films. By adjusting the metal cation ratios in the films, we demonstrate band gap tunability between 1.4 and 2.0 eV and control over the charge carrier concentration across six orders of magnitude, all while maintaining high mobilities between 5 and 70 cm²/(Vs). The combination of favorable electronic properties, low synthesis temperatures, and earth-abundant elements makes amorphous calcium zinc nitride highly promising for future sustainable electronics. Moreover, the successful synthesis of such materials, as well as their broad optical and electrical tunability, paves the way for a new class of tailored functional materials: amorphous nitride semiconductors – ANSs.

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.
.

Planar Hall magnetoresistive sensors (PHMR) are promising candidates for various magnetic sensing applications due to their high sensitivity, low power consumption, and compatibility with integrated circuit technology. However, their performance is often limited by inherent noise sources, impacting their resolution and overall sensitivity. Here the effect of three bilayer structures NiFe(10 nm)/IrMn(10 nm), NiFe(30 nm)/IrMn(10 nm), and NiFe(30 nm)/IrMn(20 nm) on noise levels is investigated at low-frequency (DC - 100 Hz). This study includes a detailed investigation on the optimization process and noise characteristics of multiring PHMR sensors, focusing on identifying and quantifying the dominant noise sources. The experimental measurements are complemented by a theoretical analysis of noise sources including thermal noise, 1/f noise, intermixing and environmental noise. The best magnetic resolution is observed for the NiFe(30 nm)/IrMn(10 nm) structure, which achieves a detectivity below 1.5 nT/√Hz at 10 Hz in a harsh environment at room temperature. In addition, a substantial improvement in sensitivity is observed by annealing the sensors at 250 °C for 1 hour. The findings of this study contribute to a deeper understanding of noise behavior in PHMR sensors, paving the way for developing strategies to improve their performance for demanding sensing applications at low frequencies.

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).

We study numerically the flow around a spherical droplet set fixed in a linear shear flow over a wide range of external Reynolds numbers ($0.1<\Rey\leq250$, $\Rey$ based on the slip velocity and the viscosity of the external fluid) and drop-to-fluid viscosity ratios ($0.01\leq\mu^\ast\leq100$). The flow structure, the vorticity field, and their intrinsic connection with the lift force are analysed. Specifically, the results on lift force are compared with the low-$\Rey$ solution derived for droplets of arbitrary $\mu^\ast$, as well as prior data at finite $\Rey$ available in both the clean-bubble limit ($\mu^\ast\to0$) and the solid-sphere limit ($\mu^\ast\to\infty$). Notably, at moderately high Reynolds numbers, $\Rey=O(100)$, the lift force exhibits a non-monotonous transition from $\mu^\ast\to0$ to $\mu^\ast\to\infty$, peaking at approximately $\mu^\ast\approx1$. This behavior is related to an internal 3D flow \textcolor{blue}{bifurcation} also occurring under uniform-flow conditions, which makes the flow to evolve from axisymmetric to biplanar symmetric. This flow \textcolor{blue}{bifurcation} occurs at low-but-finite $\mu^\ast$ when the internal Reynolds number ($\Rey^i$, based on the viscosity of the internal fluid) exceeds about 300. In the presence of shear, the corresponding \textcolor{blue}{imperfect bifurcation} enhances the extensional rate of the flow in the wake. Consequently, the streamwise vortices generated behind the droplet can be more intense compared to those behind a clean bubble. Given the close relation between the lift force and the streamwise vorticity, a droplet with $\Rey=O(100)$ and $\mu^\ast\approx1$ typically experiences a greater lift force than that in the inviscid limit.

The buoyancy-driven motion of a deformable bubble rising near a vertical hydrophilic wall is studied numerically. We focus on moderately inertial regimes in which the bubble undergoes low-to-moderate deformations and would rise in a straight line in the absence of the wall. Three different types of near-wall motion are observed, depending on the buoyancy-to-viscous and buoyancy-to-capillary force ratios defining the Galilei ($Ga$) and Bond ($Bo$) numbers of the system, respectively. For low enough $Ga$ or large enough $Bo$, bubbles consistently migrate away from the wall. Conversely, for large enough $Ga$ and low enough $Bo$, they perform periodic near-wall bounces. At intermediate $Ga$ and $Bo$, they are first attracted to the wall down to a certain critical distance, and then perform bounces with a decreasing amplitude before stabilizing at this critical separation. Periodic bounces are accompanied by the shedding of a pair of streamwise vortices in the wake, the formation of which is governed by the near-wall shear resulting from the no-slip condition. These vortices provide a repulsive force that overcomes the viscous resistance of the fluid to the departing motion, making the bubble capable of returning to the region where it is attracted again to the wall. Although periodic, the shedding/regeneration cycle of these vortices is highly asymmetric with respect to the lateral bubble displacements, vortices being shed when the gap left between the bubble and the wall reaches its maximum, and reborn only when this gap comes back to its minimum.

This research shows how environmental impacts of products could be tracked based on semantic data and environmental impact calculations with the example of secondary copper production and the subsequent production of copper alloys, namely bronze and brass, with a focus on greenhouse gas emissions mainly termed as global warming potential (GWP). Utilizing copper scrap and waste printed circuit boards (PCBs) as feed materials, three simulation cases were examined: 100 wt.% copper scrap (CuScrap), a mix of 50 wt.% copper scrap and 50 wt.% PCBs (Mix), and 100 wt.% PCBs (PCBs). The study employed HSC Sim and FactSage software to model the overall process, including shredding, smelting, fire refining, electrorefining and alloying as the main unit processes. Life cycle assessment (LCA) was conducted using OpenLCA software and the ecoinvent 3.8 database to evaluate the environmental impacts comprehensively. The GWP results indicated variations across all the studied cases, with bronze production generally exhibiting higher impacts i.e. 33.46%, 32.33%, and 32.41% for CuScrap, Mix, and PCB cases, respectively, as compared to brass production due to the presence of tin (in bronze) which exhibits 3.7 times higher emissions than zinc (present in brass). The results revealed that emissions from the burning of plastics in PCBs significantly contributed to the overall emissions (e.g. 10.21% in the bronze production in PCB case), highlighting the importance of mitigating measures such as plastic separation prior to the shredding or smelting. Moreover, it was observed that the precious metals present in the PCBs shared a significant portion of the emissions because of their high market value. Overall, the results showed that it is possible to store and track material and its production impacts through multiple process steps based on the processes described by an ontology and assignable impacts.

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.

Isostructural trivalent lanthanide and actinide amidinates bearing the N,N'-bis(isopropyl)benzamidinate (iPr2BA) ligand [LnIII/AnIII(iPr2BA)3] (Ln = La, Nd, Sm, Eu, Yb, Lu; An = U, Np) have been synthesized and characterized in both solid and solu-tion states. All compounds were examined in the solid state utilizing single crystal X-ray diffraction (SC-XRD), revealing a nota-ble deviation in the actinide series with shortened bond lengths compared to the trend in the lanthanide series, suggesting a non-ionic contribution to the actinide–ligand bonding. Quantum-chemical bonding analysis further elucidated the nature of these inter-actions, highlighting increased covalency within the actinide series, as evidenced by higher delocalization indices and greater 5f orbital occupation, except for Th(III) and Pa(III), which demonstrated substantial 6d orbital occupancies. An in-depth paramag-netic NMR study in solution also shed light on the covalent character of actinide–ligand bonding, with the separation of pseudo-contact (PCS) and contact shift (FCS) contributions employing the BLEANEY and REILLEY method. This analysis unveiled signifi-cant contact contributions in the actinide complexes, indicating enhanced covalency in actinide–ligand bonding. To corroborate these observations, an accurate PCS calculation method based on the KUPROV equation, incorporating both the distribution of electronic spin density and magnetic susceptibility obtained from CASSCF calculations, was applied and compared with experi-mental values

Worldwide, substantial amounts of the primary energy converted are lost
as waste heat. Since most of this heat is of low grade, suitable technologies
for conversion into electricity are limited and therefore new ones must be
developed. Here we present our thermoelastic generator for conversion of
low grade waste heat into electricity. It employs two sets of 1mm thick
NiTi wires in a protagonist-antagonist setup. This means, that a portion of
the generated actuation force of the transformation at one side is used to
prestrain the other. First, we present finite element models of the system,
which we used for the optimization of the conversion efficiency. We model the
heat to mechanical energy conversion with a coupling of computational fluid
dynamics, solid mechanics and heat exchange modules in COMSOL Multiphysics
®. From these simulation we derive and present design guidelines
for thermoelastic harvesting systems. Second, we show the simulation and
experimental data of the novel fluid chamber, which enables heat exchanges
rates upwards of 10 Hz, thus increasing the power output of the system.
Third, we present experimental data from the thermoelastic generator itself
and lastly we put shape memory alloy based harvesting into context to other
harvesting technologies and give an overview of the pros and cons of using
shape memory alloys for harvesting low grade waste heat.

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.

The surge in battery demand for both mobility and stationary applications necessitates a critical examination of the environmental impacts associated with battery material production and disposal. Key components such as cathodes, anodes, separators, and electrolytes contribute to environmental degradation throughout their supply chain, emphasizing the urgency for sustainable solutions. Circular economy principles offer a strategic framework for mitigating these impacts by promoting extended product lifecycles and increased utilization of recycled materials. This paradigm shift aims to minimize resource extraction and waste generation, thereby reducing greenhouse gas emissions, toxic exposure, and resource depletion. While challenges persist in achieving perfect circularity due to technical and logistical complexities, embracing the circular economy presents a promising avenue for enhancing sustainability in battery manufacturing and usage. The optimization of hydromechanical Li-ion battery recycling systems involves a multifaceted process encompassing material flow analysis and various mechanical, physical, and metallurgical processing units. The Simulation models utilizing advanced software aid in understanding material composition and flow dynamics, crucial for applying Design for Recycling Principles. Exergy calculation within a thermoeconomic framework further evaluate resource efficiency of the recycling route, and analytical techniques such as ICP-OES and XRD analysis play pivotal roles in identifying complex constituents and guiding process optimization. Regenerated lithium salt assumes integral significance in NMC battery production. This paper underscores the importance of efficient material recovery and recycling in sustainable battery production, emphasizing its critical role in meeting the demands of a greener future.

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.

Antiferromagnetic insulators are a prospective material science platform for magnonics, spin superfluidity, THz spintronics and non-volatile data storage. Due to linear magnetoelectric effect at room temperature, Cr2O3 is a convenient playground to test fundamental predictions and new device ideas. In this presentation, we will cover our activities on physics and applications of Cr2O3. In particular, we discovered a novel surface-symmetry-induced Dzyaloshinskii-Moria interaction at the nominally magnetically compensated crystallographic cuts of Cr2O3, which enables readout of the antiferromagnetic state using magnetotransport measurements [1]. We identified spin Hall magnetoresistance as a possible mechanism to explain all-electric readout of the magnetic state of insulating Cr2O3 interfaced with a heavy metal like Pt. The possibility to read-out the antiferromagnetic order parameter of magnetoelectric Cr2O3 all-electrically enabled realisation of antiferromagnetic magnetoelectric random access memory (AF-MERAM) [2]. Furthermore, we will discuss the family of flexomagnetic effects in Cr2O3 thin films [3]. It is demonstrated that in addition to the conventional magnetic moment induced by the strain gradient, there is another flexomagnetic effect which impacts the magnetic phase transition resulting in the distribution of the Néel temperature along the film thickness. The details on the study of the defect nanostructure in Cr2O3 thin films [4,5] and bulks [6] and their impact on magnetism and magnetoelectricity of Cr2O3 will be discussed as well.

[1] O. V. Pylypovskyi et al., “Surface-Symmetry-Driven Dzyaloshinskii-Moriya Interaction and Canted Ferrimagnetism in Collinear Magnetoelectric Antiferromagnet Cr2O3”. Phys. Rev. Let. 132, 226702 (2024).
[2] T. Kosub et al., “Purely antiferromagnetic magnetoelectric random access memory”. Nature Comm. 8, 13985 (2017).
[3] P. Makushko et al., “Flexomagnetism and vertically graded Néel temperature of antiferromagnetic Cr2O3 thin films”. Nature Comm. 13, 6745 (2022).
[4] I. Veremchuk et al., “Defect nanostructure and its impact on magnetism of α-Cr2O3 thin films”. Small 18, 2201228 (2022).
[5] O. V. Pylypovskyi et al., “Interaction of Domain Walls with Grain Boundaries in Uniaxial Insulating Antiferromagnets”. Phys. Rev. Applied 20, 014020 (2023).
[6] I. Veremchuk et al., “Magnetism and magnetoelectricity of textured polycrystalline bulk Cr2O3 sintered in conditions far out of equilibrium”. ACS Appl. Electron. Mater. 4, 2943 (2022).

Motion sensing is the primary task in numerous disciplines including industrial and soft robotics, prosthetics, virtual and augmented reality appliances. In rigid electronics, rotations, displacements and vibrations are typically monitored using magnetic field sensors. Here, we will discuss on the fabrication of flexible, stretchable and printable magnetoelectronic devices. The technology platform relies on high-performance magnetoresistive and Hall effect sensors either deposited or printed on polymeric foils. These skin conformal flexible and printable magnetosensitive elements enable touchless interactivity with surroundings based on the interaction with magnetic fields. This is relevant for soft robotics [1] and human-machine interfaces based on smart skins [2-4] and smart wearables [5]. In particular, reconfigurable magnetic origami actuators [1] can be equipped with ultrathin and lightweight magnetosensitive e-skins [6], which help to assess the magnetic state of the actuator (magnetized vs. non-magnetized), decide on its actuation pattern and control sequentiality and quality of the folding process. The on-board sensing adds awareness to soft-bodied magnetic actuators enabling them to act and be controlled similar to conventional robotic devices [7]. Magnetic soft robots can be designed to perform complex collaborative tasks being driven using magnetic far fields [1] and near fields [8]. The use of magnetic near fields of on-board electromagnetic coils to drive embedded permanent magnets can provide the demanded tuneability to the mechanical strength of grippers working with objects of different stiffness including biological tissues [9]. Furthermore, we will introduce printed magnetic field sensors that can be flexible [10], stretchable [4], and capable of detection in a broad range of magnetic fields. By an appropriate choice of the polymeric binder, these solution processable magnetoelectronics can self-heal upon mechanical damage [11]. This research motivates further explorations towards the realisation of eco-sustainable magnetoelectronics. To this end, we will discuss biocompatible and biodegradable magnetosensitive devices, which can help to minimise electronic waste and bring magnetoelectronics to new application fields in medical implants and health monitoring.

[1] M. Ha et al., Reconfigurable magnetic origami actuators with on-board sensing for guided assembly. Adv. Mater. 33, 2008751 (2021).
[2] G. S. Canon Bermudez et al., Electronic-skin compasses for geomagnetic field driven artificial magnetoreception and interactive electronics. Nature Electronics 1, 589 (2018).
[3] J. Ge et al., A bimodal soft electronic skin for tactile and touchless interaction in real time. Nature Communications 10, 4405 (2019).
[4] M. Ha et al., Printable and stretchable giant magnetoresistive sensors for highly compliant and skin-conformal electronics. Adv. Mater. 33, 2005521 (2021).
[5] P. Makushko et al., Flexible magnetoreceptor with tunable Intrinsic logic for on-skin touchless human-machine interfaces. Adv. Funct. Mat. 31, 2101089 (2021).
[6] G. S. Canon Bermudez et al., Magnetosensitive e-skins for interactive devices. Adv. Funct. Mater. (Review) 31, 2007788 (2021).
[7] E. S. Oliveros Mata et al., Magnetically aware actuating composites: Sensing features as inspiration for the next step in advanced magnetic soft robotics. Phys. Rev. Appl. (Review) 20, 060501 (2023).
[8] M. Richter et al., Locally addressable energy efficient actuation of magnetic soft actuator array systems. Advanced Science 2302077 (2023).
[9] L. Masjosthusmann et al., Miniaturized Variable Stiffness Gripper Locally Actuated by Magnetic Fields. Advanced Intelligent Systems 2400037 (2024).
[10] E. S. Oliveros Mata et al., Dispenser printed bismuth-based magnetic field sensors with non-saturating large magnetoresistance for touchless interactive surfaces. Adv. Mater. Technol. 7, 2200227 (2022).
[11] R. Xu et al., Self-healable printed magnetic field sensors using alternating magnetic fields. Nature Communications 13, 6587 (2022).

Extending 2D structures into 3D space has become a general trend in multiple disciplines, including electronics, photonics, plasmonics, superconductivity and magnetism [1,2]. This approach provides means to modify conventional or to launch novel functionalities by tailoring curvature and 3D shape of magnetic thin films and nanowires [2,3]. In this talk, we will address fundamentals of curvature-induced effects in magnetism and review the envisioned application scenarios. In particular, we will demonstrate that curvature allows tailoring fundamental anisotropic and chiral magnetic interactions [4] and enables fundamentally new non-local chiral symmetry breaking effect [5,6]. Application potential of geometrically curved magnetic architectures is currently being explored as mechanically reshapeable magnetic field sensors for automotive applications, memory, spin-wave filters, high-speed racetrack memory devices, magnetic soft robotics [7] as well as on-skin interactive electronics relying on thin films [8,9,10] as well as printed magnetic composites [11,12] with appealing self-healing performance [13].

[1] P. Gentile et al., Electronic materials with nanoscale curved geometries. Nature Electronics (Review) 5, 551 (2022).
[2] D. Makarov et al., New Dimension in Magnetism and Superconductivity: 3D and Curvilinear Nanoarchitectures. Advanced Materials (Review) 34, 2101758 (2022).
[3] D. Makarov et al., Curvilinear micromagnetism: from fundamentals to applications (Springer, Zurich, 2022).
[4] O. Volkov et al., Experimental observation of exchange-driven chiral effects in curvilinear magnetism. Physical Review Letters 123, 077201 (2019).
[5] D. D. Sheka et al., Nonlocal chiral symmetry breaking in curvilinear magnetic shells. Communications Physics 3, 128 (2020).
[6] O. M. Volkov et al., Chirality coupling in topological magnetic textures with multiple magnetochiral parameters. Nature Communications 14, 1491 (2023).
[7] M. Ha et al., Reconfigurable Magnetic Origami Actuators with On-Board Sensing for Guided Assembly. Advanced Materials 33, 2008751 (2021).
[8] G. S. Canon Bermudez et al., Magnetosensitive e-skins for interactive devices. Advanced Functional Materials (Review) 31, 2007788 (2021).
[9] J. Ge et al., A bimodal soft electronic skin for tactile and touchless interaction in real time. Nature Communications 10, 4405 (2019).
[10] G. S. Canon Bermudez et al., Electronic-skin compasses for geomagnetic field driven artificial magnetoception and interactive electronics. Nature Electronics 1, 589 (2018).
[11] M. Ha et al., Printable and Stretchable Giant Magnetoresistive Sensors for Highly Compliant and Skin-Conformal Electronics. Advanced Materials 33, 2005521 (2021).
[12] E. S. Oliveros Mata et al., Dispenser printed bismuth-based magnetic field sensors with non-saturating large magnetoresistance for touchless interactive surfaces. Adv. Mater. Technol. 7, 2200227 (2022).
[13] R. Xu et al., Self-healable printed magnetic field sensors using alternating magnetic fields. Nature Communications 13, 6587 (2022).

Curvilinear magnetism is a framework, which helps understanding the impact of geometric curvature on complex magnetic responses of curved 1D wires and 2D shells [1-3]. The lack of the inversion symmetry and the emergence of a curvature induced effective anisotropy and Dzyaloshinskii-Moriya interaction (DMI) stemming from the exchange interaction [4,5] are characteristic of curved surfaces, leading to curvature-driven magnetochiral effects. The exchange-driven chiral effects in curvilinear ferromagnets are experimental observables [6] and can be used to realize low-dimensional architectures with tunable magnetochiral properties based on standard magnetic materials. In particular, magnetochiral responses of any curvilinear ferromagnetic nanosystem are governed by the mesoscale DMI, which is determined via both the material and geometrical parameters [7]. Its strength and orientation can be tailored by properly choosing the geometry, which allows stabilizing distinct magnetic chiral textures including skyrmion and skyrmionium states as well as skyrmion lattices [8-10]. 
Curvilinear sample geometries support novel nonlocal chiral symmetry breaking effect, which manifests itself even in static spin textures [5]. The combined experimental and theoretical study revealed that the nonlocal chiral symmetry breaking is responsible for the coexistence and coupling of multiple magnetochiral properties within the same magnetic object [11]. 
The topology of the geometry of curvilinear magnetic objects sets a strict constraint on the magnetization vector field. For the specific case of soft magnetic wireframe structures, topological properties of their surface determine uniquely the number and type of magnetic solitons [12]. For instance, magnetic N-pods are topologically equivalent to a sphere and hence support N vortices and N-2 antivortices (i.e., 2N-2 magnetic solitons per object). Even more interesting that it is possible to realise objects with topology of N-torus, which can support only one type of magnetic solitons. Yet these are antivortices but not vortices. In 3D geometries, the prevailing type of magnetic solitons is antivortices rather than vortices. For instance, 4-torus supports 6 antivortices only. The key aspect is that these are solitons of the same type which do not annihilate upon interaction. Hence, they are attractive for implementation of reservoir and neuromorphic computing. In particular, the stability of antivortex lattices combined with spin-wave propagation into wireframe structures may be useful for potential application in magnonic-based computing.
These new fundamental discoveries will be covered in this presentation. 

References
[1] D. Makarov et al., Curvilinear micromagnetism: from fundamentals to applications (Springer, Zurich, 2022).
[2] D. Makarov et al., Advanced Materials (Review) 34 (2022) 2101758.
[3] D. D. Sheka et al., Small (Review) 18 (2022) 2105219.
[4] Y. Gaididei et al., Phys. Rev. Lett. 112 (2014) 257203.
[5] D. Sheka et al., Communications Physics 3 (2020) 128.
[6] O. Volkov et al., Phys. Rev. Lett. 123 (2019) 077201.
[7] O. Volkov et al., Scientific Reports 8 (2018) 866.
[8] V. Kravchuk et al., Phys. Rev. B 94 (2016) 144402.
[9] V. Kravchuk et al., Phys. Rev. Lett. 120 (2018) 067201.
[10] O. Pylypovskyi et al., Phys. Rev. Appl. 10 (2018) 064057.
[11] O. Volkov et al., Nature Commun. 14 (2023) 1491.
[12] O. Volkov et al., Nature Commun. 15 (2024) 2193.

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).

Skin-friction causes a large portion of energy consumption of water vessels. Air lubrication (the injection of air beneath a ship hull) is a promising technology to reduce frictional resistance and improve energy efficiency in maritime transport. It can lead to significant fuel cost savings of up to 8%, or even 12%. The effectiveness of air lubrication systems is, however, strongly influenced by various factors, including the method of air injection and ship operating conditions. The air injection beneath the ship hull results in one of the three air lubrication regimes: bubble drag reduction (BDR), air layer drag reduction (ALDR), or a transitional state. The present work assesses the capability of the morphology-adaptive MultiMorph method to predict the phenomena related to air lubrication. The method is particularly suitable as it allows to capture instantaneous transitions between different morphologies (bubbles, air layer). It is validated against flat plate experiments featuring various combinations of water velocity and gas flow rate. The application of MultiMorph to a full ship hull geometry is demonstrated.

Establishing accurate chronological frameworks is imperative for reliably identifying lead-lag dynamics within the climate system and enabling meaningful inter-comparisons across diverse paleoclimate proxy records over long time periods. Robust age models provide a solid temporal foundation for establishing correlations between paleoclimate records. One of the primary challenges in constructing reliable radiocarbon-based chronologies in the marine environment is to determine the regional marine radiocarbon reservoir age correction. Calculations of the local marine reservoir effect (ΔR) during deglaciation can be acquired using 14C-independent dating methods, such as synchronization with other well-dated archives. The cosmogenic radionuclide 10Be offers such a synchronization tool. Its atmospheric production rate is affected by the global modulations driven by fluctuations in the cosmic ray influx, caused by variations in solar activity and geomagnetic field strength. The resulting fluctuations in the meteoric deposition of 10Be are preserved in sediments and ice cores and can thus be utilized for their synchronization. In this study, for the first time, we use the authigenic 10Be/9Be record of a Laptev Sea sediment core for the period 8-14 kyr BP and synchronize it with the 10Be records from absolutely dated ice cores. Based on the resulting absolute chronology, a benthic ΔR value of +345±60 14C years was estimated for the Laptev Sea, which corresponds to a marine reservoir age of 848±90 14C years. The ΔR value was used to refine the age-depth model for core PS2458-4, establishing it as a reference chronology for the Laptev Sea. We also compare the calculated ΔR value with modern estimates from the literature and discuss its implications for the age-depth model.

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.

X-ray computed micro tomography (CT) is the main 3D technique for imaging the internal microstructures of samples. Experimental planning is crucial to ensure the adequacy of CT results to answer specific scientific questions, optimizing the use of resources and maximizing the quality of results. Proper planning requires a certain level of expertise in the technique and the details of the specific scientific question to be answered. Notably, potential new CT users who have formulated a scientific question may not have the in-depth knowledge about CT necessary to make a first assessment of whether CT is suitable for their work.
Here, a step-by-step protocol to plan CT experiments and an interactive graphical user interface (XCT-Explorer) are proposed to guide users through the different steps of the protocol and to link the various CT parameters required to perform a scan. The XCT-Explorer can be accessed at https://xct-explorer-v1.streamlit.app/. The protocol is based on the experience gained within the EXCITE community through interactions between facility managers and users from various scientific fields. The planning protocol aims to 1) help potential CT users with limited knowledge of CT (e.g. first-time users) to decide whether CT can answer their scientific question; 2) guide users to decide which parameters are the most appropriate for their sample / problem; 3) facilitate the initial contact between CT provider and new users; and 4) standardize the planning stage of CT experiments as the foundation for FAIR practices.

Bubble column reactors are the most commonly used equipment for generating gas-liquid
reactions and play a vital role in the chemical and process engineering. An understanding of the
hydrodynamics is crucial for controlling the rate of reaction in such devices and for optimizing
their design. On the component-scale the two-fluid model is the state-of-the-art approach, but
relies heavily on the accuracy, performance and generality of closure models. Continuous
efforts to improve these models benefit from the steadily growing amount of validation data
that is generated from experiments.

The Al18F-labeling approach offers a one-step access to radiofluorinated biomolecules by mimicking the labeling process for radiometals. Although these labeling conditions are considered to be mild compared to classic radiofluorinations, improvements of the chelating units have led to the discovery of (±)-H3RESCA, which allows Al18F-labeling already at ambient temperature. While the suitability of (±)-H3RESCA for functionalization and radiofluorination of proteins is well established, its use for small molecules or peptides is less explored. Herein, we advanced this acyclic pentadentate ligand by introducing an alkyne moiety for the late-stage functionalization of biomolecules via click chemistry. We show that in addition to Al18F-labeling, the cyclohexanediamine triazole (CHDT) moiety allows stable complexation of 68Ga and 111In. Three novel CHDT-functionalized PSMA inhibitors were synthesized and their Al18F-, 68Ga-, and 111In-labeled analogs were subjected to a detailed in vitro radiopharmacological characterization. Stability studies in vitro in human serum revealed amongst others a high kinetic inertness of all radiometal complexes. Furthermore, the Al18F-labeled PSMA ligands were characterized for their biodistribution in a LNCaP derived tumor xenograft mouse model by PET imaging. One radioligand, Al[18F]F-CHDT-PSMA-1, bearing a small azidoacetyl linker at the glutamate-urea-lysine motif, provided an in vivo performance comparable to that of [18F]PSMA-1007, but with even higher tumor-to-blood and tumor-to-muscle ratios at 120 min p.i. Overall, our results highlight the suitability of the novel CHDT moiety for functionalization and radiolabeling of small molecules or peptides with Al18F, 68Ga, and 111In and the triazole ring seems to entail favorable pharmacokinetic properties for molecular imaging purposes.

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.

We carry out highly accurate ab initio path integral Monte Carlo (PIMC) simulations to directly
estimate the free energy of various warm dense matter systems including the uniform electron gas
and hydrogen without any nodal restrictions or other approximations. Since our approach is based
on an effective ensemble in a bosonic configuration space, it does not increase the computational
complexity beyond the usual fermion sign problem. Its application to inhomogeneous cases such as
an electronic system in a fixed external ion potential is straightforward and opens up the enticing
possibility to benchmark density functional theory and other existing methods. Finally, it is not
limited to warm dense matter, and can be applied to a gamut of other systems such ultracold atoms
and electrons in quantum dots.

We present two methods for computing the dynamic structure factor for warm dense hydrogen
without invoking either the Born-Oppenheimer approximation or the Chihara decomposition, by
employing a wave packet description which resolves the electron dynamics during ion evolution.
Firstly, a semiclassical method is discussed which is corrected based on known quantum constraints,
and secondly, a direct computation of the density-density response function within the molecular
dynamics. The wave packet models are compared to PIMC and DFT-MD for the static and low-
frequency behaviour. For the high-frequency behaviour the models recover the expected behaviour
in the limits of small and large momentum transfers and show the characteristic flattening of the
plasmon dispersion for intermediate momentum transfers due to interactions, in agreement with
commonly used models for X-ray Thomson scattering. By modelling the electrons and ions on
an equal footing, both the ion and free electron part of the spectrum can now be treated within
a single framework where we simultaneously resolve the ion-acoustic and plasmon mode, with a
self-consistent description of collisions and screening.

Presence of magnetism in potentially altermagnetic RuO₂ has been a subject of intense debate. Using broadband infrared spectroscopy combined with density-functional band-structure calculations, we show that optical conductivity of RuO₂, the bulk probe of its electronic structure, is well described by the nonmagnetic model of this material. The sharp Pauli edge demonstrates the presence of a Dirac nodal line lying 45 meV below the Fermi level. Good match between the experimental and ab initio plasma frequencies underpins weakness of electronic correlations. The intraband part of the optical conductivity indicates Fermi-liquid behavior with two distinct scattering rates below 150 K. Fermi-liquid theory also accounts for the temperature-dependent magnetic susceptibility of RuO₂ and allows a consistent description of this material as paramagnetic metal.

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.