Publications Repository - Helmholtz-Zentrum Dresden-Rossendorf

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

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

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

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

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

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

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

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

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

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

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

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

Experimentelle Bestimmung der Aktivierung von deutschen Druckwasserreaktoren zur Validierung der Aktivitätsberechnungen

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

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

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

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

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

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

The use of metal nanoparticles (NPs) as antimicrobial agents has become a promising alternative to the problem of antibiotic-resistant bacteria and other applications. Silver nanoparticles (AgNPs) are well-known as one of the most universal biocide compounds. However, selenium nanoparticles (SeNPs) recently gained more attention as effective antimicrobial agents. This study aims to investigate the antibacterial activity of SeNPs with different surface coatings (BSA-coated, chitosan-coated, and undefined coating) on the Gram-negative Stenotrophomonas bentonitica and the Gram-positive Lysinibacillus sphaericus in comparison to AgNPs. The tested NPs had similar properties, including shape (spheres), structure (amorphous), and size (50−90 nm), but differed in their surface charge. Chitosan SeNPs exhibited a positive surface charge, while the remaining NPs assayed had a negative surface charge. We have found that cell growth and viability of both bacteria were negatively affected in the presence of the NPs, as indicated by microcalorimetry and flow cytometry. Specifically, undefined coating SeNPs displayed the highest percentage values of dead cells for both bacteria (85−91%). An increase in reactive oxygen species (ROS) production was also detected. Chitosan-coated and undefined SeNPs caused the highest amount of ROS (299.7 and 289% over untreated controls) for S. bentonitica and L. sphaericus, respectively. Based on DNA degradation levels, undefined-SeNPs were found to be the most hazardous, causing nearly 80% DNA degradation. Finally, electron microscopy revealed the ability of the cells to transform the different SeNP types (amorphous) to crystalline SeNPs (trigonal/monoclinical Se), which could have environmentally positive implications for bioremediation purposes and provide a novel green method for the formation of crystalline SeNPs. The results obtained herein demonstrate the promising potential of SeNPs for their use in medicine as antimicrobial agents, and we propose S. bentonitica and L. sphaericus as candidates for new bioremediation strategies and NP synthesis with potential applications in many fields.

Projektvorstellung

Environmental pollution by heavy metals and radionuclides is one of the biggest challenges which have to be solved globally. In the former U mine of the Wismut GmbH Schlema-Alberoda (Saxony, Germany), mine water is pumped to the surface, where it is treated by a conventional water treatment plant since certain amounts of U (1 mg/L) and other water pollutants can still be found despite remediation by flooding. Microbiological studies of the mine water, using 16S rRNA gene sequencing, revealed a microbial community, which is characterized by a relative abundance of indigenous microbial groups with U(VI)-reduction ability (e.g., sulfur- and iron-oxidizing bacteria and sulfate-reducing bacteria). From previous studies it is known that microbial cycling processes have a significant impact on the complete enzymatic reduction of soluble U(VI) to U(V) and U(IV) by the addition of an electron donor in low U contaminated mine water. In our experiments, a set of anoxic microcosms with mine water were supplemented with glycerol (10mM) as electron donor. The monitoring of the redox potential, pH and the concentration of U, Fe, As and SO₄2^- revealed a substantial decrease of the U(VI) concentration of up to 98%, as well as Fe with up to 91% and SO₄2^- up to 88% after four months, accompanied by a significant change of the redox potential. A thermodynamic Eh-pH dominance diagram calculated using Geochemist's Workbench predicted the reduction of U(VI) and the formation of a solid U(IV)-mineral. The black precipitates, which were formed during the experiments, were analyzed spectroscopically. Extended X-ray absorption fine structure (EXAFS) indicates the formation of immobile uraninite as a U(IV) solid phase. By means of high-energy-resolution fluorescence-detected X-ray absorption near-edge structure (HERFD-XANES) it was even possible to identify U(V), a highly unstable intermediate in the reduction of U(VI) to U(IV) and poorly reported in environmental samples. In electron microscopy and energy-dispersive X-ray studies (SEM/EDXS) U(IV) nanoparticles were probably detected on the surface of calcite crystals, which have formed during the reduction experiment.

The results reveal that the indigenous microbial communities in mine waters are able to modify the speciation and redox state of the soluble U(VI) to insoluble U(V) and U(IV). The in-situ biostimulation of microorganisms could thus offer an eco-friendly water remediation strategy for the management of U contaminated mine water through bioreduction and could support chemical on-site mine water treatments.

In the framework of the EU R2CA project the available experimental databases were reviewed to support nuclear power plant safety analyses in SGTR and LOCA domains. The review focused on the phenomena related to fuel failure, fission products release from the fuel rods and activity transport up to the environment. Furthermore, it was shown that the phenomena were covered by different scale facilities and different experimental procedures for several reactor designs and materials. Among the tests several separate effect tests and integral tests are listed and some NPP measurements were also included. It was concluded that the reviewed database, which include more than forty experimental programmes and measurement series can be considered as a reliable basis to support the development and validation of numerical models for SGTR and LOCA safety analyses.

Linear-response time-dependent density functional theory (LR-TDDFT) simulations of disordered extended systems require averaging over different snapshots of ion configurations to minimize finite size effects due to the snapshot-dependence of the electronic density response function and related properties. We present a consistent scheme for the computation of the macroscopic Kohn–Sham (KS) density response function connecting an average over snapshot values of charge density perturbations to the averaged values of KS potential variations. This allows us to formulate the LR-TDDFT within the adiabatic (static) approximation for the exchange–correlation (XC) kernel for disordered systems, where the static XC kernel is computed using the direct perturbation method [Moldabekov et al., J. Chem. Theory Comput. 19, 1286 (2023)]. The presented approach allows one to compute the macroscopic dynamic density response function as well as the dielectric function with a static XC kernel generated for any available XC functional. The application of the developed workflow is demonstrated for the example of warm dense hydrogen. The presented approach is applicable for various types of extended disordered systems, such as warm dense matter, liquid metals, and dense plasmas.

Warm dense matter (WDM)---an extreme state that is characterized by extreme densities and
temperatures---has emerged as one of the most active frontiers in plasma physics and material
science. In nature, WDM occurs in astrophysical objects such as giant planet interiors and brown
dwarfs. In addition, WDM is highly important for cutting-edge technological applications such as
inertial confinement fusion and the discovery of novel materials.
In the laboratory, WDM is studied experimentally in large facilities around the globe, and new
techniques have facilitated unprecedented insights into exciting phenomena like the formation of
nano diamonds at planetary interior conditions [1]. Yet, the interpretation of these experiments
requires a reliable diagnostics based on accurate theoretical modeling, which is a notoriously
difficult task [2].
In this talk, I give an overview of recent promising developments [3] in the field of ab initio
computer simulations of WDM, which open up new avenues for the accurate description of real
materials [4]. Moreover, I show that we can extract key parameters such as the temperature of a
given sample from X-ray Thomson scattering (XRTS) measurements [5] without any models or
approximations [6].

[1] D. Kraus et al., Nature Astronomy 1, 606-611 (2017)
[2] M. Bonitz et al., Physics of Plasmas 27, 042710 (2020)
[3] T. Dornheim et al., Physics Reports 744, 1-86 (2018)
[4] M. Böhme et al., Physical Review Letters 129, 066402 (2022)
[5] R. Redmer and S. Glenzer, Reviews of Modern Physics 81, 1625 (2009)
[6] T. Dornheim et al., Nature Communications 13, 7911 (2022)

The abstract was not required for this event. In the following, a brief description of the lecture content is provided. The lecture covered the following topics: 1) Fundamental mechanisms of potentiometric biosensing based on field-effect transistors (FETs); 2) Overview of FET-sensor evolution leading to the use of extended gate (EG) FET configuration; 3) Detailed comparison between the traditional ISFET/BioFET and EG FET sensor architectures; 4) Application examples of biosensing using FET biosensors with nanoscopic sensing components (Si nanowires); 5) Cost-effective immunosensor realization using of-the-shelf electronic components with sensitivity comparable to state-of-the-art nanostructured FET biosensors; 6) Mechanism of nanoparticle-based amplification of potentiometric response in EG FET biosensors.

The recovery of mineral ores greatly depends on the hydrodynamics in a froth flotation process. Turbulent jets are created inside a froth flotation cell to enhance mixing, and thus improve recovery of mineral particles. Computational Fluid Dynamics (CFD) simulations provide a means to study such two- or three-phase turbulent jet flows by using mathematical models. The purpose of the current work is to validate the Euler-Euler CFD simulations in OpenFOAM using a set of interfacial closure models to predict the behavior of multiphase turbulent jet flows. Previously, simulations using this framework and validations were carried out for bubble columns by Rzehak and Kriebitzsch (2015) and for stirred tanks with solid-liquid flows by Shi and Rzehak (2020). The baseline closure models employed include drag, shear lift, virtual mass, wall forces, and turbulent dispersion forces for the gas-liquid as well as the solid-liquid interactions. In the present contribution, new CFD simulations using this framework are reported and validated with experimental results from Sun and Faeth (1986) for bubbly jets pointing in upward direction, and from Parthasarathy and Faeth (1987) for particulate jets pointing in downward direction. Along the axial and radial direction of the jet, a reasonable agreement is observed between the experimental and simulation results. Extending the scope of the topic, an attempt is made to simulate also three-phase premixed turbulent jets using the individually validated combination of closure models for both gas-liquid and solid-liquid jets jointly in the same simulations. Suitable data to validate the overall closure models for premixed gas-solid-liquid three-phase turbulent jet flows are not available in the literature. Thus, the simulations for three-phase turbulent jets are carried out in the same setup as used previously for the gas-liquid and the solid-liquid turbulent jets. A parametric study is carried out for the interfacial forces and an attempt to understand the interaction between the disperse and accompanying continuous phase will be presented.

The Euler-Euler two-fluid framework is applied here for submerged multiphase gas-liquid and solid-liquid turbulent jets. A set of interfacial closure models that was previously established for Computational Fluid Dynamics (CFD) simulation of different geometries such as bubble columns, pipe flows, and stirred tanks by Rzehak et al. 2017 and Shi & Rzehak 2018, 2020 is employed in the present simulations. The closure models for the momentum exchange comprise of drag-, lift-, wall-, virtual mass-, and turbulent dispersion-forces. The turbulence in the liquid phase is calculated using the 𝑘−𝜔 SST model with additional terms to consider the effects of bubble- and particle-induced turbulence. An open-source CFD tool OpenFOAM, is used to perform these simulations. Validation of the CFD simulations is performed by comparison with the experimental data of Sun & Faeth 1986 for upward pointing gas-liquid jets, and Parthasarathy & Faeth 1987 for downward pointing solid-liquid jets, respectively. The results show that the closure models are able to reasonably reproduce the measured data.

Electronic biosensors based on the extended-gate field-effect transistor (EGFET) concept show great promise for multiplexed biosensing in clinical screening and monitoring of complex diseases at the point of care. These biosensors offer high sensitivity, simplified integration, and easy interfacing with conventional readout electronics. However, EGFET biosensors face practical limitations that hinder their widespread use, such as the need for complex nanostructuring of extended gates (EGs) and FET transducers to achieve ultra-high sensitivity and operate at low current levels (in the ~nA range).
We present a low-cost, standalone, and multiplexed EGFET immunosensor. Our system consists of a disposable sensing chip with an EG electrode array, a multiplexing module that allows reproducible switching between up to 32 EGs, and a readout module built around a commercial FET transducer using off-the-shelf electronic components. We detect the binding of IgG antibodies by indirectly monitoring the gate surface potential, operating the FET transducer in constant charge mode. To achieve high sensitivity levels (approximately 20 mV/dec) and a low detection limit (around 10 fM), comparable to state-of-the-art nanostructured EGFET biosensors, we employ an innovative assay approach. This involves labeling the analyte antibody through bioconjugation with gold nanoparticles (AuNPs), resulting in a detection limit approximately 10^4 times lower than with the gold-standard optical method for the same antibody. Remarkably, our approach leads to a 5-fold amplification of the potentiometric response compared to direct antibody detection without labeling. To understand the origin of this amplification, we analyze the impedimetric response and find that AuNPs exhibit nanoantennae-like behavior, disrupting charge uniformity within the diffusion barrier layer and producing signal amplification. These findings demonstrate the potential for creating a new cost-effective and highly sensitive potentiometric biosensing format by utilizing customized labeling of analyte biomolecules with metallic nanoparticles.

Die Eignung von ¹⁸F (t½ = 110 min) als konservativer Tracer für die Positronenemissionstomographie (PET) sowie seine spezifische Verwendung als reaktiver Tracer werden im Vergleich zu dem bisher nicht untersuchten ⁷⁶Br (t½ = 16,2 h) evaluiert. Der Fokus liegt zunächst auf der Sorptionskinetik an silikatischen und karbonatischen Materialien. Zusätzlich dienen die Untersuchungen zur Einschätzung der praktisch erreichbaren Datenqualität des neuen Tracers.
Ein Phantom (Modellprobe) sowie natürliche Sandsteine wurden hinsichtlich des Transportverhaltens in konstanter Strömung mit den Radiotracern ¹⁸F und ⁷⁶Br untersucht. Unterstützend zu Positronen-Emissions-Tomogrammen mit einer Ortsauflösung von 1,15 mm und einer Zeitauflösung von 2 min wurden μ-CT-Aufnahmen mit Ortsauflösungen bis 15 μm angefertigt, um Informationen über die Porengeometrie zu erhalten.
Mit K[¹⁸F] lassen sich Sorptionseffekte mit Konzentrationen <10 pmol/mm3 (bezogen auf das Ausgangsmaterial) nachweisen. An natürlichem Sandstein konnte anhand der Tracer-Durchbruchskurven gezeigt werden, dass K[⁷⁶Br] das konservative Fließverhalten selbst bei sehr großen Ionenstärken deutlich besser abbildet als K[¹⁸F]. Mit dem reaktiven Tracer ¹⁸F konnte die Bandbreite der Oberflächenreaktivität von Karbonaten in unterschiedlichen Geomaterialien quantifiziert werden.

To clinically evaluate complex diseases at the point of care (POC), it is crucial to have multiplexed quantitative sensing of biomolecules. This need has led to the development of ultra-sensitive and cost-effective biosensors. Electronic biosensors based on extended gate field-effect transistor (EGFET) are promising candidates for multiplexed biosensing due to their excellent sensitivity, facile integration, and straightforward interfacing with the readout electronics. Although some high-performance biosensing applications of EGFET systems have been demonstrated [1,2], current EGFET-based biosensors still need to overcome practical issues to reach broad use in POC settings, such as readout at low current levels (~nA), limited multiplexing ability, and complex customized nanofabrication of FET transducers. We demonstrate a custom standalone multiplexed EGFET-based potentiometric biosensing platform relying on modular electronics constructed with off-the-shelf components and an innovative assay format employing bioconjugates of gold nanoparticles (AuNPs) and antibodies (Abs). Our platform comprises a disposable sensing chip containing an EG electrode array functionalized with bioreceptor molecules, a multiplexing module enabling reproducible scanning of up to 32 electrodes, and a readout module based on a commercial FET operating in constant charge mode to enable indirect monitoring of gate surface potential shifts caused by analyte binding. We observe a remarkable 5-fold amplification of the potentiometric response due to the labeling of target antibodies with AuNPs in comparison with the traditional non-labeled assay. We investigate the amplification mechanism by analyzing and modeling the impedimetric response of the system and propose that AuNPs act as localized regions of high surface charge mediating the diffusion barrier layer disruption. The AuNP-enhanced response brings the sensitivity of our platform to a level comparable with fully customized potentiometric nanobiosensors while avoiding complex nanostructuring processes and enabling accurate readout with conventional electronics. Furthermore, our EGFET-based platform exhibits ~10^4-10^6 times lower detection limits than gold-standard optical methods. Our findings indicate great promise for the development of highly sensitive and low-cost EGFET-based electronic biosensing systems suited for use at the POC.

References

[1] K. Kim et al., Nature Communications, 11 (2020) 119.
[2] H. Kim et al., ACS Nano, 15, 3 (2021) 4054–4065.

Stone tools stratified in alluvium and loess at Korolevo, western Ukraine, have been studied by multiple research groups (Gladilin 1989; Adamenko & Gladilin 1989; Koulakovska et al. 2010) since the site’s discovery in the 1970s. Despite wide acknowledgement of Korolevo’s importance to the European Palaeolithic, age of the lowermost lithic artefacts have remained inconclusive. Here we report ages of 1.37 ± 0.09 million years ago (Ma) and 1.45 ± 0.06 Ma for the sedimentary unit containing Mode-1-type lithic artefacts based on two cosmogenic nuclide burial dating methods (Balco & Rovey 2008; Knudsen et al. 2020). Korolevo stands as the earliest securely dated hominin presence in Europe and bridges the spatial and temporal gap between the Caucasus (~1.8 Ma at Dmanisi) (Ferring et al. 2011) and Iberia (recalculated to ~1.1 Ma at Atapuerca) (Carbonell et al. 2008). Our findings advance the hypothesis of colonisation of Europe from the east, and an analysis of habitat suitability (Timmerman et al. 2022) suggests that early hominins potentially exploited warm interglacial periods to disperse into higher latitudes and relatively continental sites, such as Korolevo, well before the Middle Pleistocene Transition.

Droplet-based lab-on-a-chip systems offer vast possibilities in manipulation, guidance, tracking and labeling of individual droplet-based bioreactors. One of the targeted application scenarios is in drug discovery where millions of unique codes are required, which is out of reach for current technologies. Here, we propose and validate a concept for the realization of multiparametric codes, where information is stored in distinct physical and chemical parameters. Exemplarily we focus on the use of impedance and magnetic sensing by monitoring ionic concentration as well as magnetic content per droplet and droplet volume. Codes based on aqueous ferrofluid droplets were prepared using a tubing-based millifluidic setup and consist of up to 6 droplets of different combinations of volumes and magnetic concentration. We demonstrate that a droplet chain of 3 single droplets of different volume with 9 different magnetic nanoparticle concentrations accompanied with 4 different ionic concentrations per droplet offers up to 3 million unique codes. The developed fluidic platform can be readily extended to other types of sensors including optical ones to boost the coding capacity even further.

We present a multi beam gamma ray computed tomography (CT) scanner design for multi-phase flow investigations in industrial apparatuses. It mainly comprises a collimated 137Cs isotopic source and an in-house developed detector arc with overall 16 scintillation detectors offering a quantum efficiency of approximately 75% and an active area of 10×10 mm² each. The detectors are operated in pulse counting mode to enable gamma photon energy discrimination. A key element for highest flexible application of the proposed CT scanner is the elaborated detector design that is concerted with a sophisticated scanning procedure that allows for multi beam projection acquisition. Thus, scanning times can be adopted to various object sizes to save measuring times while the arrangement of source and detector arc remains identical.

This is a jupyter notebook used to analyze the LWFA plasma lens simulations ran at summit ORNL.

The influence of nanoscale surface topography on protein adsorption is of large importance for numerous applications in medicine and technology. Herein, the adsorption of ferritin at flat and nanofaceted Al2O3 surfaces is investigated by atomic force microscopy and X-ray photoelectron spectroscopy. The nanofaceted surfaces are generated by thermal annealing at temperature above 1000 °C, which leads to the formation of faceted saw-tooth-like surface topographies with perio-dicities of about 160 nm and amplitudes of about 15 nm. Ferritin adsorption at these nanofaceted surfaces is notably suppressed at a concentration of 10 mg/ml, which is attributed to lower ad-sorption affinities of the newly formed facets. Consequently, ferritin adsorption is restricted mostly to the grooves of the saw-tooth patterns, where the proteins can maximize their contact area with the surface. However, this effect depends on the applied protein concentration, with an inverse trend being observed at 30 mg/ml. Furthermore, different ferritin adsorption behavior is observed at topographically similar nanofacet patterns fabricated at different annealing temper-atures and attributed to different step and kink densities. These results demonstrate that while protein adsorption at solid surfaces can be notably affected by nanofacet patterns, fine-tuning protein adsorption in this way requires precise control of facet properties.

The self-assembly of conducting nanostructures is currently investigated intensively in order to evaluate the feasibility of creating novel nanoelectronic devices and circuits using such pathways. In particular, methods based on so-called DNA Origami nanostructures have shown great potential in the formation of metallic nanowires. The main challenge in this method is the reproducible generation of very well-connected metallic nanostructures which may be used as interconntects in future devices. Here we use a novel design of nanowires with a quasi-circular cross-section as opposed to rectangular or uncontrolled cross-sections in earlier studies. We find indications that the reliability of the fabrication scheme is enhanced and the overall resistance of the wires is comparable to metallic nanostructures generated by electrochemistry or top-down methods. In addition, we observe that some of the nanowires are annealed when passing a current through them, which leads to a clear enhancement for the conductance. We envision that these nanowires are providing further steps towards the succesful generation of nanoelectronics using self-assembly.

The SLC3A2 gene encodes for a cell-surface transmembrane protein CD98hc (4F2hc). Together with the light subunits (L-type amino acid transporters) LAT1 (SLC7A5), LAT2 (SLC7A8), and xCT (SLC7A11), CD98hc constitutes heterodimeric transmembrane amino acid transporters. It interacts with other surface molecules such as extracellular matrix metalloproteinase inducer CD147 (EMMPRIN) and integrins. Thus, CD98hc plays an essential role within a protein complex critical for tumor energy metabolism, proliferation, and migration and serves as a vital regulator of the stress response and tumor growth in different types of tumors. The elevated expression levels of CD98hc have been confirmed in various tumor entities, including head and neck squamous cell carcinoma (HNSCC), glioma, colon adenocarcinoma, pancreatic ductal adenocarcinoma and others. Furthermore, a high expression of CD98hc has been linked to prognosis and response to chemo- and radiotherapy. In this mini-review, we discuss the physiological functions of CD98hc, its role in the regulation of tumor stemness, metastasis, and therapy resistance, and the clinical significance of CD98hc as a tumor marker and therapeutic target.

Increasing demand to store intermittent renewable electricity from, e.g., photovoltaic and wind energy has led to much research and development in large-scale energy storage, for example, ZEBRA batteries (Na-NiCl2 solid electrolyte batteries). Replacing Ni with abundant and low-cost Zn makes the ZEBRA battery more cost-effective. However, few studies were done on this next-generation ZEBRA (Na-ZnCl2) battery system, particularly on its AlCl3-NaCl-ZnCl2 secondary electrolyte. Its properties like phase diagrams and vapor pressures are vital for the cell design and optimization. In our previous work, a simulation-assisted method for molten salt electrolyte selection has shown its successful application in molten salt batteries. The same method is used here to in-depth study the AlCl3-NaCl-ZnCl2 salt electrolyte in terms of its phase diagrams and vapor pressures via FactSage and thermo-analytical techniques (Differential Scanning Calorimetry (DSC) and OptiMelt), and their effects on battery performance like operation safety and charging/discharging reaction mechanism. The DSC and OptiMelt results show that the experimental data such as melting temperatures and phase changes agree well with the simulated phase diagrams. Moreover, the FactSage simulation shows that the salt vapor pressure increases significantly with increasing temperature and molar fraction of AlCl3. The obtained phase diagrams and vapor pressures will be used in the secondary electrolyte selection, cell design and battery operation.

Abstract: Pool scrubbing is a widely used technique for retaining aerosol particles. It is characterized by high gas injection flow rates and substantial topological changes in different zones within the scrubber. The scrubbing process is generally divided into injection and swarm zones based on the evolution of the gas-liquid interface topology, and different mechanisms prevail in each zone. The disintegration of large globules in the injection zone forms a swarm of stable bubbles that significantly affect the retention efficiency since scrubbing largely depends on bubble size and velocity. However, the characteristics of the pool scrubbing process, such as high momentum, a wide range of bubble sizes, and complex interactions, make numerical simulations difficult. Turbulence is a key factor affecting bubble breakup, and estimating turbulence parameters properly is essential. In bubble columns, the effect of bubble-induced turbulence is dominant compared to turbulent pipe flows. However, the contribution of shear-induced turbulence is also significant due to circulation and strong oscillation formed in the pool by high-velocity gas injection. Modeling turbulence considering both shear and bubble-induced turbulence is still challenging in multiphase simulations. In this work, two turbulence models (mixtureKEpsilon and k-omega SST) that include the bubble-induced effects in OpenFOAM are evaluated for a pool scrubbing experiment from the literature. Using the two-equation models for turbulence is the widely accepted method in numerical simulations, making the accurate estimation of the turbulence boundary conditions critical. However, most of the correlations developed to estimate the turbulence boundary conditions are for fully developed pipe flow, making it harder to use them for bubble column simulations. Therefore, special attention is paid to characterizing turbulence intensity in a bubble column and estimating inlet boundary conditions for turbulence parameters such as turbulent kinetic energy and energy dissipation. The key parameter in estimating accurate turbulence parameters at the inlet is the turbulent viscosity. It is found that the classical definition of turbulence intensity, as the ratio between fluctuation and mean velocity, leads to an unreasonably large value for bubble column simulations because the mean velocity in the pool is extremely low, consequently, inaccurate estimation of inlet turbulence boundary conditions may result. Therefore, an approach is proposed to estimate the inlet turbulence boundary conditions that satisfy a condition revealed by the sensitivity tests in the current study. According to the results, the turbulent intensity can be estimated by constraining the turbulent viscosity value to be in the range of the molecular viscosity at the inlet if the inlet Reynolds number is in the range of laminar or transitional. Thus, too high or too low values for turbulent viscosity at the inlet may lead to numerical instabilities, considering that both the liquid and gas are quasi-laminar at the inlet.

Transferrin (Tf) is a glycoprotein that transports iron from the serum to the various organs. Several studies have highlighted that Tf can interact with metals other than Fe(III), including actinides that are chemical and radiological toxics. We propose here to report on the behavior of Th(IV) and Pu(IV) in comparison with Fe(III) upon Tf complexation. We first considered UV-Vis and IR data of the M2Tf complex (M = Fe, Th, Pu) and combined experimental EXAFS data with MD models in order to better describe the metallic coordination site. EXAFS data of the first M-O coordination sphere are consistent with the MD model considering 1 synergistic carbonate. Further EXAFS data analysis strongly suggests that contamination by Th/Pu colloids seems to occur upon Tf complexation, but this contamination seems limited. SAXS data have also been recorded for all complexes and also after the addition of DFOB in the medium. The Rg values are very close for apoTf, ThTf and PuTf, but slightly larger than for holoTf. Data suggest that the structure of the protein is more ellipsoidal than spherical, with a flattened oblate form. From this data, the following order of conformation size might be considered : holoTf < M2Tf (M = Th, Pu) < apoTf < M2Tf-DFOB (M = Fe, Th, Pu).

Objectives
Theranostic concepts and the usage of alpha-particle emitting radionuclides belong to the emerging fields of radiopharmaceutical sciences. Especially and due to its excellent complexation properties, the chelator macropa (mcp)[1,2] was reported to be a suitable complexing agent for 225Ac conjugates[3] and as macrocycle a highly promising starting point for the development of 223/224Ra chelators as well. To follow the theranostic approaches with these alpha emitters, due to their chemical similarities 131Ba[4] for SPECT and 133La[5] for PET are available as diagnostic radionuclide surrogates of radium and actinium, respectively. In our recent study, we aim to establish a new workflow to evaluate and predict the complex stability of new chelating systems by obtaining both protonation constants for respective ligands and association constants for their metal complexes starting with mcp.

Methods
As a prerequisite for the calculation of stability constants (log(K)), the protonation constants (pKa) of mcp were determined by pH‑dependent 1H NMR studies in the first step. Based on these obtained data, the europium-mcp-complex was examined using time-resolved, laser-induced luminescence spectroscopy (TRLFS) and the log(K) was calculated as reference stability constant. Additionally, Eu-TRLFS was used to determine the Eu-mcp species during titration and pH-dependency of the complexation. The method of isothermal titration calorimetry (ITC) was used to measure the complex stability constants of La-, Ba-mcp-complex, as well as Eu-mcp-complex to value the results in comparison with TRLFS data. The evaluation and calculation of the log(K) values were carried out by parallel factor analysis (PARAFAC).

Results
Depending on the protonation ability of the functional groups found in mcp (amines and carboxylates), pKa values were obtained as well as the log(K) values for the respective mcp-complexes with Ba, Eu and La and are shown in Table 1.

Conclusion
By combining 1H-NMR, TRLFS and ITC we demonstrated a new approach to fully characterize the ligand, determine metal complex speciation, pKa values for the mcp chelator and log(K) values of the mcp complexes and agree with previous works by potentiometric titration. Furthermore, this method can be transferred to functionalized and improved chelators and their complexes with a wide variety of metal ions of radionuclides used in nuclear medicine, especially the heavy alkaline earth metal ions Ba2+ and Ra2+. Ultimately, this allows a reliable comparison of the individual affinities of the different chelators to the metal ions and thus a predictability of the complex stabilities for future radiopharmaceuticals.

Complexes of macrocyclic ligands are commonly utilized in many medicinal applications, such as MRI contrast agents and radiopharmaceuticals. Due to their thermodynamic stability and kinetic inertness, they overcome toxicity of free heavy metal ions and, thus, enable their use in vivo. However, there is no “general” ligand suitable for any metal ion in the periodic table and, thus, useful chelator should be specially designed for each metal ion. Among metal radionuclides, there is an increasing interest in those of large elements (i.e. large metal ions) to be used for both, radiotherapy and imaging. The 18-memberred macrocycles are suitable scaffolds for the utilizations.
This contribution deals with chemistry and radiochemistry of H4pyta (18-py2N4Ac4), a parent rigidified macrocycle suitable for large metal ions. Although the ligand was synthesized in mid-nineties, there are almost no data focused on its possible utilization in radiopharmaceutical context.[2] The ligand forms thermodynamically stable complexes with Ln(III) ions. Its ten donor atoms completely wrap the large Ln(III) ions but one pendant arm is not coordinated for small Ln(III) ions. Thus, the early Ln(III) ions form more stable complexes. The Ln(III)-H4pyta complexes are 2–3 orders of magnitude more kinetically inert than those of H4dota and, thus, they will be fully stable in vivo.
Radiolabeling of H4pyta with 133La and 177Lu is, at different pH’s and temperatures, comparable with that of H4dota. Challenging experiments showed that these radiolabeled H4pyta complexes are fully resistant to transmetallation and transchelation, and show very high stability in human blood serum stability. For larger 133La, the results are much better if compared with data obtained for H4dota and macropa in the parallel experiments. For smaller 177Lu, the results are also more promising compared to those of H4dota and its analogues.
This ligand shows that the H4pyta (18-py2N4Ac4) scaffold offers new possibilities for design of chelators for radioisotopes of large metal ions from the bottom of the Periodic Table, e.g. 225Ac, and the data are promising for future conjugations and in vivo applications.

225Ac-Radiotracer werden mit macropa (mcp) als Chelator bereits in präklinischen Studien für die zielgerichtete Alpha-Therapie verwendet. [1] Mit dem β+-Emitter 133La bildet 225Ac ein „Matched Pair“ gemäß des theranostischen Konzeptes. [2] Ein weiteres „Matched Pair“ bilden der γ-Strahler 131Ba mit 223/224Ra. Obwohl der [131Ba]Ba-mcp-Komplex in vivo eine zu geringe Stabilität aufweist und sich freies Ba2+ in den Knochen einlagert,[3] eignet sich der Ba-mcp-Komplex als Referenz für die Entwicklung verbesserter, mcp-basierter Chelatoren. Assoziationskonstanten, ausgedrückt als logK-Werte, sind ein Maß für die Komplexstabilität. Für deren Bestimmung wurde eigens eine neue Methode entwickelt und sowohl auf mcp als Referenz als auch auf die neuen Chelatoren angewendet.

Methodik/Methods:

Die pKs-Werte der Chelatoren wurden mittels NMR-Spektroskopie bestimmt, da diese zur Berechnung der logK-Werte essentiell sind. Mithilfe der Laser-induzierten Lumineszenzspektroskopie an Europium als Fluorophor (Eu-TRLFS) wurde dann die Bildung des Eu-mcp-Komplexes untersucht, sowie die logK-Werte der mcp-Komplexe mit Ba2+ und La3+ bestimmt. Ergänzend wurde die isotherme Titrationskalorimetrie (ITC) für die Chelatisierung von La, Eu und Ba durchgeführt. Die Berechnung der logK-Werte erfolgte durch parallele Faktoranalyse.

Ergebnisse/Results:

Die pKs-Werte von macropa wurden reproduziert und lieferten logK-Werte der Ba-, Eu- und La-mcp-Komplexe von 10.2, 14.2 bzw. 14.6.

Schlussfolgerungen/Conclusions:

Der neue methodische Ansatz, eine Kombination aus NMR, TRLFS und ITC, wurde erfolgreich etabliert und ermöglicht eine präzise Vorhersagbarkeit der Komplexstabilitäten der modifizierten mcp-Liganden für zukünftige radiopharmazeutische Anwendungen in vivo.

Ziel/Aim:

Der Einsatz von Actinium-225 mit dem DOTA-Konjugat PSMA-617 befindet sich in der klinischen Entwicklung. DOTA ist jedoch nicht ideal, da hohe Temperaturen für die Markierung benötigt werden und der Komplex in vivo nicht stabil genug ist. Ziel ist es, einen besseren, macropa-basierten Chelator zu finden und mit von PSMA-617 abgeleiteten Bindungsvektoren zu verknüpfen.

Methodik/Methods:

Es wurden 4 verschiedene Konjugate hergestellt, welche sich hinsichtlich der Anzahl der Bindungsmotive sowie ihrer Fähigkeit, an Albumin zu binden, unterscheiden. Die Stabilität der markierten Komplexe wurde über 10 Tage in Puffer und Serum untersucht. Weiterhin wurden Bindungsaffinitäten und Koloniebildungsassays an PSMA-positiven LNCaP-Zellen durchgeführt. Alle Konjugate wurden hinsichtlich ihrer Organverteilung in LNCaP-Tumor-tragenden SCID-Mäusen untersucht.

Ergebnisse/Results:

Alle 4 Konjugate wurden unter milden Bedingungen radiomarkiert und zeigen bei Zugabe von Gentisinsäure die höchste Stabilität über 10 Tagen. Die Bindungsaffinitäten der Konjugate wurden als KD-Werte bestimmt und liegen zwischen (10-40) nM. Die Untersuchungen zum Zellüberleben zeigen einen therapeutischen Vorteil der bivalenten gegenüber den monovalenten Konjugaten. Alle vier Konjugate erreichten in unterschiedlichen Zeitspannen (bis 5 d p.i.) Tumoranreicherungen von (12-85) %ID/g. Unerwünschte Anreicherungen traten v. a. bei dem dimeren, albuminbindenden Konjugat in Form von Akkumulationen (Leber, Milz, Nieren) auf.

Schlussfolgerungen/Conclusions:

Die Verwendung von macropa-basierten Konjugaten für die Therapie mit Actinium‑225 oder die zukünftige Bildgebung mit Lanthan‑133 ist vorteilhaft, da die gebildeten Komplexe stabiler sind und damit eine Anreicherung der Aktivität in off-Target-Regionen verringert werden kann. Weiterhin ergibt sich ein Vorteil im Handling, da die Reaktionen schnell und bei Raumtemperatur durchgeführt werden können, was die spätere Umsetzung in eine GMP-gerechte Herstellung erleichtert.

Das prostataspezifische Membranantigen (PSMA) ist ein hoch attraktives biologisches Target für die molekulare Bildgebung und für die zielgerichtete Radionuklidtherapie bei kastrationsresistentem Prostatakrebs (mCRPC), da es in allen Phasen der Erkrankung bei den Tumorzellen expremiert ist. Somit bieten hoch affine, PSMA-bindende Biomoleküle eine exzellente Basis zur Entwicklung von Radiokonjugaten für die Therapie mit Alphastrahlern.
Aufgrund seiner hervorragenden kernphysikalischen Eigenschaften wird zunehmend Actinium-225 für diese Zwecke in der Nuklearmedizin verwendet. Das dreiwertige Kation Ac3+ muss dazu in einem Chelator hoch stabil komplexiert werden. Um das zu realisieren, wird der Chelator macropa verwendet, welcher eine sehr hohe In-vivo-Stabilität zeigt und Radiomarkierungen unter sehr milden Bedingungen zulässt. Dieser wird mit einer bzw. zwei PSMA-bindenden Einheiten modifiziert, um den 225Ac-Komplex zu den Tumorzellen zu bringen.
Zunächst wurden zwei Actinium-225-Radiokonjugate entwickelt und deren pharmakologische Eigenschaften, z. B. die Bindung an Tumorzellen, Anreicherung im Tumor (ca. 10%ID/g für beide Konjugate) und in anderen Organen überprüft. Hier wurde ein ähnliches Verhalten festgestellt, vergleichbar mit dem Standardkonjugat 225Ac-PSMA-617. Die beiden 225Ac-Radiokonjugate wurden weiterentwickelt und mit einem Albumin-Binder (4-Iodphenylbutyrat) versehen. Dadurch wurde eine längere Blutverweilzeit, kombiniert mit einer höheren Aufnahme in den Tumor, erreicht (bis 50%ID/g Monomer, bis 120 %ID/g Dimer), um die Effektivität der Radiotherapie zu erhöhen.

To follow the design of in vivo stable chelating systems for radiometals, a concise and straightforward method toolbox was developed combining NMR, ITC, and Eu-TRLFS. For this purpose, the macropa chelator was chosen and Lu3+, La3+, Pb2+, Ra2+, and Ba2+ as radiopharmaceutically relevant metal ions. They differ in charge (+2, +3) and coordination properties (main group vs. lanthanides). 1H NMR was used to determine four pKa values (carboxylate functions: 2.40 and 3.13; amine functions: 6.80 and 7.73). Eu-TRLFS was used to validate the exclusive existence of the Mn+:ligand 1:1 complex in the chosen pH range. ITC measurements were accomplished to determine the resulting stability constants of the desired complexes with log K values ranging from 18.5 for the Pb-mcp complex to 7.3 for the Lu-mcp complex. DFT-calculated structures nicely mirror the complexes’ order of stabilities by bonding features. Radiolabeling with macropa using ligand concentrations from 10–3 M to 10–6 M pointed out the complex stability (133La > 131Ba > 177Lu).

This paper proposes a new benchmark for VVER-1000 control rod ejection transient. The benchmark is designed for code-to-code comparison and its purpose is testing and verifications of time-dependent solvers, core models and cross section generation methodology. Four solutions obtained using different combinations of three lattice transport, two nodal neutronics, and two thermo-hydraulic codes are analyzed, demonstrating good agreement in predicting transient reactivity and power peaks and highlighting the impact of gas gap modeling and DNBR correlation on simulation results.

The martensitic microstructure decides on the functional properties of shape memory alloys. However, for the most commonly used alloy, NiTi, it is still unclear how its microstructure is built up because the analysis is hampered by grain boundaries of polycrystalline samples. Here, we eliminate grain boundaries by using epitaxially grown films in (111)B2 orientation. By combining scale-bridging microscopy with integral inverse pole figures, we solve the puzzle of the hierarchical martensitic microstructure. We identify two martensite clusters as building blocks and three kinds of twin boundaries. Nesting them at different length scales explains why habit plane variants with 〈011〉B19' twin boundaries and {942} habit planes are dominant; but also some incompatible interfaces occur. Though the observed hierarchical microstructure agrees with the phenomenological theory of martensite, the transformation path decides which microstructure forms. The combination of local and global measurements with theory allows solving the scale bridging 3D puzzle of the martensitic microstructure in NiTi exemplarily for epitaxial films.

Fredo Erxleben vom Helmholtz-Zentrum Dresden-Rossendorf erzählt uns, wie er und seine KollegInnen WissenschaftlerInnen, DoktorantInnen und Postdocs Programmieren beibringt. Der Bedarf an Training ist riesig. Der Bedarf an Ausbildern auch.
In dieser Folge schauen wir ein wenig hinter die Kulissen und Fredo erzählt welche Herausforderungen es bei den Trainingsprogrammen gibt.

Within the extension of the ΛCDM model, allowing for the presence of neutrinos or warm dark matter, we develop the analytical cosmological perturbation theory. It covers all spatial scales where the weak gravitational field regime represents a valid approximation. Discrete particles -- the sources of the inhomogeneous gravitational field -- may be relativistic. Similarly to the previously investigated case of nonrelativistic matter, the Yukawa interaction range is naturally incorporated into the first-order scalar metric corrections.

In this seminar talk, I will introduce applications of fragment molecular orbital method to study the interactions between protein and lanthanide/actinide.

The CFD modelling of annular flow is a challenge since it should take into account the continuous liquid film, the continuous gas core, and the dispersed droplets simultaneously. Recently, the CFD department in Helmholtz-Zentrum Dresden - Rossendorf (HZDR) are developing a morphology adaptive multifield two-fluid model that has great potential to simulate the three structures in a single computational domain. To complete the annular flow simulation in the morphology adaptive framework, a new droplet entrainment model is proposed in this work, which describes the mass transfer from the continuous liquid film to the dispersed droplets. The new entrainment model is developed based on the shear-off mechanism on the interfacial wave, implying that the entrainment behavior is dominated by the shear force and surface tension on the gas and liquid interface. Contrarily to previous entrainment models, the new model is correlated to the local flow parameters on the interface, so that it is suitable for the CFD framework. The properties of the new model are discussed and the model performance is verified by laboratory experiments. Qualitatively, the proposed model can simulate the generation of the interfacial wave from the inlet to the downstream. The droplets are mainly entrained at the front tip of the disturbance wave, where the shear force effect is remarkable. These phenomena are identical to the physical understanding of the droplet entrainment. Quantitatively, the characteristics of the droplet fraction matches the experimental results. The liquid film fraction obtained with the new model is analyzed and compared with the experiment. It turns out that the statistical parameters of film fraction's average value, standard deviation, possibility density function, and power spectral density match well with the experiment. Finally, the model comparisons show that the new model outperforms previous models with regard to droplet generation.

As an excellent demonstration of SRF gun technology, HZDR's SRF Gun-II has been rountinely operated as an electron gun for the ELBE THz radiation and the ELBE neutron source since 2018, delivering CW beams with bunch charges of up to 300 pC at 50-100 kHz.

As is well known, the quality of the photocathodes is crucial for the stability and reliability of the gun operation. Different cathodes have been used in the HZDR SRF gun and the cathodes have been replaced three to four times per year. In the last five years, the quality of the superconducting cavity has remained almost stable, but some characteristics of the gun have been observed related to the cathodes. In this contribution, we will introduce the operational aspect of the photocathodes in HZDR SRF gun, look back at the achievements and discuss open issues and possible improvements for future application.

Superconducting radio frequency photo injectors (SRF gun) offer advantages for operating in continuous wave (CW) mode and generating high-brightness and high-current beams. A new SRF gun is designed as a low emittance photo injector for LCLS-II-HE and a prototype gun is currently being developed under collaboration between SLAC, FRIB, HZDR and ANL. The aim is to demonstrate stable CW operation at a cathode gradient of 30 MV/m.
One of the crucial components for successful SRF gun operation is the photocathode system. The new SRF gun will adopt the HZDR-type cathode, which includes a cathode holder fixture (cathode stalk) developed by FRIB and a cathode exchange system designed by HZDR. This innovative cathode insertion system ensures accurate, particle-free and warm cathode exchanges. A novel alignment process targets the cathode to the stalk axis without touching cathode plug itself.
To commission the prototype gun, metallic cathodes will be used. A specifically designed vacuum system ensures vacuum pressure of 10-9 mbar for transport of a single cathode from the cleanroom to the gun.

The understanding of the contribution of the tumour microenvironment to cancer progression and metastasis, in particular the interplay between tumour cells, fibroblasts and the extracellular matrix has grown tremendously over the last years. Lysyl oxidases are increasingly recognised as key players in this context, in addition to their function as drivers of fibrotic diseases. These insights have considerably stimulated drug discovery efforts towards lysyl oxidases as targets over the last decade.
This review article summarises the biochemical and structural properties of theses enzymes. Their involvement in tumour progression and metastasis is highlighted from a biochemical point of view, taking into consideration both the extracellular and intracellular action of lysyl oxidases. More recently reported inhibitor compounds are discussed with an emphasis on their discovery, structure-activity relationships and the results of their biological characterisation. Molecular probes developed for imaging of lysyl oxidase activity are reviewed from the perspective of their detection principles, performance and biomedical applications.

The compositional, optical and structural stability of transparent conductive oxide SnO₂:Ta (1.25 at.% Ta) thin films at 650 °C and 800 °C in air was studied under isothermal conditions. After the high-temperature treatment, the element composition and the optical spectra of the material were unchanged. The X-ray diffraction confirmed the conservation of a single rutile-type phase. Two strong Raman lines located out of the SnO₂ phonon range indicated point defects in the material, which were identified as Sn vacancies and O interstitials by theoretical calculations. These point defects were partially healed out during the high-temperature treatment, without affecting the transmittance and reflectance of the material. Our study demonstrates an exceptional high in-air stability of Ta-doped SnO₂ and encourages it for applications in fields, where transparent conductive oxides with high-temperature and oxidation stability are required. These are, e.g., selective transmitters for concentrated solar power or electrodes for dye-sensitized solar cells and dynamic random-access memories.

Assuming nonnegligible relativistic component densities alongside the cold dark matter of the ΛCDM model, we reformulate cosmological perturbations within the framework of the cosmic screening approach. The scheme addresses all spatial scales, provided that gravitational interactions may be studied in the weak field limit to a good approximation. As a novel feature of the formulation, delta-shaped sources responsible for the inhomogeneous gravitational field are now allowed to be relativistic so that neutrinos or warm dark matter may also be incorporated into the extended model. Analytical expressions obtained for the first-order scalar potentials reveal that, like in the case of purely nonrelativistic matter studied previously, gravitational interactions of this wider class of components are also characterized by the time-dependent screening length, associated with the exponential cutoff introduced at large distances. (arXiv:2206.13495 [gr-qc])

NiMnGa shape-memory alloys are promising candidates for large strain actuation or magnetocaloric cooling devices. In view of potential small-scale applications, we probe here nanomechanically the stress-induced austenite-martensite transition in single crystalline austenitic thin films as a function of temperature. In 0.5 µm thin films, a marked incipient phase transformation to martensite is observed during nanoindentation, leaving behind pockets of residual martensite after unloading. These nanomechanical instabilities occur irrespective of deformation rate and temperature, are Weibull distributed, and reveal large spatial variations in transformation stress. In contrast, at a larger film thickness of 2 m fully reversible transformations occur, and mechanical loading remains entirely smooth. Ab-initio simulations demonstrate how an in-plane constraint can considerably increase the martensitic transformation stress, explaining the thickness-dependent nanomechanical behavior. These findings give insights into how reduced dimensions and constraints can lead to unexpectedly large transformation stresses in the studied shape-memory Heusler alloy.

Magnetic shape memory alloys exhibit various multifunctional properties, which range from high stroke actuation and magnetocaloric refrigeration to thermomagnetic energy harvesting. Most of these applications benefit from miniaturization and a single crystalline state. Epitaxial film growth is so far only possible on some oxidic substrates, but they are expensive and incompatible with standard microsystem technologies. Here, we demonstrate epitaxial growth of Ni-Mn-based Heusler alloys with single crystal-like properties on silicon substrates by using a SrTiO3 buffer. We show that this allows using standard microfabrication technologies to prepare partly freestanding patterns. Our approach is versatile, as we demonstrate its applicability for the NiTi shape memory alloy and discuss for spintronic and thermoelectric Heusler alloys. This paves the way for integrating additional multifunctional effects into state-of-the-art microelectronic and micromechanical technology, which is based on silicon.

Gravitational clustering of cold dark matter, as predicted by concordance cosmology, is often studied via N-body simulations based on Newtonian dynamics. Though efficient in tracking nonlinear growth of fluctuations at small scales, outcomes of such simulations cannot be linked to observables immediately, and a certain effort is required to obtain relativistic interpretations of variables by employing convenient gauges and dictionaries. Based on a weak-field expansion of general relativity, a fully-relativistic N-body code has been introduced in the past decade (Adamek, J., Daverio, D., Durrer, R., Kunz, M., JCAP 07, 053 (2016)), capable of evolving all metric variables in the Poisson gauge which is the conventional choice in formulating cosmological perturbations. However, spatial and temporal derivates are assigned different orders of smallness and field equations, containing admixtures of higher-order terms, acquire a rather complex form. In this talk we will explore an alternative formulation of perturbations, still based on a weak-field expansion, and expressed in the Poisson gauge, which however treats all derivates on equal footing and hence a clear distinction exists between first and second order contributions in the expansion (Eingorn, M., ApJ 825, 84 (2016), Canay, E., Eingorn, M., PDU 29, 100565 (2020), arXiv:2206.13495 [gr-qc]). We will show that it is possible to obtain analytical solutions for the scalar and vector potentials in this scheme and that they hint at some exciting characteristics of gravitational interactions at large-enough cosmological scales.

We describe multi-quark clusters in quark matter within a Beth-Uhlenbeck approach in a background gluon field coupled to the underlying chiral quark dynamics using the Polyakov gauge. An effective potential for the traced Polyakov loop is used to establish the property of color SU(3) center symmetry as an aspect of confinement.
A higher multi-quark cluster of size $a$ is described as a binary composite of smaller subclusters a1 and a2 (where a1+a2=a) with a bound state and a scattering state spectrum. For the corresponding cluster-cluster phase shifts we use simple ansätze that capture the Mott dissociation of clusters as a function of temperature and chemical potential. We compare the simple "step-up-step-down" model that ignores continuum correlations with an improved model that includes them in a generic form.
In order to explain the model, we restrict ourselves here to the cases where the largest cluster contains six quarks.
One striking result is the suppression of the abundance of colored multi-quark clusters at low temperatures by the coupling to the Polyakov loop. This is understood in close analogy to the suppression of free quark abundances by the same mechanism. We derive here the corresponding Polyakov-generalized distribution functions of b -quark clusters. Another new result is the effective suppression of free quarks by a large (> 600 MeV) constituent quark mass generated by dynamical breaking of the approximate chiral symmetry in the quark sector and its sudden restoration at the Mott temperature, where all hadronic bound states become dissociated into the multi-quark continuum.
Within our approach we calculate thermodynamic properties such as baryon density and entropy. A comparison with lattice calculations shows that our model is able to give a unified, systematic approach to describe properties of the quark-gluon-hadron system.

This is a talk for students of RTG 2767 “Supracolloidal structures” running at the TUD. I will discuss current developments in magnetic composite-based actuators and sensor devices.

Density functional methods have been successfully applied to describe properties of atomic nuclei and infinite nuclear matter. A particularly successful approach for applications in simulations of neutron stars, their mergers and supernova explosions is the relativistic mean field theory with density dependent couplings (DD2). For densities exceeding twice the nuclear saturation density, i.e. for neutron stars heavier than about 1.4 solar masses, the excitation of hyperons and heavy baryons leads to a softening of the nuclear equation of state and a limitation of the maximum neutron star mass to about 2 solar masses (“Berlin wall” constraint, formerly known as the hyperon puzzle), a tension with recent mass measurements.
I will review recent progress to overcome the Berlin wall constraint with quark deconfinement in neutron star interiors, where the dense quark matter equation of state is obtained from a relativistic density functional approach that allows to model quark confinement at low densities as well as color superconductivity and the transition to the conformal symmetric phase at high densities.
On the basis of this new density functional approach to quark matter a supernova explosion mechanism for massive blue supergiant stars has been suggested and a signal of quark deconfinement in the pattern of gravitational waves from binary neutron star mergers.
I shall give an outlook to the development of a unified description of quark-nuclear matter in the form of a density functional approach.

The cosmogenic radionuclide 10Be is used for a variety of applications, its analysis however requires laborious purification methods. We developed a simple purification protocol for Be from sediment samples that works without strongly hazardous chemicals or time consuming and expensive ion exchange columns. The combination of hydroxide precipitations and precipitation in NaHCO3 was compared to an established protocol of hydroxide precipitations and ion exchange columns. The new method has a slightly lower Be-yield and purity of the resulting samples. However, this does not have a significant influence on performance during AMS-measurement where both methods performed equally well. The avoidance of column chromatography reduces sample preparation costs and space requirements in the lab allowing for more samples to be prepared simultaneously.

T-cells genetically modified to express chimeric antigen receptors (CARs) are playing a more and more
important role in targeted cancer immunotherapy. However, these living drugs can also cause lifethreatening
side effects. To overcome such limitations and improve the safety of CAR T-cell therapy,
adaptor CAR platforms such as the universal CAR (UniCAR) have been developed. This platform consists
of the UniCAR T-cell and a target module (TM) cross-linkage effector and tumor cells. Here, we have
established a novel UniCAR system targeting Fibroblast Activation Protein (FAP) that is highly expressed
in the tumor microenvironment of epithelial cancers and a marker for cancer-associated fibroblasts. For
that, we constructed two novel FAP-directed TMs possessing different sizes and pharmacokinetic
properties, in which one is based on a single-chain variable fragment (scFv), and the other is based on an
IgG4 backbone. We have shown that both TMs were able to bind to FAP-expressing cells and redirect
UniCAR T-cells in vitro to monolayer and spheroid target cells inducing effective killing. Furthermore, we
could show infiltration and activation of T-cells in the spheroid setting. Using in vivo models, the TMs were
proven to be suitable to be used for PET imaging showing FAP-specific accumulation at the tumor site.
Moreover, the immunotherapeutic effect of UniCAR T-cells in combination with FAP TMs was
demonstrated using mouse models. In conclusion, in this work, we could show that the two novel anti-
FAP TMs prove to hold great theranostic potential for diagnostic imaging and immunotherapy.

Immunotherapy based on chimeric antigen receptor (CAR) T-cells has demonstrated remarkable therapeutic effects, particularly against some hematological cancers. A versatile adaptor CAR system called RevCAR, consisting of RevCAR T-cells and a bispecific target module (RevTM) has been developed to overcome severe side effects associated with conventional CAR T-cell therapy. As the activity of RevCAR T-cells can be steered based on the availability of RevTM, working as an on/off switch, the system can be immediately turned off if side effects occur. Furthermore, the RevCAR system is highly flexible, since the same RevCAR T-cell can be directed towards different tumor-associated antigens (TAA) simply by adding RevTMs with different specificities. However, the effectiveness of CAR T-cells against solid tumors remains limited particularly due to their immunosuppressive tumor microenvironment (TME). To overcome these hurdles, we have established a novel RevCAR system targeting immune checkpoint molecules such as PD-L1, which are frequently overexpressed by cancer cells to suppress immune responses. We have constructed novel RevTMs that can redirect RevCAR T-cells to kill tumor cells that express such immune checkpoint molecules. Furthermore, true AND gate tumor targeting was achieved by targeting a TAA in addition to PD-L1 in a combinatorial manner using our Dual-RevCAR system. In this way, targeting PD-L1 not only results in Dual-RevCAR T-cell activation but simultaneously blocks the immunosuppressive PD-L1/PD-1 axis. Altogether, we have turned an immunosuppressive marker into an immune-activating signal that might modulate the TME in a beneficial manner, showing promise for the development of an effective immunotherapy against solid tumors.

Engineered T cells that express chimeric antigen receptors (CARs) show a big potential in cancer immunological research. They are synthetic receptors that can target antigens independently from the MHC complex. However, most tumor associated antigens are not only expressed on the tumor site but also on healthy tissues. To switch off CAR T cells in case of on-target/off-tumor effects occur, an adaptor CAR platform, called the universal CAR (UniCAR), was developed. In contrast to conventional CAR systems this platform consists of the engineered T cells and a linker molecule, called target module (TM), that is both binding to the target antigen and recognized by the UniCAR T cell. With this approach there is the possibility to switch the system on and off when needed.
Fibroblast activation protein (FAP) is a protein of high interest in cancer research as it is upregulated in most of epithelial cancers but shows a comparably low expression in healthy tissues. It is shown to be expressed on cancer associated fibroblasts and therefore plays an important role in the tumor microenvironment where it has pro-tumorigenic activity both in the FAP positive and surrounding cells. Given this, the goal of this work was to develop new TMs against FAP.
To achieve such aim, we cloned two TM formats, either based on a single-chain variable fragment (scFv) or an IgG4 based backbone. The difference in the size of the backbones translates into different half-lifes and kinetics. These different TM formats can be used to customize UniCAR therapy according to the given circumstances. We were able to purify and perform various experiments with the mentioned TMs. We could show binding to the target cells using flow cytometry. We could also show that the TMs could be used to induce specific lysis in vitro on monolayer cells and spheroids. We were also able to show UniCAR T cell infiltration into the spheroids and their consequent activation. Moreover, in mouse models the TMs could be used for PET imaging, showing specific accumulation at FAP-expressing tumor cells, as well as for killing of such tumors using redirected UniCAR T cells.
By that we could show that the anti-FAP scFv and IgG4 based TMs have high theragnostic potential as they can be used for both immunotherapy and diagnostic imaging.

The recent flourishing of research on non-aqueous actinide coordination chemistry has facilitated a deeper understanding of actinide metal-ligand interactions. In particular, studies utilizing ligands with soft donor atoms (N, S) have highlighted the subtle chemical differences between trivalent actinide (An) and lanthanide (Ln) ions. They provide not only theoretical and experimental insights but also the foundation for practical applications e.g. minor actinides separation. As part of our efforts to elucidate these differences, typically attributed to an increased covalency in the actinide compounds, we conducted research using N,N’-diisopropylbenzamidinate (iPr2BA) as a model N-donor ligand.

In this work, a series of trivalent lanthanide (La, Nd, Sm, Eu) and actinide (U, Np) tris-iPr2BA complexes [M(iPr2BA)3] were successfully synthesized and characterized in solid state to gain a comprehensive understanding of the bonding situation between f-block elements and N-donor ligands. Intensive paramagnetic NMR studies in solution have been carried out and the Bleaney method was applied to separate hyperfine shift contributions (Fermi contact and Pseudocontact contributions). Furthermore, quantum chemical calculations have been performed in order to evaluate the intramolecular bonding trends and electronic structures.

ACKNOWLEDGEMENT
This study was supported by the German Federal Ministry of Education and Research (BMBF) under the project No. 02NUK059B (f-Char).

Although the chemistry of uranium alkoxides has been widely studied, not much attention has been paid to alkoxide chemistry of transuranic elements. In 1967, Samulski and Karraker were able to isolate a few examples of transuranic alkoxides. However, these complexes were only characterized using elemental analysis and absorption spectra. These compounds were never structurally characterized.
Based on recent achievements in synthesizing novel transuranic starting materials, we were able to isolate four mono- and bimetallic tert-butoxides with Np(IV). [Np₃O(OtBu)₁₀] and [K₄Np₂O(OtBu)₁₀] were synthesized using the ligand substitution between neptunium(IV) silylamides and HOtBu, whereas the salt metathesis between [NpCl₄(DME)₂] (DME = dimethoxyethane) and various amounts of LiOtBu resulted in the formation of the oxo-free alkoxides [Np(OtBu)₄(py)₂] (py = pyridine) and [Li(THF)]₂[Np(OtBu)₆]. To the best of our knowledge, these compounds represent the first structurally characterized Np(IV) alkoxides using single crystal X-ray diffraction and solid-state UV-vis-NIR spectroscopy. Furthermore, treatment of [Np(OtBu)₄(py)₂] with [Fe(OtBu)₃]₂ results in the formation of a heterobimetallic complex [NpFe(OtBu)₇(py)]. A solvent dependent coordination motif on both metal sides was observed, leading to the formation of [NpFe(OtBu)₇].

Actinides (An) play an important role in chemical engineering and environmental science related to the nuclear industry or nuclear waste disposal. In contrast to the strongly shielded 4f electrons of the lanthanides, 5f electrons of particularly the early An are found to participate in bonding, e.g. to organic ligands. Another characteristic of the An is their huge variety of possible oxidation states, typically ranging from +II to +VII for early actinides, making their chemistry complex but interesting.
A suitable approach to explore fundamental physico-chemical properties of the actinides is to study series of isostructural An compounds in which the An is in the same oxidation state. Observed changes in e.g. the binding situation or magnetic effects among the An series may deliver insight into their unique electronic properties mainly originating from the f electrons. A question still remaining in the field of An chemistry is the degree of “covalency” in compounds across the actinide series, which may be addressed by systematic studies on series of An compounds, including transuranium elements.
We investigate the coordination chemistry of low-valent actinides using organic N-, O-, and S-donor ligands. Information on trends in covalency as well as mutual ligand influences can be obtained by the analysis of solid-state structures derived by SC-XRD in combination with quantum chemical calculations. Additional insight can be gained from high-energy-resolution fluorescence detection X-ray absorption near edge spectroscopy. In solution, NMR spectroscopy permits to draw conclusions about the complex speciation in solution, the intrinsic magnetic properties of the actinides, or subtle changes in covalency in the ligand-actinide bonding.

Often the bulk properties of materials like the lattice constant (interparticle distance and/or separation), stress tensor, etc., at high pressures and temperatures differ significantly from those under ambient conditions. The situation is particularly unsatisfactory for warm dense matter (WDM), where basic atomic properties like an atomization energy become ill defined and where bulk properties such as bulk moduli cannot be accurately measured due to extreme conditions. This calls for an approach that allows the non-empirical choice of the parameters of hybrid functionals without employing properties limited to ambient conditions. At the same time, it is preferable that such an approach have some connection to properties that are well defined and measurable in experiments across temperature and pressure regimes. We report that the static XC kernel can serve as a theoretical device for constructing hybrid functionals that are non-empirical and that apply for both solid-state systems and WDM [1-3].

[1] Zhandos A. Moldabekov, Mani Lokamani, Jan Vorberger, Attila Cangi, and Tobias Dornheim, Non-empirical Mixing Coefficient for Hybrid XC Functionals from Analysis of the XC Kernel, The Journal of Physical Chemistry Letters 14, 1326–1333 (2023), https://doi.org/10.1021/acs.jpclett.2c03670

[2] Zhandos Moldabekov, Maximilian Boeme, Jan Vorberger, David Blaschke, and Tobias Dornheim, Ab initio Static Exchange-Correlation Kernel across Jacob’s Ladder without functional derivatives, Journal of Chemical Theory and Computation 19, 1286–1299 (2023), https://doi.org/10.1021/acs.jctc.2c01180

[3] Zhandos A. Moldabekov, Mani Lokamani, Jan Vorberger, Attila Cangi, Tobias Dornheim, Assessing the accuracy of hybrid exchange-correlation functionals for the density response of warm dense electrons, J. Chem. Phys. 158, 094105 (2023)
https://doi.org/10.1063/5.0135729

Invited talk at CLFV23 conference, June 20 - 23, 2023.

We presetnt a method to compute a static exchange-correlation (XC) kernel across temperature regimes using KS-DFT for any XC functional available in Libxc [1]. We show the results of the static exchange-correlation kernel analysis using various XC functionals for dense electron gas and warm dense hydrogen. The results allow to better understund the effect of thermal excitations and density inhomogeneity on the XC kernel. Based on a comparison of KS-DFT data with high-precision Quantum Monte Carlo (QMC) data for both high temperatures and the ground state, we present the results of the analysis of the accuracy of the commonly used XC functionals for warm dense matter simulations [1-4]. As an application of the static XC kernel, we discuss linear-response time-dependent density functional theory (TDDFT) approach to warm dense matter with adiabatic exchange--correlation kernels [5].

The exchange correlation kernel (XC) naturally arises within the framework of linear response theory as a key quantity for describing correlated systems of many particles. Particularly, the XC kernel is needed in linear response TDDFT (LR-TDDFT), which is a powerful ab initio method that
allows one to describe dynamical and transport properties of equilibrium quantum-many body systems. A standard approach of the calculation of the XC kernel in LR-TDDFT is based on the computation of the second order functional derivative of a XC functional with respect to density. For extended systems, this approach is limited to simple static (adiabatic) LDA and GGA (such as PBE ) level XC functionals due to mathematical and computational challenges of computing functional derivatives of meta-GGA and hybrid level functionals. In fact, only adiabatic LDA (ALDA) is available in commonly used open source DFT codes. We have overcome these limitations by developing a new method of the calculation of the XC kernel [1], which utilizes the method of a direct harmonic perturbation. The essence of the developed approach is to compute a static density response function of a system by measuring the density perturbation induced by an external static harmonic field; with density being extracted from an equilibrium KS-DFT simulation. An alternative and equivalent definition of the XC kernel as a difference between the inverse values of the density response functions of systems with non-zero and zero XC functionals allows us to access the XC kernel without explicitly computing functional derivatives. This allows one to compute the XC kernel using available XC functionals through the ranks of Jacob's ladder and for any temperature. We demonstrated the utility of this method by analyzing the XC kernel beyond GGA level including meta-GGA and hybrid XC functionals [1-3]. In addition, we have presented a workflow for using the static XC kernel from the direct perturbation approach in the
LR-TDDFT of warm dense matter [4].

[1] Zhandos Moldabekov, Maximilian Böhme, Jan Vorberger, David Blaschke, and Tobias
Dornheim, Ab Initio Static Exchange–Correlation Kernel across Jacob’s Ladder without Functional
Derivatives, Journal of Chemical Theory and Computation 19 (4), 1286-1299 (2023 )
[2] Zhandos A. Moldabekov, Mani Lokamani, Jan Vorberger, Attila Cangi, Tobias Dornheim,
Assessing the accuracy of hybrid exchange-correlation functionals for the density response of warm
dense electrons. J. Chem. Phys. 158 (9), 094105 (2023).
[3] Zhandos A. Moldabekov, Mani Lokamani, Jan Vorberger, Attila Cangi, and Tobias Dornheim,
Non-empirical Mixing Coefficient for Hybrid XC Functionals from Analysis of the XC Kernel, The
Journal of Physical Chemistry Letters 14 (5), 1326-1333 (2023)
[4] Zhandos A. Moldabekov, Michele Pavanello, Maximilian P. Böhme, Jan Vorberger, and Tobias
Dornheim, Linear-response time-dependent density functional theory approach to warm dense
matter with adiabatic exchange-correlation kernels, Phys. Rev. Research 5, 023089 (2023)

To improve postoperative monitoring of patients undergoing pancreatic surgery, we propose a bedside, droplet-based millifluidic device that facilitates near real-time accurate and rapid determination of drain amylase activity. Drain liquid is co-encapsulated with a starch substrate in multiple nanoliter-sized reactors to track the fluorescence intensity released upon reaction with amylase. Comparing the amylase levels of 32 patient samples, 31 out of 32 millifluidic system results (96.9%) matched the clinical data within the 95% confidence interval. Importantly, the new millifluidic strategy significantly reduces the amylase assay time from several hours to approximately 3-4 minutes and offers a ca. 10 times lower limit of detection of 0.007 µmol/sL compared to that of current clinical techniques. Finally, we for the first time demonstrate the possibility of dynamic monitoring of amylase levels in the patient samples. Thus, the proposed droplet-based instant assay system could augment state-of-the-art clinical methods and significantly improve diagnosis of postoperative complications in patients after pancreatic surgery via near-real-time bedside monitoring.

Oncology research has been an exciting area for the application of electrical biosensors over the last few decades. Extremely high sensitivity of field-effect transistor-based (FET) biosensors directed the interest of scientists mostly to early cancer detection applications. However, the potential of electrical biosensors should not be limited to cancer diagnosis. With immunotherapy on the way to become the fourth pillar of cancer treatment, there will be an increasing demand for immunoassay testing before, during, and after the conduction of therapeutic treatment. Our previous results have demonstrated the usefulness of FET-based biosensors in the research and development of a safer engineered chimeric antigen receptor (CAR) T-cells-based therapy. In this work, we continue to explore the practicality of electrical biosensors in the potential therapeutic setting of immunotherapy. Here, we present a complete stand-alone FET-based biosensing system relying on the extended gate (EG) concept. Our platform has an independent readout which is portable, compatible with multiplexed measurement, and self-sufficient for point-of-care sensing purposes. The extended gate sensing chip is disposable and can be tailored for the specific sensing application. Compared to the traditional ion-sensitive FET setup, EG FET provides improved flexibility, cost-effectiveness, and adaptiveness to individual needs making it a promising candidate for clinical application. During a universal CAR T-cells (UniCAR) therapy, “switch” molecules are injected into the patient’s bloodstream to activate the T-cell processes for attacking tumors. Therefore, it is crucial to monitor the level of CAR T-cells and switch molecules for better control and decision-making related to personalized treatment. Here, we demonstrate the application of our EG FET platform in testing the therapeutic components of this treatment and discuss the related outlook for FET-based biosensors in immunotherapy. Our work endeavors to bridge the gap between clinical needs in immunotherapy and available sensing technology by broadening the application area for electrical biosensors.

Microorganisms show a high affinity for trivalent actinides and lanthanides, which play an important role in the safe disposal of high-level radioactive waste as well as in the mining of various rare earth elements. The interaction of the lanthanide Eu(III) with the sulfate-reducing microorganism Desulfosporosinus hippei DSM 8344T, a representative of the genus Desulfosporosinus that naturally occurs in clay rock and bentonite, was in-vestigated. Eu(III) is often used as a non-radioactive analogue for the trivalent actinides Pu(III), Am(III), and Cm(III), which contribute to a major part of the radiotoxicity of the nuclear waste. D. hippei DSM 8344T showed a weak interaction with Eu(III), most likely due to a complexation with lactate in artificial Opalinus Clay pore water. Hence, a low removal of the lanthanide from the supernatant was observed. Scanning transmission electron microscopy coupled with energy-dispersive X-ray spectroscopy revealed a bioprecipitation of Eu(III) with phosphates potentially excreted from the cells. This demonstrates that the ongoing interaction mechanisms are more complex than a sim-ple biosorption process. The bioprecipitation was also verified by luminescence spec-troscopy, which showed that the formation of the Eu(III) phosphate compounds starts almost immediately after the addition of the cells. Moreover, chemical microscopy pro-vided information on the local distribution of the different Eu(III) species in the formed cell aggregates. These results provide first insights into the interaction mechanisms of Eu(III) with sulfate-reducing bacteria and contribute to a comprehensive safety concept for a high-level radioactive waste repository, as well as to a better understanding of the fate of heavy metals (especially rare earth elements) in the environment.

From microplastics resuspending into the atmosphere to earth particles left behind during extraterrestrial explorations, the resuspension of microparticles by a turbulent gas flow occurs in many natural and industrial systems. Wall surfaces, onto which particles initially adhere, are rarely smooth and this surface roughness affects their resuspension. Available experimental data on particle resuspension have been obtained with substrates, whose surfaces are either unaltered or manually abraded with, for instance, sand blasting. In these experiments, the roughness elements span a wide size range and are in-homogeneously distributed in space. Surface functionalization is a modern technique allowing the precise fabrication of a wall surface with well-characterized microstructures, hence reducing the asperity randomness associated with conventional abrasion techniques. Taking advantage of surface functionalization, we present here a new set of reference data, where the wall asperities are represented by a structured arrangement of micropillars and microcubes. Adhesion force measurements and particle remaining fraction against gas velocity, at Reynolds number up to 8000, are reported for one reference and two artificially roughened substrates. Laboratory measurements show that the microasperities have little to moderate effect on the mean adhesion force and the threshold velocity, at which half of the 100-µm particles resuspend. The standard deviations are, however, significantly affected. The presented results will primary contribute to the improvement of resuspension models, which until now rely on a simplified representation of the surface roughness elements. The presented measurements are highly compatible with such models, which involve elementary roughness features, such as hemispherical asperities superimposed with a flat plate.

We study the meson contribution to the equation of state of the 2-flavor Polyakov-loop Nambu–Jona-Lasinio model, including the full momentum dependence of the meson polarization loops. Within the Beth-Uhlenbeck approach, we demonstrate that the contribution from the quark-antiquark continuum excitations in the spacelike region ω^2 − q^2 < 0, i.e., the Landau damping, leads to an increase of the pressure for temperatures ≳0.8T^χ_c and a significant meson momentum cutoff dependence in the mesonic pressure and the QCD trace anomaly. We investigate the dependence of the results on the choice of the Polyakov-loop potential parameter T_0. From the dependence of the mesonic pressure on the current quark mass, by means of the Feynman-Hellmann theorem, we evaluate the contribution of the pion quasiparticle
gas and Landau damping to the chiral condensate.

We utilize pump-probe spectroscopy to measure the quasiparticle relaxation dynamics of BaFe2As2 in a diamond anvil cell at pressures up to 4.4 GPa and temperatures down to 8 K. Tracing the amplitude of the relaxation process results in an electronic phase diagram that illustrates the variation of the spin-density wave (SDW) order across the whole range of the applied pressures and temperatures. We observe a slowing down of the SDW relaxation dynamics in the vicinity of the phase transition boundary. However, its character depends on the trajectory in the phase diagram: the slowing down occurs gradually for the pressure-induced transition at low temperatures and abruptly for the thermally-driven transition. Our results suggest that the pressure-induced quantum phase transition in BaFe2As2 is related to the gradual worsening of the Fermi-surface nesting conditions.

To date, perfusion simulations in the human brain have been limited to a relatively small number of patient-specific cases. Here, a
pipeline relying on magnetic resonance imaging (MRI) is proposed to overcome this limitation. The computational geometry is
adjusted using T1-weighted MRI, whereas the perfusion model parameters are tuned based on arterial spin labeling perfusion MRI. A
cohort of 75 patients is considered to demonstrate that the pipeline is suitable to generate virtual patients with statistically realistic
cerebral blood flow maps. In the future, in silico clinical trials will be conducted using similar virtual cohorts to improve ischaemic
stroke interventions.

We demonstrate a significantly simplified experimental approach for investigating liquid metallic hydrogen, which is crucial to
understand the internal structure and evolution of giant planets. Plastic samples were shockcompressed and then probed by
short pulses of X-rays generated by free electron lasers. By comparison with ab initio simulations, we provide indirect
evidence for the creation of elemental hydrogen in shock-compressed plastics at ∼150GPa and ∼5,000K and thus in a
regime where hydrogen is predicted to be metallic. Being the most common form of condensed matter in our solar system,
and ostensibly the simplest of all elements, hydrogen is the model case for many theoretical studies and we provide a new
possibility to benchmark models for conditions with extreme pressures and temperatures. Moreover, this approach will also
allow to probe the chemical behavior of metallic hydrogen in mixture with other elements, which, besides its importance for
planetary physics, may open up promising pathways for the synthesis of new materials.

Actinides (An) play an important role in chemical research and environmental science related to the nuclear industry or nuclear waste repositories. Investigating their coordination chemistry can function as a tool to obtain fundamental understanding of actinide binding. Due to the radiotoxicity of actinide complexes, special care in handling those material is needed in form of working in a controlled area lab. Therefore, the understanding of complexation properties of the actinides, in particular the transuranium (TRU) elements, is lacking behind those of the d- or 4f-elements.
For the early actinides possible oxidation states typically range from +II to +VII. A suitable approach to explore fundamental physico-chemical properties of the actinides is to study series of isostructural An compounds in which the An is in the same oxidation state. Therefore, our investigations are directed towards the synthesis of actinide complexes (An = Th, U, Np, and Pu) with the f-element in the oxidation state IV, the dominant oxidation state particularly under anoxic conditions. Observed changes in e.g. the binding situation or magnetic effects along such series deliver insight into the elements’ unique electronic properties mainly originating from the f-electrons. One important question in the field of An chemistry is the degree of “covalency” in compounds across the An series, which may be addressed by systematic studies on series of An compounds, including transuranium (TRU) elements.
An complexes using ambidentate ligand systems can give valuable information on covalency differences between soft and hard donor atoms in one complex system. We therefore chose the 2-mercaptopyridyl ligand system (PyS) as monoanionic ambidentate S,N-moiety. Due to possible resonance structures in the ligand backbone, the negative charge can be distributed over both donor atoms. This leaves sufficient flexibility for PyS to coordinate to the actinide atom in a S- or N-monodentate or S,N-chelating manner. We synthesized a series of PyS-containing Th, U, Np, and Pu complexes and compare their structural and spectroscopic characteristics along the early actinides. These results are used as a basis to further analyze bonding trends along the actinide series by means of quantum chemical calculations.
From the results, trendlines along the actinides were obtained, which shed some light in the ongoing debate of covalency in actinide bonding.

https://u.ganil-spiral2.eu/10.26143/GANIL-2016-E710.html

Im Zusammenspiel magnetischer und elektrischer Felder entstehen
elektromagnetische Kräfte. Deren praktische Anwendung z. B. in Elektromotoren ist aus unserem Alltag nicht mehr wegzudenken.
Elektromagnetische Kräfte sind aber auch in der Lage, leitfähige Flüssigkeiten, wie Elektrolyte und Metallschmelzen, kontaktlos zu beeinflussen.
Die Vielfalt an Strömungskonfigurationen, die mit einfachen Permanentmagneten in einer Elektrolysezelle einstellbar sind, wird im Experiment
demonstriert.

Energie ist auf vielfltige Weise mit dem Leben verknüpft. Im Laufe der Geschichte dominierten unterschiedliche Energieträger. Der Vortrag nimmt sie unter die Lupe und zeigt den Wandel ihrer Nutzung und die damit verbundenen Konsequenzen. Ein Schwerpunkt ist die im Horizon 2020 Projekt SOLSTICE entwickelte Speichertechnologie.

Die geplante Umstellung des Energiesystems auf fluktuierende Erzeuger zieht einen immensen Bedarf an Speichern nach sich, um Angebot und Nachfrage auszugleichen. Der Vortrag stellt verschiedene Arten von Flüssigmetallbatterien vor, die derzeit mit dem Ziel einer ökonomischen stationären Energiespeicherung entwickelt werden.

Die geplante Umstellung des Energiesystems auf fluktuierende Erzeuger zieht einen immensen Bedarf an Speichern nach sich, um Angebot und Nachfrage auszugleichen. Der Vortrag stellt verschiedene Arten von Flüssigmetallbatterien vor, die derzeit mit dem Ziel einer ökonomischen stationären Energiespeicherung entwickelt werden.

Classical novae are thermonuclear explosions in stellar binary sys- tems, and important sources of 26Al and 22Na. While γ rays from the decay of the former radioisotope have been observed throughout the Galaxy, 22Na remains untraceable. Its half-life (2.6 yr) would allow the observation of its 1.275 MeV γ-ray line from a cosmic source. However, the prediction of such an observation requires good knowl- edge of its nucleosynthesis. The 22Na(p,γ)23Mg reaction remains the only source of large uncertainty about the amount of 22Na ejected. Its rate is dominated by a single resonance on the short-lived state at 7785.0(7) keV in 23Mg. Here, a combined analysis of particle-particle correlations and velocity-difference profiles is proposed to measure femtosecond nuclear lifetimes. The application of this method to the study of the 23Mg states, places strong limits on the amount of 22Na produced in novae and constrains its detectability with future space-borne observatories.

Radionuclide therapies are an important tool for the management of patients with neuroendocrine tumors (NETs). Especially [131I]MIBG and [177Lu]Lu-DOTA-TATE are routinely used for the treatment of a subset of NETs, including phechromocytomas, paragangliomas and gastroenteropancreatic tumors. Some patients suffering from other forms of NETs, such as medullary thyroid carcinoma or neuroblastoma, were shown to respond to radionuclide therapy; however, no general recommendations exist. Although [131I]MIBG and [177Lu]Lu-DOTA-TATE can delay disease progression and improve quality of life, complete remissions are achieved rarely. Hence, better individually tailored combination regimes are required. This review summarizes currently applied radionuclide therapies in the context of NETs and informs about recent advances in the development of theranostic agents that might enable targeting subgroups of NETs that previously did not respond to [131I]MIBG or [177Lu]Lu-DOTA-TATE. Moreover, molecular pathways involved in NET tumorigenesis and progression that mediate features of radioresistance and are particularly related to the stemness of cancer cells are discussed. Pharmacological inhibition of such pathways might result in radiosensitization or general complementary antitumor effects in patients with certain genetic, transcriptomic, or metabolic characteristics. Finally, we provide an overview of approved targeted agents that might be beneficial in combination with radionuclide therapies in the context of a personalized molecular profiling approach.

In our HELIPORT workshop, we provided insights into our project and share our results. In addition, we would like to provide a platform for the presentation of similar projects, as well as extensions or integrations from the surrounding research areas. The overall goal of the workshop is bringing together different institutions with similar challenges and establishing a community around our HELIPORT project.
We therefore encouraged our community to submit an abstract for a talk or poster. The submissions are dedicated to four thematic points:

• HELIPORTuse-cases,
• Scientificprojectandmetadatamanagement, • Experiment-specificandoverallmetadataand • Scientificworkflows.

Warm dense matter (WDM)---an extreme state that is characterized by extreme densities and temperatures---has emerged as one of the most active frontiers in plasma physics and material science. In nature, WDM occurs in astrophysical objects such as giant planet interiors and brown dwarfs. In addition, WDM is highly important for cutting-edge technological applications such as inertial confinement fusion and the discovery of novel materials. In the laboratory, WDM is studied experimentally in large facilities around the globe, and new techniques have facilitated unprecedented insights. Yet, the interpretation of these experiments requires a reliable diagnostics based on accurate theoretical modeling, which is a notoriously difficult task [1]. In this work, I will give an overview of how we can use exact ab-initio path integral Monte Carlo (PIMC) simulations [2] together with thermal density functional theory (DFT) calculations to get new insights into the behavior of WDM. Moreover, I will show how switching to the imaginary time representation allows us to significantly improve the interpretation of X-ray Thomson scattering (XRTS) experiments, which are a key diagnostic for WDM [3]. Specifically, I will present a model-free temperature diagnostic [4] based on the well-known principle of detailed balance, but available for all wave numbers, and a new idea to directly extract the electron— electron static structure factor from an XRTS measurement [5]. As an outlook, I will show how new PIMC capabilities will allow to give us novel insights into electronic correlations in warm dense quantum plasmas, leading to unprecedented agreement between experiments [6] and theory.

[1] M. Bonitz et al., Physics of Plasmas 27, 042710 (2020)

[2] M. Böhme et al., Physical Review Letters 129, 066402 (2022)

[3] S. Glenzer and R. Redmer, Reviews of Modern Physics 81, 1625 (2009)

[4] T. Dornheim et al., Nature Communications 13, 7911 (2022)

[5] T. Dornheim et al., arXiv:2305.15305 (submitted)

[6] T. Döppner et al., Nature 618, 270-275 (2023)

In this talk, I will present our research on the application of time-dependent density functional theory (TDDFT) to model observables induced in matter under extreme conditions. Specifically, I will discuss the electron loss function in scattering experiments with X-ray free electron lasers [1] and the electrical conductivity in metals [2, 3]. Additionally, I will explore the potential of physics-informed neural networks for solving the time-dependent Kohn-Sham equations, which describe electron dynamics in response to incident electromagnetic waves [4].

[1] Z. Moldabekov, T. Dornheim, A. Cangi, Sci. Rep. 12, 1093 (2022).
[2] K. Ramakrishna, M. Lokamani, A. Baczewski, J. Vorberger, A. Cangi, Phys. Rev. B 107, 115131 (2023).
[3] K. Ramakrishna, M. Lokamani, A. Baczewski, J. Vorberger, A. Cangi, arXiv:2210.10132 (2022).
[4] K. Shah, P. Stiller, N. Hoffmann, A. Cangi, NeurIPS Machine Learning and the Physical Sciences, arXiv:2210.12522 (2022).

In this talk, I will present two lines of our research. In the first part, I will discuss the application of time-dependent density functional theory (TDDFT) in modeling observables induced in matter under extreme conditions, such as the electron loss function relevant to scattering experiments with X-ray free electron lasers [1] and the electrical conductivity in metals [2]. In the second part, I will highlight our recent progress in leveraging Artificial Intelligence (AI) to enhance the efficiency of electronic structure calculations [3]. Specifically, I will focus on our efforts to accelerate Kohn-Sham density functional theory calculations at finite temperatures by integrating deep neural networks into the Materials Learning Algorithms framework [4,5]. Our results demonstrate significant improvements in calculation speed for metals up to their melting point. Additionally, our implementation of automated machine learning has led to substantial savings in computational resources for identifying optimal neural network architectures, paving the way for large-scale AI-driven investigations [6]. Lastly, I will present our latest breakthrough, showcasing the capability of neural-network-driven electronic structure calculations for systems containing over 100,000 atoms [7].

[1] Z. Moldabekov, T. Dornheim, A. Cangi, Sci. Rep. 12, 1093 (2022).
[2] K. Ramakrishna, M. Lokamani, A. Baczewski, J. Vorberger, A. Cangi, Phys. Rev. B 107, 115131 (2023).
[3] L. Fiedler, K. Shah, M. Bussmann, A. Cangi, Phys. Rev. Materials 6, 040301, (2022).
[4] A. Cangi, J. A. Ellis, L. Fiedler, D. Kotik, N. A. Modine, V. Oles, G. A. Popoola, S. Rajamanickam, S. Schmerler, J. A. Stephens, A. P. Thompson, MALA, https://doi.org/10.5281/zenodo.5557254 (2021).
[5] J. A. Ellis, L. Fiedler, G. A. Popoola, N. A. Modine, J. A. Stephens, A. P. Thompson, A. Cangi, Phys. Rev. B 104, 035120 (2021).
[6] L. Fiedler, N. Hoffmann, P. Mohammed, G. A. Popoola, T. Yovell, V. Oles, J. A. Ellis, S. Rajamanickam, A. Cangi, Mach. Learn.: Sci. Technol. 3, 045008 (2022).
[7] L. Fiedler, N. A. Modine, S. Schmerler, D. J. Vogel, G. A. Popoola, A. P. Thompson, S. Rajamanickam, A. Cangi, Npj Comput. Mater., accepted (2023).

This paper defines a 3D full core neutronics benchmark which is based on the NuScale small modular reactor (SMR) concept. The paper provides a detailed description of the NuScale-like core, a list of expected outputs, and a reference solution to the benchmark exercises obtained with the Monte Carlo code Serpent.

The benchmark was developed in the framework of the Euratom McSAFER project and can be used for verification of computational chains dedicated to 3D full-core neutronics simulations of water cooled SMRs.

The paper is supplemented with a digital data set to ease the modeling process.

BaFe2As2 is the parent compound for a family of iron-based high-temperature superconductors as well as a prototypical example of the spin-density wave (SDW) system. In this study, we perform an optical pump-probe study of this compound to systematically investigate the SDW order across the pressure-temperature phase diagram. The suppression of the SDW order by pressure manifests itself by the increase of relaxation time together with the decrease of the pump-probe signal and the pump energy necessary for complete vaporization of the SDW condensate. We have found that the pressure-driven suppression of the SDW order at low temperature occurs gradually in contrast to the thermally-induced SDW transition. Our results suggest that the pressure-driven quantum phase transition in BaFe2As2 (and probably other iron pnictides) is continuous and it is caused by the gradual worsening of the Fermi-surface nesting conditions.