Publications Repository - Helmholtz-Zentrum Dresden-Rossendorf

Copper nanowires (Cu NWs) are popular potential building blocks of various interconnecting components, microscale circuits, and nanoelectronics. Making interconnects at the nanoscale is still an open problem, and various methods have been explored during the past decades. While ion beam joining has been known for quite some time, the beam parameter-dependent processes leading to joining is yet to be understood in detail. A low-energy (5 keV) and broad argon ion beam is unable to induce joining among the Cu NW mesh, at the low ion currents (<400 nA). However, when the ion current was elevated to 1 µA at the same energy, a large-scale joining was observed. We developed a 3D finite volume model for heat transfer and Joule heating-based melting, which successfully explains the ion current-induced joining. When the current is increased to a significantly high level, the network fragments into smaller copper nanoparticles due to the heat produced. On the other hand, at higher argon ion energy (200 keV) a large-scale joining is observed even at small (<400 nA) beam current. A state-of-the-art, Monte Carlo-based TRI3DYN simulation predicted the role of recoils, redeposition, and ion beam mixing in such joining process at high ion energy, which is mostly due to elastic collisional consequences. Such ion current-induced nanowelded copper mesh-coated PET substrate shows good transmission in the optical range of wavelengths and a notable decrease in the sheet resistance is observed.

Plant growth on mine wastes is restricted by the lack of water, nutrients, phytotoxic responses and
the absence of a seedbank. In a mesocosm study, we addressed the establishment of vegetation
on metalliferous mine wastes from two seed mixtures. Besides the composition of the vegetation
and the increase in plant cover and biomass over time, we studied concentrations of heavy metals
in the shoot and analyzed the quantity of throughflow, its pH and EC to follow pollutant discharge.
We hypothesized that the types of mine wastes and sown grasslands will affect species composition
and the formation of a protective plant cover. Our platform was well-suited to study build-up and
succession of a vegetation layer and its potential to stabilize mine wastes. However, the establishing
community was less diverse than expected. The dilution of wastes increased species number and
biomass, and we found a reduction of material discharge with increasing vegetation cover. Over
time, drainage was reduced, while pH of the throughflow did not change. However, it was higher
under the addition of greywater. Interestingly, the use of greywater led to a higher biomass in one
mixture and slight changes in the chemistry of the throughflow and the plant matter.

The dataset consists of Infrared photodissociation (IRPD) spectra of Cu+(H2O)(H2)n (with n ≤ 3) and its isotopologue measured on the Leipzig 5 K ring-electrode ion-trap triple mass spectrometer. Besides, it contains the Energy Decomposition Analysis (EDA), the benchmark results, the harmonic and the anharmonic VPT2 frequencies results as well as the script used to get the predicted separation factor for the adsorbed dihydrogen isotopologue.

Little is known about the strong mediating effect of the ligand sphere and the coordination geometry on the strength and isotopologue selectivity of hydrogen adsorption on the undercoordinated copper(I) site. Here, we explore this effect using gas-phase complexes Cu+(H2O)(H2)n (with n ≤ 3) as model systems. Cu+(H2O) attracts dihydrogen (82 kJ mol−1) more strongly than bare Cu+ (64 kJ mol−1) does. Combining experimental and computational methods, we demonstrate a high isotopologue selectivity in dihydrogen binding to Cu+(H2O), which results from a large difference in the adsorption zero-point energies (2.8 kJ mol−1 between D2 and H2, including an anharmonic contribution of 0.4 kJ mol−1). We investigate its origins and the bond strengthening between Cu+ and H2 upon addition of a single H2O ligand. We discuss the role of the environment and the coordination geometry of the adsorption site in achieving a high selectivity and the ramifications for identifying and designing future materials for adsorptive dihydrogen isotopologue separation.

Gas evolution at surfaces occurs in a multitude of industrial processes and is a complex phenomenon. A wide range of length scales is involved from nucleation to bubble departure. The evolution of gas bubbles depends on the specific wetting dynamics at the surface and the local conditions like species distribution, temperature, pressure or outer flow. Advancing the bubble growth and gas transport in electrochemical electrolyzers for producing hydrogen can be expected to be beneficial with respect to the overall efficiency of the device.
The presentation will show detailed results of the gas evolution at surfaces of different morphology and surface in order to improve our knowledge how the gas transport can be improved. The results are based on numerical simulations by a VOF method and a mass transfer model that correctly accounts for the flux of dissolved gas into the bubble. Hereby, different wetting dynamics are considered to elaborate the surface influence. The results will further be compared with experimental results available in our group and from literature.

The process of electrolysis at microelectrodes in acidic solutions allows the detailed study of the dynamics of single hydrogen bubbles from nucleation to growth until detachment from the electrode. In earlier work, we have identified three different growth regimes of single hydrogen bubbles that occur depending on the potential applied and the electrolyte concentration [1]. At the bubble interface, a thermal Marangoni flow exists, and the hydrogen bubble may exhibit periodic oscillations or steady growth due to the varying influence of buoyancy, electric and surface tension force [2,3].
Although the thermocapillary effect during bubble growth at microelectrodes is well recognized, the interfacial flow velocity measured decays faster than found in the first simulation results of Massing et al. [4]. This might be caused by the presence of tracer particles in the electrolyte used for the flow measurements, which has been overlooked so far [5]. Our recent experimental findings underscore that variations in the concentration of tracer particles exert notable changes on both the shape and dynamics of bubbles, as well as the flow patterns of the nearby electrolyte. In the steady growth regime, the current and departure time are slightly increased when the particle volume concentration is increased, but the contact radius is reduced. In the oscillatory regime, the oscillating frequency, departure time and current all decrease with the increase in particle volume concentration.
Consequently, we propose a theoretical model elaborating the attraction of charged particles to the bubble interface and the resulting modification of the dynamics of the particle laden interface and the bubble [6]. This model enables quantitative corrections for the measurement and simulation deviations. The numerical simulations are conducted using COMSOL, revealing a good agreement in the tangential velocity profile at the bubble interface arising from both thermo- and soluto-capillary effects (see Figure 1). The oscillatory motion of a hydrogen bubble on the electrode is also simulated. Furthermore, the force balance on the bubble is studied in detail, which provides a deeper insight into the complex phenomena of electrolytic gas evolution.

Electrochemical gas evolution at electrodes beside mass transfer across the interface involves a variety of phenomena at different scales that are coupled with each other. Today, our understanding still seems to be limited, e.g. with respect of accurately predicting the bubble departure size. As the details of growth and transport of gas bubbles have a strong impact on the performance of electrolyzer devices, a better understanding is needed for improving their efficiency. The talk will elaborate on recent progress in understanding how capillary, thermal, electric and wetting effects influence the gas bubble evolution, thereby combining experimental and numerical efforts.

In this work, we developed a direct strategy to fabricate Palladene (i. e. Palladium metallene) aerogels and propose a temperature-dependent growth mechanism. Besides the typical three-dimensional networks and wrinkled surface morphologies, the as-prepared Palladene₅₀ aerogel is endowed with abundant Pd²⁺. The as-prepared Palladene₅₀ aerogel exhibits an excellent mass activity in the formic acid oxidation reaction and a good half-wave potential in the oxygen reduction reaction in comparison with Pd/C and a Pd aerogel. This work expands the range of metal aerogels from the perspective of the building block units and demonstrates a direct approach to fabricate highly promising bifunctional electrocatalysts for fuel cells.

Nitrilotris(methylenephenylphosphinic) acid (NTPAH₃) was silylated using hexamethyldisilazane to produce the tris(trimethylsilyl) derivative NTPA(SiMe₃)₃. From the latter, upon alcoholysis in chloroform, NTPAH₃ could be recovered. Thus, a new modification of that phosphinic acid formed. Meanwhile, NTPAH₃ synthesized in aqueous hydrochloric acid crystallized in the space group P3c1 with the formation of O-H···O H-bonded networks (NTPAH₃P), in chloroform crystals in the space group R3c formed (NTPAH₃M), the constituents of which are individual molecules with exclusively intramolecular O-H···O hydrogen bonds. Both solids, NTPAH₃P and NTPAH₃M, were characterized by single-crystal X-ray diffraction, multi-nuclear (¹H, ¹³C, ³¹P) solid-state NMR spectroscopy, and IR spectroscopy as well as quantum chemical calculations (both of their individual constituents as isolated molecules as well as in the periodic crystal environment). In spite of the different stabilities of their constituting molecular conformers, the different crystal packing interactions rendered the modifications of NTPAH₃P and NTPAH₃M similarly stable. In both solids, the protons of the acid are engaged in cyclic (O=P–O–H)₃ H-bond trimers. Thus, the trialkylamine N atom of this compound is not protonated. IR and ¹H NMR spectroscopy of these solids indicated stronger H-bonds in the (O=P–O–H)₃ H-bond trimers of NTPAH₃M over those in NTPAH₃P.

The exploration of the coordination chemistry of actinides significantly lags behind that of transition metals as well as their lanthanide homologues. As such, a fundamental understanding of the binding properties in actinide compounds is still leaving many open questions. Therefore, systematic investigation of various coordination motives around an actinide centre can be used as benchmark to evaluate what analytic techniques can reveal about novel actinide-ligand bonding.
In this study, we focus on a square antiprism coordination of only oxygen donor atoms in an actinide series ranging from thorium to plutonium. Installing either one or two transition metals in close proximity to the actinide, leads to an 8+2 coordination at the actinide centre. These heterobi- and trimetallic complexes have been investigated using single-crystal X-ray diffraction, NMR, HERFD-XANES, and SQUID magnetometry. The experimental findings were further analysed with quantum chemical calculations. A comparison with their monometallic counterparts gives new insight into actinide-transition metal bonding.

The 2-pyridyloxy ligand (PyO−) has proven to be a useful ligand to isolate heterobimetallic complexes and thus supporting bonds between transition metals (TM) and/or main-group elements. Although interesting coordination motifs can be expected especially with actinides, metal-metal interactions remain a scarce phenomenon in actinide chemistry. Together with the high coordination numbers and various oxidation states, actinide 2-hydroxypyridinolate complexes would have the necessary flexibility to form a variety of actinide complexes also containing a transition metal.
Initially, treatment of tetravalent [AnCl₄(THF)₃] (An = Th, U, Np, Pu) with excess 2-hydroxypyridine gave a series of heteroleptic 2(1H)-pyridinone actinide complexes [AnCl(HPyO)₇]Cl₃. These complexes were good candidates to synthesise heterobimetallic complexes by the addition of [TMCl₂(THT)₂] (TM = Pd, Pt; THT = tetrahydrothiophene) and Et₃N as a supporting base. Using this synthesis method, a series of eight complexes of the type [TM(µ-PyO)₄An(µ-PyO)₄TM] (An = Th, U, Np, Pu; TM = Pd, Pt) could be isolated. These complexes have been investigated using single-crystal X-ray diffraction, NMR, HERFD-XANES spectroscopy, and SQUID magnetometry. The experimental findings were supported by quantum chemical calculations. The obtained data allows us to draw comparisons along the tetravalent actinide series and between palladium and platinum, whereby an unexpected trend in An-TM bonding has been observed.

Nanostructured silicon can reduce reflectance loss in optoelectronic applications, but intrinsic silicon cannot absorb photons with energy below its 1.1 eV bandgap. However, incorporating a high concentration of dopants, i.e., hyperdoping, to nanostructured silicon is expected to bring broadband absorption ranging from UV to short-wavelength IR (SWIR, <2500 nm). In this work, we prepare nanostructured silicon using cryogenic plasma etching, which is then hyperdoped with selenium (Se) through ion implantation. Besides sub-bandgap absorption, ion implantation forms crystal damage, which can be recovered through flash lamp annealing. We study crystal damage and broadband (250–2500 nm) absorption from planar and nanostructured surfaces. We first show that nanostructures survive ion implantation hyperdoping and flash lamp annealing under optimized conditions. Secondly, we demonstrate that nanostructured silicon has a 15% higher sub-bandgap absorption (1100–2500 nm) compared to its non-hyperdoped nanostructure counterpart while maintaining 97% above-bandgap absorption (250–1100 nm). Lastly, we simulate the sub-bandgap absorption of hyperdoped Si nanostructures in a 2D model using the finite element method. Simulation results show that the sub-bandgap absorption is mainly limited by the thickness of the hyperdoped layer rather than the height of nanostructures.

Two-dimensional (2D) van der Waals heterostructures that embody the electronic characteristics of each constituent material have found extensive applications. Alloy engineering further enables the modulation of the electronic properties in these structures. Consequently, we envisage the construction and modulation of composition-dependent antiambipolar transistors (AATs) using van der Waals heterostructures and alloy engineering to advance multivalued inverters. In this work, we calculate the electron structures of SnSe2(1–x)S2x alloys and determine the energy band alignment between SnSe2(1–x)S2x and 2H-MoTe2. We present a series of vertical AATs based on the SnSe2(1–x)S2x/MoTe2 type-III van der Waals heterostructure. These transistors exhibit composition-dependent antiambipolar characteristics through the van der Waals heterostructure, except for the SnSe2/MoTe2 transistor. The peak current (Ipeak) decreases from 43 nA (x = 0.25) to 0.8 nA (x = 1) at Vds = −2 V, while the peak-to-valley current ratio (PVR) increases from 4.5 (x = 0.25) to 6.7 × 103 (x = 1) with a work window ranging from 30 to 47 V. Ultimately, we successfully apply several specific SnSe2(1–x)S2x/MoTe2 devices in binary and ternary logic inverters. Our results underscore the efficacy of alloy engineering in modulating the characteristics of AATs, offering a promising strategy for the development of multivalued logic devices.

Fe-Cr alloys serve as model alloys for the investigation of radiation induced effects in ferritic-martensitic steels which are candidate structural materials for future fusion reactors. In this work the effect of Cr segregation and/ or agglomeration in 490 keV Fe+ ion irradiated Fe-10at%Cr alloys in the form of thin films is investigated. The irradiations took place at 300 ◦C at doses ranging from 0.5 to 20 displacements per atom (dpa). Polarized Neutron Reflectivity (PNR) measurements were used for the determination of the solute Cr concentration in the Fe-Cr matrix. Cr depletion from the Fe-Cr matrix up to 2.4 at% was found. This is related to solute Cr decrement as the accumulated dose increases. After the damage of 4 dpa, solute Cr reaches the asymptotic value of 8.4 at%, close to that of the thermodynamic equilibrium in Fe-Cr. Atom Probe Tomography (APT) measurements showed that after irradiation Cr accumulates into clusters the majority of which is co-located with oxygen.

The factors that influence the formation of helium blisters in copper were studied, including crystallographic grain orientation and thermomechanical conditions. Helium implantation experiments were conducted at 40 KeV with a dose of 5 × 10¹⁷ ions/cm², and the samples were then subjected to post-implantation heat treatments at 450 °C for different holding times. A scanning electron microscope (SEM) equipped with an electron backscatter diffraction (EBSD) detector was used to analyze the samples, revealing that the degree of blistering erosion and its evolution with time varied with the crystallographic plane of the free surface in different ways in annealed and cold rolled copper. Out of the investigated states, rolled copper with a (111) free surface had superior helium blistering durability. This is explained by the consideration of the multivariable situation, including the role of dislocations and vacancies. For future plasma-facing component (PFC) candidate material, similar research should be conducted in order to find the optimal combination of material properties for helium blistering durability. In the case of Cu selection as a PFC, the two practical approaches to obtain the preferred (111) orientation are cold rolling and thin layer technologies.

Hyperdoped germanium (Ge) has demonstrated increased sub-bandgap absorption, offering potential applications in the short-wavelength-infrared spectrum (1.0–3.0 μm). This study employs ion implantation to introduce a high concentration of selenium (Se) into Ge and investigates the effects of post-implantation annealing techniques on the recovery of implantation damage and alterations in optical properties. We identify optimal conditions for two distinct annealing techniques: rapid thermal annealing (RTA) at a temperature of 650 °C and ultrafast laser heating (ULH) at a fluence of 6 mJ/cm2. The optimized ULH process outperforms the RTA method in preserving high doping profiles and achieving a fourfold increase in sub-bandgap absorption. However, RTA leads to regrowth of single crystalline Ge, while ULH most likely leads to polycrystalline Ge. The study offers valuable insights into the hyperdoping processes in Ge for the development of advanced optoelectronic devices.

Recently, both large language models and large vision models (LVMs) have gained significant attention. Trained on large-scale datasets, these large models have showcased remarkable capabilities across various research domains. To enhance the accuracy of remote sensing (RS) scene classification, LVM-based methods are explored in this letter. Due to the differences between RS images and natural images, simply transferring LVMs to RS tasks is impractical. Therefore, we conducted research on relevant techniques and appended learnable prompt tokens to the input tokens while freezing the backbone weights, reducing the parameter scale and making the LVM weights easier to harness and to transfer. In consideration of latent catastrophic forgetting issues induced by ordinary finetuning techniques and the inherent complexity and redundancy of RS images, we introduced soft adaption mechanisms between backbone layers based on prompt tuning technique and implemented the first LVM tuning method, namely, the Large Vision Model Soft Adaption for RS scene classification (LVM-StARS)-Deep and the LVM-StARS-Shallow to make LVMs more suitable for RS scene classification tasks. The proposed methods are evaluated on two popular RS scene classification datasets, and the experimental results indicate that the proposed method outperforms other state-of-the-art methods. The experimental results demonstrate that our proposed method enhances overall accuracy (OA) by 1.71%–3.94%, while updating only 0.1%–0.5% of the parameters compared to full finetuning. Furthermore, our method outperforms the existing methods.

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

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

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

Overview of needs and status of near real-time adaptive particle therapy

In this overview talk the following questions will be addressed:

-What is the status concerning fast adaptions in particle therapy also in relation to photon therapy?
-Why we need online-adaptive particle therapy (OAPT)?
-What are different approaches also in relation to different adaption speed?
-What are the different imaging approaches for OAPT?
-How can we verify the treatment delivery when no pre-treatment phantom QA is performed?
-What is the role of I-based decision support?
-What initiatives exist on national and international level? Where do we stand?

The fundamental understanding of the proton transport mechanism through graphene-based proton exchange membranes (PEMs) is crucial to develop novel and advanced two-dimensional (2D) separation materials for energy conversion devices. [1] We computationally investigate ways to enhance the balance between proton permeability and selectivity using a combination of ReaxFF molecular dynamics (ReaxFF-MD), Density Functional Theory (DFT), and metadynamics. In both the cases of graphene nanopore and pristine graphene, covalent benzenesulfonic functionalization introduces significant improvements in proton permeability and selectivity compared to other moieties. [2,3] For the graphene nanopore scenario, the benzenesulfonic functionality dynamically acts as a proton trap and proton shuttle by establishing a favourable hydrogen-bond network, resulting in an effective proton channel through the nanopore (Figure 1a). [2] In the pristine graphene case, the benzenesulfonic functionality guides the proton hopping toward the distorted basal plane, enabling successive proton tunnelling to the other side of the graphene monolayer (Figure 1b). [3,4] Notably, in these systems we achieve estimated proton diffusion coefficients that are comparable to or higher than the current state-of-the-art PEM, Nafion. [2,3] The mechanisms exhibited by these benzenesulfonic functionalized graphene-based systems set the ground for designing new 2D-PEMs with efficient unidirectional proton transport features.

References

[1] Liu, X. et al. Nat. Nanotechnol. 15, 307–312 (2020).
[2] Calvani, D. et al. J. Phys. Chem. C. 128, 8, 3514–3524 (2024).
[3] Zhang, W. et al. arXiv:2308.16112.
[4] An, Y. et al. Adv. Mater. 32 (37), 2002442 (2020).

Dual energy/spectral CT

CT for RTP*: technical requirements and QA guidlines

X-ray computed tomography (CT) is the clinical standard for treatment planning in particle therapy. In this chapter, the basic principles of this state-of-the-art image modality will be described, as well as strategies to account for uncertainties of the conversion from CT number to ion stopping power.

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

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

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

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

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

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

Energy functionals serve as the basis for different models and methods in quantum and classical many-particle physics. Arguably, one of the most successful and widely used approaches in material science at both ambient and extreme conditions is density functional theory (DFT). Various flavors of DFT methods are being actively used to study material properties at extreme conditions, such as in warm dense matter, dense plasmas, and nuclear physics applications. In this review, we focus on the warm dense matter regime, which occurs in the core of giant planets and stellar atmospheres, and as a transient state in inertial confinement fusion experiments. We discuss the connection between linear density response functions and free energy functionals as well as the utility of the linear response formalism for the construction of advanced functionals. As a new result, we derive the stiffness theorem linking the change in the intrinsic free energy to the density response properties of electrons. We review and summarize recent works that assess various exchange-correlation (XC) functionals for an inhomogeneous electron gas that is perturbed by a harmonic external field and for warm dense hydrogen using exact path integral quantum Monte Carlo data as an unassailable benchmark. This constitutes a valuable guide for selecting an appropriate XC functional for DFT calculations in the context of investigating the inhomogeneous electronic structure of warm dense matter. We stress that correctly simulating the strongly perturbed electron gas necessitates the correct UEG limit of the XC and non-interacting free-energy functionals.

Matter under extreme densities and temperatures—often referred to as warm dense matter (WDM)— is pivotal for a number of cutting-edge technological applications such as the discovery and synthesis of novel materials and hot-electron chemistry. A particularly important and timely application is given by inertial confinement fusion, where the fuel capsule has to traverse the WDM regime in a controlled way towards ignition. Unfortunately, the theoretical understanding of such extreme states is rendered notoriously difficult by the complex interplay of a variety of physical effects (Coulomb coupling, thermal excitations, quantum degeneracy, etc.). In practice, density functional theory (DFT) constitutes the workhorse of WDM theory. In this work we present our results on the dynamic structure factor and dynamic dielectric function of warm dense hydrogen computed from first principles using linear response time-dependent density functional theory. In addition, we discuss the relevance of the thermal exchange-correlation effects for the electronic structure in warm
dense hydrogen [1-4].

REFERENCES
[1] Z. Moldabekov, M. Lokamani, J. Vorberger, A. Cangi, T. Dornheim, “Non-empirical Mixing
Coefficient for Hybrid XC Functionals from Analysis of the XC Kernel”, J. Phys. Chem. Lett., 14,
1326-1333 (2023)
[2] Z. Moldabekov, M. Böhme, J. Vorberger, D. Blaschke, T. Dornheim, “Ab Initio Static Exchange–
Correlation Kernel across Jacob’s Ladder without Functional Derivatives”, J. Chem. Theory
Comput., 19, 1286-1299 (2023)
[3] Z. Moldabekov, M. Lokamani, J. Vorberger, A. Cangi, T. Dornheim, “Assessing the accuracy of
hybrid exchange-correlation functionals for the density response of warm dense electrons”, J.
Chem. Phys., 158, 094105 (2023)
[4] Z. Moldabekov, M. Pavanello, M. Böhme, J. Vorberger, T. Dornheim, “Linear-response time-
dependent density functional theory approach to warm dense matter with adiabatic exchange-
correlation kernels”, Phys. Rev. Research 5, 023089 (2023)
[5] Z. Moldabekov, S. Schwalbe, M. Böhme, J. Vorberger, X. Shao, M. Pavanello, F. Graziani, T.
Dornheim, “Bound state breaking and the importance of thermal exchange-correlation effects in warm
dense hydrogen”, J. Chem. Theory Comput., 20, 68-78 (2024)

Hydrogen at extreme temperatures and pressures has significant relevance for cutting-edge technological applications, and its natural occurrence in astrophysical objects further underscores its importance. In this work, we develop a new framework to identify the breaking of bound states due to pressure ionization in bulk hydrogen [1]. Firstly, we show that the dimensionless reduced density gradient (RDG) is a valuable tool for detecting pressure-induced ionization in the medium. Secondly, the generalized RDG is proposed as an effective means for examining the interstitial electronic structure. Finally, our rigorous assessment of a variety of exchange-correlation (XC) functionals in density functional theory calculations for different density regions reveals the crucial role of thermal XC effects in accurately describing density gradients in high-energy density systems. Our exact path integral Monte-Carlo (PIMC) test set generated for this project is freely available online [2]. The insights gained from this research could also have implications for our understanding of astrophysical phenomena, such as white dwarf stars. Furthermore, this study is an addition to our current research on thermal effects in XC functionals, which we are exploring at various complexity levels [3-6].

References:

[1] Z. Moldabekov, S. Schwalbe, M. P. Böhme, J. Vorberger, X. Shao, M. Pavanello, F.
Graziani, T. Dornheim, Journal of Chemical Theory and Computation (in print) (2023).
DOI: 10.1021/acs.jctc.3c00934 ; arXiv:2308.07916.
[2] The data is available according to the FAIR principles on the bound state breaking BSB
GitLab Repository. 2023; https://gitlab.com/theonov13/bsb
[3] Z. Moldabekov, M. Lokamani, J. Vorberger, A. Cangi, and T. Dornheim, The Journal of
Physical Chemistry Letters 14 (5), 1326-1333 (2023).
[4] Z. Moldabekov, M. Lokamani, J. Vorberger, A. Cangi, T. Dornheim, J. Chem. Phys.
158, 094105 (2023).
[5] Z. Moldabekov, T.Dornheim, M. Böhme, J. Vorberger, A. Cangi, J. Chem. Phys. 155,
124116 (2021).
[6] Z. Moldabekov, M. Böhme, J. Vorberger, D. Blaschke, and T. Dornheim, Journal of
Chemical Theory and Computation 19, 1286-1299 (2023)

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

Laser-driven dynamic compression experiments of plastic materials have found surprisingly fast formation of nanodiamonds (ND) via X-ray probing. This mechanism is relevant for planetary models, but could also open efficient synthesis routes for tailored NDs. We investigate the release mechanics of compressed NDs by molecular dynamics simulation of the isotropic expansion of finite size diamond from different P-T states. Analysing the structural integrity along different release paths via molecular dynamic simulations, we found substantial disintegration rates upon shock release, increasing with the on-Hugnoiot shock temperature. We also find that recrystallization can occur after the expansion and hence during the release, depending on subsequent cooling mechanisms. Our study suggests higher ND recovery rates from off-Hugoniot states, e.g., via double-shocks, due to faster cooling. Laser-driven shock compression experiments of polyethylene terephthalate (PET) samples with in situ X-ray probing at the simulated conditions found diamond signal that persists up to 11 ns after breakout. In the diffraction pattern, we observed peak shifts, which we attribute to thermal expansion of the NDs and thus a total release of pressure, which indicates the stability of the released NDs.

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

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

Technetium (Tc) is an element originating mostly from the fission of ²³⁵U and ²³⁹Pu with a yield of 6%.¹ Therefore, ⁹⁹Tc is mainly found in high-level radioactive waste, e.g. from nuclear power or reprocessing plants.² The waste disposal is the subject of numerous studies due to the long half-life of many radionuclides (e.g. ⁹⁹Tc: 2.1 · 10⁵ years)¹ and their high radiotoxicity. One of the most accepted concepts is the deep geological underground repository. A multiple barrier system is planned to reduce the risk of a worst-case scenario, when water ingress could induce the corrosion of the canister containing the waste and, thus, radionuclide release. For the long-term safety, including the construction of effective barriers, the interaction of the radionuclides with different minerals present in the repository needs to be studied at a fundamental level. Tc shows a complex redox chemistry and is considered very mobile compared to cationic radionuclides, due to the presence of the negatively charged TcO₄⁻ under oxidising conditions. However, Tc migration decreases when Tc(VII) is reduced to Tc(IV) since it forms precipitates or is immobilized by mineral surfaces, e.g. with Fe(II) minerals (Fig. 1).³

Vivianite (Fe₃(PO₄)₂ · 8 H₂O) is a naturally occurring Fe(II) mineral under reducing conditions⁵ and can be formed by microorganisms.⁶ Phosphate phases are already being considered as an immobilisation matrix for other radionuclides relevant in deep geological repositories (e.g. ²³⁵U, ²³⁷Np, ²³⁹Pu, ²⁴³Am).⁷ ⁸

This study investigates the retention of Tc by synthetic vivianite particles as a function of pH, Tc concentration and ionic strength on a macroscopic and molecular scale. In addition, Tc(IV) reoxidation experiments were performed.⁴

The synthesis of vivianite was carried out by precipitation from a solution mixture of an iron(II) sulphate and ammonium hydrogen phosphate, as described by Roldán et al..⁹ The product was characterised by Raman microscopy, Mössbauer spectroscopy, powder X-ray diffraction and solubility studies with regard to the pH-dependent behaviour under N₂ atmosphere. The identified phase at pH 5.0 and pH 8.0 is vivianite. At pH 12.0 vivianite transforms into Fe(II)(OH)₂. The change in solid morphology due to the mineralogical modification was also observed with scanning electron microscopy.

Batch contact experiments at N₂ atmosphere were carried out to determine the interaction between vivianite particles suspended in water and KTcO₄. The Tc concentrations in solution were determined by liquid scintillation counting and the Tc-loaded solid was analysed by X-ray photoelectron spectroscopy (XPS). Kinetic contact experiments of 1 µM TcO₄⁻ show that Tc uptake by vivianite increases with longer contact time at pH 8.0 and is complete after 20 days, while no Tc retention takes place at pH 6.5. The Tc-containing solids from experiments at pH 5.0 and pH 12.0 were analysed by XPS to determine the oxidation state of the Tc and Fe. The results show that Tc(IV) was present on the solid surface in all samples analysed. It indicates that Tc removal at high pH values is due to the reductive immobilization of Tc(VII) to Tc(IV) by vivianite. However, at acidic pH values (pH 5.0) Tc(VII) reduction occurs without decreasing the Tc concentration in solution, but by XPS, formerly dissolved Tc(IV) could be detected on the solid surface.

To investigate the remobilisation of reduced Tc(IV), samples obtained after completion of Tc retention experiments at different pH were exposed to ambient atmosphere and Tc concentration was monitored for six months. Under oxidising conditions, no remobilisation of Tc takes place at pH values above pH 8.0. The immobilisation of Tc by vivianite remains complete over the course of six months. This shows a slower Tc(IV) reoxidation than in Tc(IV)-containing FeS₂ mineral phases, where reoxidation starts after 64 days.¹⁰ Additionally, an increase of Tc retention was determined at pH 2.0 and pH 3.0. This can be explained by a time-delayed immobilisation of Tc by the dissolved Fe(II).¹¹

Those promising results show a high affinity of vivianite towards Tc, aided by the reduction of Tc(VII) to Tc(IV) by structural Fe(II).

The authors acknowledge the German Federal Ministry of Education and Research (BMBF) for the financial support of the NukSiFutur TecRad young investigator group (02NUK072).¹²

References:

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The application of Co-Pt thin films as functional elements of novel nanoelectronics and spintronics devices requires the formation of a homogeneous ferromagnetic CoPt phase with tunable magnetic properties. A diffusion-controlled synthesis of this ferromagnetic phase can be implemented through the annealing of deposited Co/Pt bilayers. Apart from thermal treatment, both structural and magnetic properties of such layered stacks can be affected by ion preirradiation. In this work, we, therefore, studied the effect of a two-stage process consisting of preirradiation with 110 keV Ar+/N+ ions followed by post-annealing in vacuum at 550 °С for 30 min on the evolution of the structural, chemical, and magnetic properties of Co/Pt/substrate and Pt/Co/substrate heterostructures. The results obtained for such two-stage processing were compared to those received after single-stage vacuum annealing. It was found that when ion preirradiation is followed by annealing, the diffusion-driven intermixing of Pt and Co leading to the formation of the ferromagnetic Co-Pt phase is slowed down compared to the non-irradiated samples, which is associated with the barrier effect of implanted projectiles. Furthermore, we demonstrate that preirradiation does not compromise the magnetic properties of the samples. For instance, preirradiation leads to a coercivity increase of up to 38% compared to the non-irradiated annealed samples which is attributed to the presence of remaining paramagnetic Pt between the grains of the ferromagnetic A1-CoPt phase. We demonstrate that the applied two-stage processing (consisting of ion preirradiation followed by thermal annealing) of magnetic thin films is a promising approach for tailoring their magnetic properties such as the in-plane coercivity, saturation, and effective magnetization.

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

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

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

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

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

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

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

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

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

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

Nuclear spins are considered as a very promising quantum system for quantum information processing and sensing. Due to their very long spin coherence time, they are a key component of spin-based quantum registers. Nuclear spin hyperpolarization can enhance the signal intensities in magnetic resonance imaging by several orders of magnitude allowing detection of small chemical shifts and analysis of single cells. Due to the small value of the nuclear magneton, an effective way to initialize nuclear spins is first to polarize electron spins using optical excitation and then to transfer this polarization to the nuclear spin via the hyperfine interaction (HFI). Dynamic nuclear polarization (DNP) has been demonstrated in a variety of materials, including GaAs [1], diamond [2] and silicon carbide (SiC) [3].
Coupled electron-nuclear spins represent a promising quantum system, where the optically induced electron spin polarization can be dynamically transferred to nuclear spins via the hyperfine interaction. Most experiments on DNP are performed at cryogenic temperatures and/or in moderate external magnetic fields, the latter approach being very sensitive to the magnetic field orientation. Here, we demonstrate that the 29Si nuclear spins in SiC can be efficiently polarized at room temperature even in the Earth’s magnetic field. We exploit the asymmetric splitting of the optically detected magnetic resonance (ODMR) lines inherent to half-integer S = 3/2 electron spins, such that certain transitions involving 29Si nuclei can be clearly separated and selectively addressed using two radiofrequency fields. As a model system, we use the V3 silicon vacancy (VSi) in 6H-SiC, which has the zero-filed splitting parameter comparable with the HFI constant. Our theoretical model considers DNP under optical excitation in combination with RF driving and agrees very well with the experimental data. These results provide a straightforward approach for controlling the nuclear spin under ambient conditions, and may be an important step toward realizing nuclear hyperpolarization for bioimaging and long nuclear spin memory for quantum networks.

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

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

In this paper, we leverage multimodal data to classify minerals using a multi-stream neural network. In a previous study on the Tinto dataset, which consisted of a 3D hyperspectral point cloud from the open-pit mine Corta Atalaya in Spain, we successfully identified mineral classes by employing various deep learning models. However, this prior work solely relied on hyperspectral data as input for the deep learning models. In this study, we aim to enhance accuracy by incorporating multimodal data, which includes hyperspectral images, RGB images, and a 3D point cloud. To achieve this, we have adopted a graph-based neural network, known for its efficiency in aggregating local information, based on our past observations where it consistently performed well across different hyperspectral sensors. Subsequently, we constructed a multi-stream neural network tailored to handle multimodality. Additionally, we employed a channel attention module on the hyperspectral stream to fully exploit the spectral information within the hyperspectral data. Through the integration of multimodal data and a multi-stream neural network, we achieved a notable improvement in mineral classification accuracy: 19.2%, 4.4%, and 5.6% on the LWIR, SWIR, and VNIR datasets, respectively.

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

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

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

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

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

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

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

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

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

Background

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

Methods

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

Results

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

Conclusion

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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