Publications Repository - Helmholtz-Zentrum Dresden-Rossendorf

The bone-resorbing activity of osteoclasts plays a critical role in the life-long remodeling of our bones that is perturbed in many bone loss diseases. Multinucleated osteoclasts are
formed by the fusion of precursor cells, and larger cells – generated by an increased number of cell fusion events – have higher resorptive activity. We find that osteoclast fusion and bone resorption are promoted by reactive oxygen species (ROS) signaling and by an unconventional low molecular weight species of La protein, located at the osteoclast surface. Here, we develop the hypothesis that La’s unique regulatory role in osteoclast multinucleation and function is controlled by an ROS switch in La trafficking. Using antibodies that recognize reduced or oxidized species of La, we find that differentiating osteoclasts enrich an oxidized species of La at the cell surface, which is distinct from the reduced La species conventionally localized within cell nuclei. ROS signaling triggers the shift from reduced to oxidized La species, its dephosphorylation and delivery to the surface of osteoclasts, where La promotes multinucleation and resorptive activity. Moreover, intracellular ROS signaling in differentiating osteoclasts oxidizes critical cysteine residues in the C-terminal half of La,
producing this unconventional La species that promotes osteoclast fusion. Our findings suggest that
redox signaling induces changes in the location and function of La and may represent a promising
target for novel skeletal therapies.

Despite the extensive body of research conducted on the fusion of lidar and hyperspectral data for land cover classification in urban areas, the predominant approach has been the utilization of rasterized lidar data merged with hyperspectral data. This image-centric methodology tends to overlook the primary advantage inherent in lidar technology—namely, the production of 3D point cloud data. In our work, we present a framework demonstrating how we infer semantic information from 3D point cloud data, comprising both lidar and hyperspectral features—a concept we refer to as a 3D hyperspectral point cloud. We illustrate the generation of hyperspectral point clouds and evaluate the performance of various deep learning models for point learning. Our findings on the original test data of the 2018 IEEE GRSS Data Fusion Challenge, disclosed by IEEE Image Analysis and Data Fusion Technical Committee, indicate that recent deep learning models not only produce better shapes for predicted objects but also yield more precise semantic information. Finally, we plan to release the 3D hyperspectral point cloud data to the community, hoping to inspire future studies on data fusion in the point cloud domain.

Recent advancements in Remote Sensing (RS) for Change Detection (CD) and Change Captioning (CC) have seen substantial success by adopting deep learning techniques. Despite these advances, existing methods often handle CD and CC tasks independently, leading to inefficiencies from the absence of synergistic processing. In this paper, we present ChangeMinds, a novel unified multi-task framework that concurrently optimizes CD and CC processes within a single, end-to-end model. We propose the change-aware long short-term memory module (ChangeLSTM) to effectively capture complex spatiotemporal dynamics from extracted bi-temporal deep features, enabling the generation of universal change-aware representations that effectively serve both CC and CD tasks. Furthermore, we introduce a multi-task predictor with a cross-attention mechanism that enhances the interaction between image and text features, promoting efficient simultaneous learning and processing for both tasks. Extensive evaluations on the LEVIR-MCI dataset, alongside other standard benchmarks, show that ChangeMinds surpasses existing methods in multi-task learning settings and markedly improves performance in individual CD and CC tasks. Codes and pre-trained models will be available online.

Mining change detection requires dedicated datasets because it includes unique objects such as pits or quarries, tailings dams, overburden, processing plants, haul roads, access roads, buildings/sheds, mining and blasting equipment, and plants, among others. This paper introduces a benchmark, large dataset for mining change detection, termed the MineNet-CD, to facilitate large-scale change detection. The proposed dataset contains a total of 100 high-resolution bi-temporal mining images from all over the world with corresponding ground truth. Unlike existing datasets, the images of MineNet-CD exhibit significant background, topological variation, and well-defined ground truth that ignores insignificant change maps. The work analyzes the efficacy of state-of-the-art deep learning methods for change detection. The results demonstrate that more efficient and advanced networks are required to accurately predict the change maps. The dataset and code are available at https://github.com/EricYu97/MineNet-CD.

This work numerically examines the stability of this configuration in the presence of a nearby vertical wall. The focus is on moderately inertial regimes, where two bubbles rising initially in line typically separate laterally from each other under unbounded conditions. In the presence of the wall, our results indicate that while the path of the bubble pair predominantly separates laterally, the plane of separation largely depends on the wall-bubble interaction. This interaction involves a competition between two distinct effects, with the dominance determined by the ratios of buoyancy-to-viscous and buoyancy-to-capillary forces, which define the Galilei $(\Ga)$ and Bond $(\Bo)$ numbers, respectively. When $\Bo$ is below a critical $\Ga$-dependent threshold, irrotational effects dominate, initially stabilizing both bubbles near the wall until horizontal separation among them occurs in the wall-parallel plane. Conversely, at higher $\Bo$, vortical effects dominate such that both bubbles migrate away from the wall. During the departure, asymmetric interactions cause the wall-normal velocities of the two bubbles to differ, leading to horizontal separation in the wall-normal plane. These two separation motions, both newly identified in the present study, are found to result from two distinct mechanisms: one associated with the shear flow generated in the gap separating the wall and the leading bubble, which attracts the trailing bubble toward the wall, and the other linked to vortex shedding from the leading bubble, which promotes the trailing bubble’s faster escape from the wall. A slight angular deviation favours separation in the wall-parallel plane, promoting the formation of a near-wall, bubble-rich layer as observed in prior investigations of buoyancy-driven, bubble-laden flows.

HZDR’s SRF Gun-II is an excellent demonstration of SRF technology application in the field of electron sources operating in continuous wave mode. As well known, quality of the photocathode is crucial for operational stability and reliability of an SRF gun. In this contribution, various studies on Cs2Te cathodes, including cleaning, preparation, transport/insertion, RF and beam operation will be summarised. We will look back at the achievements and open issues, and discuss possible improvements and further development.

The density-density correlations of the non-interacting finite temperature electron gas are discussed in detail. Starting from the ideal linear density response function and utilizing general relations from linear response theory, known and novel expressions are derived for the pair correlation function, static structure factor, dynamic structure factor, thermal structure factor and imaginary time correlation function. Applications of these expressions in the classical mapping approach, self-consistent dielectric formalism and equation-of-state construction are analyzed in depth.

Abstract—Developing a cross-domain classification model for
remote sensing images has drawn significant attention in the
literature. By leveraging the open-set Unsupervised Domain
Adaptation (UDA) technique, the generalization performance of
deep learning models has been improved with the capability to
recognize unknown categories. However, it remains challenging
to explore distribution patterns in the target domain using
uncertain category-wise supervision from unlabeled datasets
while reducing negative transfer caused by unknown samples. To
develop a robust open-set UDA framework, this paper presents
Prototypical Unknown-aware Multiview Consistency Learning
(PUMCL) designed for remote sensing scene classification across
heterogeneous domains. Specifically, it employs a consistency
learning scheme with multiview and multilevel perturbations
to improve feature learning from unlabeled target samples. An
entropy separation strategy is utilized to facilitate open-set detection
and recognition during adaptation, enabling unknown-aware
feature alignment. Furthermore, the introduction of prototypical
constraints optimizes pseudo-label generation through online
denoising and promotes a compact category-wise feature subspace
for improved class separation across domains. Experiments
conducted on six cross-domain scenarios using AID, NWPU, and
UCMD datasets demonstrate the method’s superior performance
compared to nine state-of-the-art approaches, achieving a gain
of 4.5% to 21.2% in mIoU. More importantly, it shows promising
class separability with clear boundaries between different classes
and compact clustering of unknown samples in the feature space.
The source code will be available at https://github.com/zxk688.

Curvilinear magnetism is a framework, which helps understanding the impact of geometric curvature on complex magnetic responses of curved 1D wires and 2D shells [1-3]. This approach provides means to modify conventional or to launch novel functionalities by tailoring curvature and 3D shape of magnetic thin films and nanowires [3]. In this talk, we will address fundamentals of curvature-induced effects in magnetism and review the envisioned application scenarios. In particular, we will demonstrate that curvature allows tailoring fundamental anisotropic and chiral magnetic interactions and enables fundamentally new nonlocal chiral symmetry breaking effect [4]. The topology of the geometry of 3D shaped magnetic objects allows stabilizing multiple solitons within a confined nanoarchitecture [5]. Those are relevant for numerous research and technology fields ranging from non-conventional computing and spin-wave splitters for low-energy magnonics. The application potential of geometrically curved magnetic architectures is being explored as mechanically reshapeable magnetic field sensors for automotive applications, spin-wave filters, high-speed racetrack memory devices, magnetic soft robots [6] as well as on-skin interactive electronics relying on thin films [7-9] as well as printed magnetic composites [10,11] with appealing self-healing performance [12]. This opens perspectives for magnetoelectronics in smart wearables, interactive printed electronics and motivates further explorations towards the realization of eco-sustainable magnetic field sensing relying on biocompatible and biodegradable materials [13-15].

[1] P. Gentile et al., Electronic materials with nanoscale curved geometries. Nature Electronics (Review) 5, 551 (2022).
[2] P. Makushko et al., A tunable room-temperature nonlinear Hall effect in elemental bismuth thin films. Nature Electronics 7, 207 (2024).
[3] D. Makarov et al., New Dimension in Magnetism and Superconductivity: 3D and Curvilinear Nanoarchitectures. Advanced Materials (Review) 34, 2101758 (2022).
[4] O. M. Volkov et al., Chirality coupling in topological magnetic textures with multiple magnetochiral parameters. Nature Communications 14, 1491 (2023).
[5] O. Volkov et al., Three-dimensional magnetic nanotextures with high-order vorticity in soft magnetic wireframes. Nature Communications 15, 2193 (2024).
[6] M. Ha et al., Reconfigurable Magnetic Origami Actuators with On-Board Sensing for Guided Assembly. Advanced Materials 33, 2008751 (2021).
[7] G. S. Canon Bermudez et al., Magnetosensitive e-skins for interactive devices. Advanced Functional Materials (Review) 31, 2007788 (2021).
[8] J. Ge et al., A bimodal soft electronic skin for tactile and touchless interaction in real time. Nature Communications 10, 4405 (2019).
[9] G. S. Canon Bermudez et al., Electronic-skin compasses for geomagnetic field driven artificial magnetoception and interactive electronics. Nature Electronics 1, 589 (2018).
[10] M. Ha et al., Printable and Stretchable Giant Magnetoresistive Sensors for Highly Compliant and Skin-Conformal Electronics. Advanced Materials 33, 2005521 (2021).
[11] E. S. Oliveros Mata et al., Dispenser printed bismuth-based magnetic field sensors with non-saturating large magnetoresistance for touchless interactive surfaces. Advanced Materials Technologies 7, 2200227 (2022).
[12] R. Xu et al., Self-healable printed magnetic field sensors using alternating magnetic fields. Nature Communications 13, 6587 (2022).
[13] X. Wang et al., Printed magnetoresistive sensors for recyclable magnetoelectronics. J. Mater. Chem. A 12, 24906 (2024).
[14] E. S. Oliveros Mata et al., Magnetically aware actuating composites: Sensing features as inspiration for the next step in advanced magnetic soft robotics. Phys. Rev. Appl. (Review) 20, 060501 (2023).
[15] L. Guo et al., Printable magnetoresistive sensors: A crucial step toward unconventional magnetoelectronics. Chinese Journal of Structural Chemistry (Review) 100428 (2024).

Composites consisting of magnetic fillers in polymers and elastomers enable new types of applications in soft robotics, reconfigurable actuation and sensorics. In this presentation we will focus on the development of magnetic composites to realize solution processable and eco-sustainable magnetic field sensors. This functional electronic component is a currently missing member in the family of eco-sustainable electronics. In particular, we will present approaches to realize magnetic composites based on materials revealing high degree of spin polarization and electrical percolation, which result in printed magnetic field sensors [1,2]. First, we will review recent demonstrations of printed magnetoelectronics that can be stretchable, skin-conformal, capable of detection in low magnetic fields and withstand extreme mechanical deformations [3,4]. The use of Bi as a functional filler of a composite [3] acts as a green alternative to conventional environmentally polluting Ni-based sensors [4]. We show that printed Bi sensors reveal a linear nonsaturating magnetoresistive response, which is a fingerprint of the electronic band structure of the Bi material - a higher order topological insulator. We feature the potential of printed magnetic field sensors to turn any object into an interactive surface via the realization of a smart magnetosensitive wallpaper or in-mold magnetoelectronics [3]. We will introduce a technology to realize self-healable magnetic field sensors, which can be repaired upon mechanical damage, hence extending the life-time of magnetoelectronics and reducing the amount of toxic magnetic waste [5]. This opens new perspectives for magnetoelectronics in smart wearables, interactive printed electronics and motivates further explorations towards the realization of recyclable magnetoelectronics [6]. For the latter, we will discuss eco-sustainable, namely biocompatible and biodegradable magneto sensitive devices, which can help to minimise electronic waste and bring magnetoelectronics to new application fields in medical implants, health monitoring, and realization of self-aware soft-bodied robots [1].

[1] E. S. Oliveros Mata et al., Magnetically aware actuating composites: Sensing features as inspiration for the next step in advanced magnetic soft robotics. Phys. Rev. Appl. (Review) 20, 060501 (2023).
[2] L. Guo et al., Printable magnetoresistive sensors: A crucial step toward unconventional magnetoelectronics. Chinese Journal of Structural Chemistry (Review) 100428 (2024).
[3] E. S. Oliveros Mata et al., Dispenser printed bismuth-based magnetic field sensors with non-saturating large magnetoresistance for touchless interactive surfaces. Adv. Mater. Technol. 7, 2200227 (2022).
[4] M. Ha et al., Printable and stretchable giant magnetoresistive sensors for highly compliant and skin-conformal electronics. Adv. Mater. 33, 2005521 (2021).
[5] R. Xu et al., Self-healable printed magnetic field sensors using alternating magnetic fields. Nature Communications 13, 6587 (2022).
[6] X. Wang et al., Printed magnetoresistive sensors for recyclable magnetoelectronics. J. Mater. Chem. A 12, 24906 (2024).

Composites consisting of magnetic fillers in polymers and elastomers enable new types of applications in soft robotics, reconfigurable actuation and sensorics. We will introduce lightweight, durable, untethered and ultrafast soft-bodied robots that can walk, swim, levitate, transport cargo, and perform collaborative tasks being driven using magnetic far fields [1,2] and near fields [3,4]. Reconfigurable magnetic origami actuators [2] can be equipped with ultrathin magnetosensitive e-skins [5] to decide on and control the actuation pattern. The on-board sensing adds awareness to soft-bodied magnetic actuators enabling them to act and be controlled similar to conventional robotic devices [6]. Magnetic composites containing functional fillers with high degree of spin polarization can be readily used to realise not only actuators but also solution-processable magnetic field sensors [7]. We will demonstrate that printed magnetoelectronics can be stretchable, skin-conformal, capable of detection in low magnetic fields and withstand extreme mechanical deformations [8,9]. The use of Bi as a functional filler of a composite [9] acts as a green alternative to conventional environmentally polluting Ni-based sensors [8]. We show that printed Bi sensors reveal a linear nonsaturating magnetoresistive response, which is a fingerprint of the electronic band structure of the Bi material - a higher order topological insulator. We feature the potential of printed magnetic field sensors to turn any object into an interactive surface via the realization of a smart magnetosensitive wallpaper or in-mold magnetoelectronics [9]. We will present a technology to realize self-healable magnetic field sensors, which can be repaired upon mechanical damage, hence extending the life-time of magnetoelectronics and reducing the amount of toxic magnetic waste [10]. This opens new perspectives for magnetoelectronics in smart wearables, interactive printed electronics and motivates further explorations towards the realization of recyclable magnetoelectronics [11]. For the latter, we will discuss eco-sustainable, namely biocompatible and biodegradable magneto sensitive devices, which can help to minimise electronic waste and bring magnetoelectronics to new application fields in medical implants and health monitoring [6].

[1] X. Wang et al., Untethered and ultrafast soft-bodied robots. Commun. Mater. 1, 67 (2020).
[2] M. Ha et al., Reconfigurable magnetic origami actuators with on-board sensing for guided assembly. Adv. Mater. 33, 2008751 (2021).
[3] M. Richter et al., Locally addressable energy efficient actuation of magnetic soft actuator array systems. Advanced Science 2302077 (2023).
[4] L. Masjosthusmann et al., Miniaturized variable stiffness gripper locally actuated by magnetic fields. Advanced Intelligent Systems 6, 2400037 (2024).
[5] G. S. Canon Bermudez et al., Magnetosensitive e-skins for interactive devices. Adv. Funct. Mater. (Review) 31, 2007788 (2021).
[6] E. S. Oliveros Mata et al., Magnetically aware actuating composites: Sensing features as inspiration for the next step in advanced magnetic soft robotics. Phys. Rev. Appl. (Review) 20, 060501 (2023).
[7] L. Guo et al., Printable magnetoresistive sensors: A crucial step toward unconventional magnetoelectronics. Chinese Journal of Structural Chemistry (Review) 100428 (2024).
[8] M. Ha et al., Printable and stretchable giant magnetoresistive sensors for highly compliant and skin-conformal electronics. Adv. Mater. 33, 2005521 (2021).
[9] E. S. Oliveros Mata et al., Dispenser printed bismuth-based magnetic field sensors with non-saturating large magnetoresistance for touchless interactive surfaces. Adv. Mater. Technol. 7, 2200227 (2022).
[10] R. Xu et al., Self-healable printed magnetic field sensors using alternating magnetic fields. Nature Communications 13, 6587 (2022).
[11] X. Wang et al., Printed magnetoresistive sensors for recyclable magnetoelectronics. J. Mater. Chem. A 12, 24906 (2024).

When radionuclides (RN) enter the food chain and are ingested by humans, they pose a potential health risk due to their radio- and chemotoxicity. To minimize the health risk, decorporation agents (DA), which are usually strong complexants, are used after the accidental incorporation of RN to increase their excretion. In order to accurately assess the health risk after oral ingestion and to apply effective decontamination methods, it is essential to understand the processes of (bio)chemistry and speciation of RN at the molecular and cellular level. Within the joint research project RADEKOR: “Speciation and transfer of radionuclides in the human organism especially taking into account decorporation agents”, molecular speciation studies of RN in artificial biofluids of the digestive system of humans and cytotoxicity studies with respective human and rat renal cell lines in vitro both in the absence and presence of DA were performed.

As DA we investigated i) aminopolycarboxylate diethylenetriaminepentaacetic acid DTPA as the only approved and commercially used DA and ii) some promising new chelators like the hydroxypyridinone 3,4,3-(LI-1,2-HOPO) (HOPO) and 1-hydroxy-ethylidene-1,1-diphosphonic acid (HEDP), which was formerly used as a pharmaceutical. First, the complex formation of the non-radioactive An(III) analogue Eu(III) with HEDP in aqueous solution and cell culture medium was studied. Second, Eu(III) and Am(III) cytotoxicity onto kidney cells was investigated in absence and presence of DTPA and HOPO. Finally, the molecular speciation of Eu(III) and Am/Cm(III) with and w/o DTPA and HOPO was studied in both cell culture medium and exposed renal cells. The results of this work contribute to a better understanding of the effect of DA after RN incorporation at the molecular level and support making them more effective in the future.

When radionuclides (RN) enter the food chain and are ingested by humans, they can present significant health risks due to their radiotoxic and chemotoxic properties. To mitigate these risks, decorporation agents (DA), which are typically strong chelators, are employed after accidental RN exposure to facilitate their removal from the body. A thorough understanding of the (bio)chemical behavior and speciation of RN at both the molecular and cellular levels is essential for assessing health impacts and applying effective decontamination techniques. In the joint BMBF project RADEKOR, studies were conducted to investigate the molecular speciation of RN in artificial digestive biofluids, alongside with in vitro cytotoxicity assessments using human and rat kidney cell lines, with and without DA.

As DA we investigated i) aminopolycarboxylate diethylenetriaminepentaacetic acid (DTPA) as the only approved and commercially used DA, ii) alternative aminocarboxylates like ethylenediaminetetraacetic acid (EDTA) or ethyleneglycoltetraacetic acid (EGTA), and iii) some promising new chelators like the hydroxypyridinone 3,4,3-(LI-1,2-HOPO) (HOPO) and 1-hydroxyethylidene-1,1-diphosphonic acid (HEDP), which was formerly used as a pharmaceutical. The complex formation of Eu(III) as a non-radioactive analogue for An(III) with EGTA was studied along with its molecular speciation in simulated body fluids in presence and absence of DTPA, EGTA, and HOPO. Furthermore, the molecular speciation of U(VI) in simulated body fluids and cell culture medium as well as its cytotoxicity onto kidney cells was investigated in absence and presence of DTPA, HEDP, and HOPO. The results of this work contribute to a better understanding of the effect of DA after RN incorporation at the molecular level and support making them more effective in the future.

The vast repository of van der Waals (vdW) materials supporting polaritons offers numerous possibilities to tailor electromagnetic waves at the nanoscale. The development of twistoptics—the modulation of the optical properties by twisting stacks of vdW materials—enables directional propagation of phonon polaritons (PhPs) along a single spatial direction, known as canalization. Here we demonstrate a complementary type of directional propagation of polaritons by reporting the visualization of unidirectional ray polaritons (URPs). They arise naturally in twisted hyperbolic stacks with very different thicknesses of their constituents, demonstrated for homostructures of -MoO3 and heterostructures of -MoO3 and -Ga2O3. Importantly, their ray-like propagation, characterized by large momenta and constant phase, is tunable by both the twist angle and the illumination frequency. Apart from their fundamental importance, our findings introduce twisted asymmetric stacks as efficient platforms for nanoscale directional polariton propagation, opening the door for applications in nanoimaging, (bio)-sensing, or polaritonic thermal management.

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 widely accepted strategies is the deep geological underground repository. This approach relies on a multi-barrier system designed to minimize the risk of a worst-case scenario, where water intrusion could lead to the corrosion of the waste canister and the subsequent release of radionuclides. For the long-term safety, including the construction of effective barriers, it is essential to study the interaction of radionuclides with the various minerals present in the repository at a fundamental level. Tc poses a particular challenge due to its complex redox chemistry high mobility in its oxidized form TcO₄¯, under oxidising conditions. However, Tc migration decreases significantly when Tc(VII) is reduced to Tc(IV), as it then forms precipitates or becomes immobilized by mineral surfaces such as Fe(II) minerals.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, while the Tc-loaded solids were 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 XPS results of Tc-containing solids from experiments at pH 5.0 and pH 12.0 show that Tc(IV) was present on the solid surface. It indicates that Tc removal at high pH values is due to the reductive immobilization of Tc(VII) to Tc(IV) by vivianite. In contrast, 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. Further X-ray absorption spectroscopy (XAS) measurements were performed to determine the molecular environment of Tc when it was directly presence in the vivianite synthesis (coprecipitate) and after interaction with vivianite at pH 8.5 and 11.0. The first preliminary results indicate that Tc(IV) coordination environment drastically differs when changing pH and Tc concentration. Their final structural rearrangement is yet to be deciphered.

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:

1 NDS-Datenbank, https://www-nds.iaea.org, (accessed 4 June 2024).
2 A. H. Meena, Y. Arai, Environ. Chem. Lett., 2017, 15, 241–263.
3 C. I. Pearce, R. C. Moore, J. W. Morad, R. M. Asmussen, S. Chatterjee, A. R. Lawter, T. G. Levitskaia, J. J. Neeway, N. P. Qafoku, M. J. Rigali, S. A. Saslow, J. E. Szecsody, P. K. Thallapally, G. Wang, V. L. Freedman, Sci. Total Environ., 2020, 716, 132849.
4 C. Börner, Masterarbeit, Technische Universität Dresden, 2023.
5 A. Al-Borno, M. B. Tomson, Geochim. Cosmochim. Acta, 1994, 58, 5373–5378.
6 J. M. McBeth, J. R. Lloyd, G. T. W. Law, F. R. Livens, I. T. Burke, K. Morris, Mineral. Mag., 2011, 75, 2419–2430.
7 P. Sengupta, J. Hazard. Mater., 2012, 235–236, 17–28.
8 M. R. Rafiuddin, G. Donato, S. McCaugherty, A. Mesbah, A. P. Grosvenor, ACS Omega, 2022, 7, 39482–39490.
9 R. Roldán, V. Barrón, J. Torrent, Clay Miner., 2002, 37, 709–718.
10 D. M. Rodríguez, N. Mayordomo, D. Schild, S. Shams Aldin Azzam, V. Brendler, K. Müller, T. Stumpf, Chemosphere, 2021, 281, 130904.
11 J. M. Zachara, S. M. Heald, B. H. Jeon, R. K. Kukkadapu, C. Liu, J. P. McKinley, A. C. Dohnalkova, D. A. Moore, Geochim. Cosmochim. Acta, 2007, 71, 2137–2157.
12 TecRad-group, https://www.hzdr.de/db/Cms?pNid=1375, (accessed 4 June 2024).

Background: Oropharynx cancer is characterized by an increasing incidence and a relatively good prognosis, especially in human papilloma virus associated disease. Nonetheless, a considerable amount of patients develops metachronous distant metastases, identification of these patients is an urgent medical need.
Methods: This is a retrospective evaluation of 431 patients from five European centers and 3 public repositories. All patients underwent pre-treatment 18f-flurodeoxyglucose (FDG) Positron emission tomography (PET) staging without evidence for distant metastases and primary radiotherapy/ chemoradiation. The cohort was split into an explorative group (N=366) and a validation group (N=65). Primary tumor and lymphnodes were manually delineated in the explorative group and automatically delineated by a convolutional neuronal network (CNN) that had been trained on the explorative contours in the validation group. Quantitative FDG-PET parameters standardized uptake value (SUV), metabolic tumor volume (MTV) and total lesion glycolysis (TLG) were calculated for primary tumors (prim) and tumor plus lymphnodes (all). Association of these quantitative parameters with freedom from distant metastases (FFDM) and overall survival (OS) was tested by uni- and multivariate cox regression analyses and both parameters were compared using bootstrapping.
Results: In the explorative group univariate analyses revealed an association of metric MTVprim (p = 0.022), MTVall (p < 0.001) and TLGall (p < 0.001) with FFDM, binarized parameters were also associated with FFDM (p < 0.001 for all three and p = 0.002 for TLGprim). Bootstrap analyses revealed a significantly better association of TLGall compared to TLGprim with FFDM (p = 0.02). MTVall and TLGall remained significantly associated with FFDM upon multivariate testing (p=0.002, p=0.031, respectively).
In the validation group the cutoff value for TLGall was also significantly associated with FFDM (HR=3.1, p=0.045). Additional analyses with manually delineated contours of the validation cohort revealed a similar effect (TLGall HR=3.47, p=0.026). No considerable differences between HPV positive and negative disease were observed.
Conclusions: TLGall is a promising biomarker to select OPC patients with high risk for metachronous distant metastases.

This article provides an introduction to nuclear magnetic resonance spectroscopy in pulsed magnetic fields (PFNMR), focussing on its capabilities, applications, and future developments in research involving high magnetic fields. It highlights the significance of PFNMR in enhancing the understanding of solid-state materials, with particular emphasis on those exhibiting complex interactions and strong electronic correlations. Several technical aspects are discussed, including the challenges associated with high-frequency NMR experiments. The power of PFNMR is showcased through several examples, including studies on the topical materials LiCuVO₄, SrCu₂(BO₃)₂, and CeIn₃, offering insights into their magnetic and electronic properties at high magnetic fields. The article also discusses possible future directions for the technique, including improvements in PFNMR instrumentation and the exploration of materials under extreme conditions. This exposition underscores the role of PFNMR in advancing the frontiers of materials-science research.

Hydride superconductors continue to fascinate the communities of condensed matter physics and material scientists because they host the promising near room-temperature superconductivity. Current research has concentrated on the new hydride superconductors with the enhancement of the superconducting transition temperature (T_c). The multiple extreme conditions (high pressure/temperature and magnetic field) will introduce new insights into hydride superconductors. The study of transport properties under very high magnetic fields facilitates the understanding of superconductivity in conventional hydride superconductors. In the present work, we report experimental evidence of an unusual metal state in a newly synthesized cubic A15-type La₄H₂₃ that exhibits superconductivity with a T_c reaching 105 K at 118 GPa. A large negative magnetoresistance is observed in strong pulsed magnetic fields in the non-superconducting state of this compound below 40 K. Moreover, we construct the full magnetic phase diagram of La₄H₂₃ up to 68 T at high pressure. The present work reveals anomalous electronic structural properties of A15-La₄H₂₃ under high magnetic fields, and therefore has great importance with regard to advancing the understanding of quantum transport behaviors in hydride superconductors.

Collective behavior of spins, frustration-induced strong quantum fluctuations, and subtle interplay between competing degrees of freedom in quantum materials can lead to correlated quantum states with exotic excitations that are essential ingredients for establishing paradigmatic models and have immense potential for quantum technologies. Disorder is ubiquitous in real materials, and the detailed insights into the role of disorder on the intriguing ground state borne out of quenched randomness provide a route towards the design and discovery of functional quantum materials. Herein we report magnetization, specific heat, electron spin resonance, and muon spin resonance studies on a 3d-electron-based antiferromagnet Sr₃CuTa₂O₉. The negative value of Curie-Weiss temperature, obtained from the Curie-Weiss fit of high-temperature magnetic susceptibility data indicates the presence of antiferromagnetic interaction between Cu²⁺ moments. Specific heat data show the absence of long-range magnetic ordering down to 64 mK despite a reasonably strong exchange interaction between Cu²⁺ (S = 1/2) spins as reflected from a Curie-Weiss temperature of −27 ± 1 K. The power-law behavior and the data collapse of specific heat and magnetization data evince the emergence of a random-singlet state in Sr₃CuTa₂O₉. The power-law-like spin autocorrelation function and the data collapse of muon polarization asymmetry with longitudinal field dependence of t/(μ₀H)^γ further support credence to the presence of a randomness-induced quantum disordered state. Our results suggest that randomness induced by disorder is an alternate route to realize quantum spin disordered state in this antiferromagnet.

We report magnetic susceptibility, high-field magnetization, muon spin relaxation, and electron spin resonance measurements of the breathing pyrochlore antiferromagnets LiGa_1−xIn_xCr₄O₈ (x = 0.2, 0.5). Unlike the previously proposed spin-glass-like phase for 0.1 < x < 0.75, we find no signature for spin glassiness and phase segregation in both the x = 0.2 and 0.5 compounds. Instead, we identify a two-step magnetic transition with a partial spin freezing at T^∗ = 12 K (x = 0.2) and 9 K (x = 0.5) followed by quasistatic order at T_m = 6 K (x = 0.2) and 3 K for (x = 0.5). In addition, for T_m < T < T^∗, we observe evidence of a competition between fast and slow spin dynamics, suggesting a thermal and temporal distribution of spin correlations. Our findings underscore the possibility of realizing novel magnetic phases by tuning bond alternation and introducing bond disorder through chemical substitution.

Ni-Co-Mn-Ti all-d Heusler alloys are attracting considerable attention for solid-state caloric cooling applications due to their promising combination of excellent caloric and mechanical properties. Here, we report on the maximum attainable magnetocaloric effect in Ni₃₇Co₁₃Mn_34.5Ti_15.5, which shows a first-order magnetostructural martensitic transformation around room temperature. Heat capacity measurements reveal a giant transition entropy change of 43.5 J(kgK)⁻¹ and are utilized to estimate the magnetocaloric effect as well as the magnetic fields required to saturate it in isothermal and adiabatic conditions. Confirming the results based on this approach, we achieve maximum isothermal entropy changes and directly measured adiabatic temperature changes of 37.8 J(kgK)⁻¹ and −20.2 K, respectively. Thus, the herein reported maximum attainable magnetocaloric effect outperforms classical Ni-Mn-based Heusler alloys, such as Ni(-Co)-Mn-In. Especially the saturated adiabatic temperature change surpasses all previously published values of magnetic field-induced first-order phase transitions measured around room temperature in pulsed magnetic fields in recent years. Thereby, we demonstrate that Ni(-Co)-Mn-Ti Heusler alloys are particularly suitable for the application of sufficiently large external stimuli to fully induce the phase transition and exploit their intrinsically large caloric effect.

The evolution of the critical superconducting temperature and field, quantum oscillation frequencies, and effective mass m∗ in underdoped YBa₂Cu₃O_7−δ (YBCO) crystals (p = 0.11, with p the hole concentration per Cu atom) points to a partial suppression of the charge orders with increasing pressure up to 7 GPa, mimicking doping. Application of pressures up to 25 GPa pushes the sample to the overdoped side of the superconducting dome. In contrast to other cuprates, or to doping studies on YBCO, the frequencies of the quantum oscillations measured in that pressure range do not support the picture of a Fermi-surface reconstruction in the overdoped regime, but possibly point to the existence of a new charge order.

This paper delves into the connection between flat and curvilinear magnetization dynamics. For this, we numerically study the evolution of the magnon spectrum of rectangular waveguides upon rolling its cross section up to a full tube. Magnon spectra are calculated over a wide range of magnetization states using a finite-element dynamic-matrix method, which allows us to trace the evolution of the magnon frequencies and several critical magnetic fields with increasing curvature. By analyzing the parity of the higher-order magnon modes, we find a curvature-induced mode heterosymmetry that originates from a chiral contribution to the exchange interaction and is related to the Berry phase of magnons in closed loops. Importantly, this curvature-induced parity loss has profound consequences for the linear coupling between different propagating magnons, allowing for hybridization between initially orthogonal modes. In this context, we demonstrate the integral role of edge modes in forming the magnon spectrum in full tubes. Our findings provide theoretical insights into curvilinear magnetization dynamics and are relevant for interpreting and designing experiments in the field.

Progress in fabrication of curvilinear magnetic nanoarchitectures is enabled by a variety of methods oriented on single free-standing objects like focused electron/ion beam induced deposition or glancing-angle deposition. Effects of interest are mostly related to anisotropic and chiral responses originating in exchange interactions [1]. Recently, is has been shown that the magnetostatic interaction offers another possibility of non-local symmetry breaking in 3D samples [2]. Asymmetries in geometric shapes lead to magnetic symmetry breaking and even lifting degeneracy between magnetic vortices of opposite chiralities [3].
Here, we report recent advances of scalable fabrication of large arrays of magnetic nanostructures and the observation of magnetostatic effects in curvilinear shells. Periodic structures over several cm scales consisting of 50 nm thin Permalloy objects were fabricated with nanoflower shapes separated by deep valleys with small curvatures at characteristic spatial scales of about 400 nm. The shell keeps periodicity over cm-large scales. We were able to transfer the shell from Aluminium template to a TEM grid, to allow for characterization of magnetic textures by MOKE, MTXM and holography. On a microscale, due to the interaction between the uniformly magnetized valleys, one can observe the interaction domains with additional 4-fold symmetry, formed due to the corresponding geometrical symmetry of the valleys. This happens because each valley is magnetized almost uniformly following its surface. The nanoflowers support a variety of magnetic textures. The ground state of the nanoflower is the magnetic vortex with four edge states. The vortex line is shifted from the origin and is bent with zero torsion and curvature of about 0.027 nm-1. This asymmetric state is formed due to the interaction of surface and volume magnetostatic charges. High-energy states include the so-called flower state, several vortices bounded within single nanoflower and purely symmetric configuration with a vortex in the center of the nanoflower. In conclusion, these ordered arrays of magnetic architectures of complex shape enable further research in nonlinear magnetization dynamics, 3D magnonics and curvilinear spintronics.

[1] D. Makarov and D. D. Sheka, Ed., Springer International Publishing (2022)
[2] D. D. Sheka et al., Communications Physics, 3(1), 128 (2020)
[3] O. M. Volkov et al., Nature Communications, 14(1), 1491 (2023)

Due to climatic changes, excessive grazing, and deforestation, semi-arid and arid ecosystems are vulnerable to desertification and land degradation. Adversely affected biological productivity has a negative impact on social, economic, and environmental factors. The term 'arid ecosystems' refers not only to water-scarce landscapes but also to nutrient-poor environments. Specifically, the vegetation cover loses spatial homogeneity as aridity increases, and the self-organized heterogeneous vegetation patterns developed could eventually collapse into a bare state. It is still unclear whether this transition would be gradual or abrupt, leading to the often-called catastrophic shift of ecosystems. Several studies suggest that environmental inhomogeneities in time or space can promote a gradual transition to bare soil, thus avoiding catastrophic shifts. Environmental inhomogeneities include non-uniformities in the spatial distribution of precipitation, spatial irregularities in topography and other external factors. Employing a generic mathematical model including environmental inhomogeneities in space, we show how two branches of vegetation patterns create a hysteresis loop when the effective mortality level changes. These two branches correspond to qualitatively distinct vegetation self-organized responses. In an increasing mortality scenario, one observes an equilibrium branch of high vegetation biomass forming self-organized patterns with a well-defined wavelength. However, reversing the mortality trend, one observes a low biomass branch lacking a wavelength. We call this phenomenon the clustering of vegetation patches. This behavior can be connected to historically significant trends of climate change in arid ecosystems.

Self-organization and pattern formation are ubiquitous processes in nature. We study the properties of migrating banded vegetation patterns in arid landscapes, usually presenting dislocation topological defects. Vegetation patterns with dislocations are investigated in three different ecosystems. We show through remote sensing data analysis and theoretical modeling that the number of dislocations N(x) decreases in space according to the law N ∼ log(x/B)/x, where x is the coordinate in the opposite direction to the water flow and B is a suitable constant. A sloped topography explains the origin of banded vegetation patterns with permanent dislocations. Theoretically, we considered well-established approaches to describe vegetation patterns. All the models support the law. This contrasts with the common belief that the dynamics of dislocations are transient. In addition, regimes with a constant distribution of defects in space are predicted. We analyze the different regimes depending on the aridity level and water flow speed. The reported decay law of defects can warn of imminent ecosystem collapse.

Encounters between individuals are fundamental for many ecological processes such as mate finding, predation, and disease transmission, among others. Computing encounter rates in these scenarios provides insight into how individual movement strategies lead to population-level consequences. Many previous studies, focused on tying individual movement behavior to encounters, suggest that directionally persistent movement (ballistic movement) strategies improve encounter rates. However, these models often ignore the effect of range residency of animals, where the individuals use space non-uniformly and occupy a home range that is considerably smaller than the population range. Here we show that when we consider the range resident behavior, the ballistic movement strategy does not always result in increased encounter as previously thought. Rather, we show that the effect of ballistic movement on encounter rates is influenced by the spatial distribution of the individual home ranges. We demonstrate these features by deriving exact analytical expressions for encounter rates under the Ornstein-Uhlenbeck movement with foraging (OUF), which is a movement model that allows directional persistence (correlations in velocity) along with range residency.

Large-scale vegetation patterns, with wavelengths up to hundreds of meters, have inspired scientists to understand their origin and their influence on ecosystems. One global observation is that banded patterns generally appear on sloped territories, where the environment imposes a clear break of symmetry, favoring stripes with well-defined directions. Most models predict a perfect stripe pattern as the asymptotic state. Including the break of symmetry in mathematical models and realistic boundary conditions enables the formation of banded structures characterized by showing dislocations throughout the pattern. The pattern as a whole acquires a group velocity, propagating as a nonlinear wave with singularities, which is permanently sustained by boundaries. This same bifurcation from perfect bands to bands with dislocations is observed in three different models of vegetation biomass spatiotemporal evolution proposed in the literature. Surprisingly, this new dynamical regime could leave an imprint in the spatial distribution of dislocations, which is observed in actual vegetation banded patterns from Chile, Sudan, and North America, where we analyzed the distribution of dislocations together with the topography of the territory to unveil a clear break of symmetry, in line with our theory. We explore how ecologically relevant parameters could mediate the transition between the different dynamical regimes. Our work proposes that the break of symmetry due to the environment and the boundary conditions could play a crucial role in understanding these complex systems.

Magnetic van der Waals materials, such as transition metal phosphorous chalcogenides MPS3 and MPS4 (M = Mn, Fe, Co, and Ni), offer potential for coupled spintronic and optoelectronic applications due to their wide band gap (1.2 - 3.5 eV) [1] and efficient light absorption. While both belong to the C2/m space group, they differ in magnetic ordering, with MPS3 preserving antiferromagnetic (AFM) ordering [1] and CrPS4 changing from AFM to ferromagnetic (FM) in the monolayer limit [2]. However, the mechanism and role of exchange interaction still need to be clarified, especially in the case of MPS4. Our methodology involved using VASP with PAW and PBE+D3, optB86-vdW functionals, and the SCAN functional. For the magnetic structure, we adopted the GGA+U approach with Dudarev formalism [3]. The exchange parameters for a Heisenberg Hamiltonian were then derived with the TB2J Python package [4] by downfolding the DFT bands in the vicinity of the Fermi energy employing Wannier functions. First, we studied CrPS4 and found an FM ground state with a magnetic moment of 3.0 µB/magnetic
atom, in agreement with the literature [5]. The exchange parameters of CrPS4 were analyzed in detail, providing insight into the competition between different exchange-interaction mechanisms.

In hyperarid environments, vegetation is highly fragmented, with plant populations exhibiting non‐random biphasic structures where regions of high biomass density are separated by bare soil.
In the Atacama Desert of northern Chile, rainfall is virtually nonexistent, but fog pushed in from the interior sustains patches of vegetation in a barren environment. Tillandsia landbeckii, a plant with
no functional roots, survives entirely on fog corridors as a water source. Their origin is attributed to interaction feedback among the ecosystem agents, which have different spatial scales, ultimately generating banded patterns as a self‐organising response to resource scarcity. The interaction feedback between the plants can be nonreciprocal due to the fact that the fog flows in a well‐
defined direction. Using remote sensing analysis and mathematical modelling, we characterise the orientation angle of banded vegetation patterns with respect to fog direction and topographic slope gradient. We show that banded vegetation patterns can be either oblique or horizontal to the fog flow rather than topography. The initial and boundary conditions determine the type of the pattern. The bifurcation diagram for both patterns is established. The theoretical predictions are in agreement with observations from remote sensing image analysis.

Magnetic van der Waals materials, such as transition metal phosphorus chalcogenides MPS3 and MPS4 (M = Mn, Fe, Co, Ni), offer potential for spintronic and optoelectronic applications
due to their wide band gaps (1.2 - 3.5 eV) [1] and efficient light absorption. Both belong to the C2/m space group but differ in magnetic ordering: MPS3 maintains antiferromagnetic (AFM)
ordering [1], while CrPS4 shifts from AFM to ferromagnetic (FM) in the monolayer limit [2].However, the mechanisms involving ligand field theory and exchange interactions are still
unclear, necessitating further research on the magnetic states in FePS4, CoPS4, MnPS4, and NiPS4, and their instability factors.
We studied the stability and electronic properties of the MPS4 family using DFT, focusing on magnetic properties. VASP with PAW, PBE+D3, optB86-vdW functionals, and the SCAN
functional were employed with the GGA+U approach with Dudarev formalism. Analysis was done using a Heisenberg model derived using TB2J [3] and bond analysis using LOBSTER [4].
First, we studied CrPS4 and found an FM ground state with a magnetic moment of 3.0 μB per magnetic atom, consistent with the literature [5]. Detailed analysis of CrPS4's exchange
parameters provided insight into the competition between exchange interaction mechanisms, explaining why it exhibits FM order in the monolayer. We also studied FePS4, CoPS4, MnPS4,
and NiPS4. The exchange parameters, combined with structural and COHP analysis, suggest these materials are unstable due to a structure favoring FM ordering. However, the electron distribution in these MPS4 compounds, except CrPS4, favors AFM coupling.
In conclusion, our study of CrPS4 confirmed the FM ground state and magnetic moment reported in previous literature. We now understand why CrPS4 exhibits FM behavior and
envision that this property can be influenced through targeted modifications. Additionally, we provide insights into the instability of other MPS4 compounds, which can guide experimentalists in modifying these materials to enhance their stability.

Current vs. Voltage data including the raw data

A direct nanowriting procedure using helium- and neon-focused ion beams and spin-coated organo-
metallic thin films is introduced and applied to the fabrication of Pd-enriched metallic structures in a
single lithography step. This process presents significant advantages over multi-step resist-based lithogra-
phy and focused beam-induced deposition using gaseous precursors, such as its simplicity and speed,
respectively. The optimized process leads to Pd-rich structures with low electrical resistivity values of 141
and 152 μΩ cm under Ne+ or He+ fluences of 1000 and 5000 μC cm−2, respectively. These resistivity
values correlate well with compositional and microstructural studies, indicating a high Pd metallic content
in a dense structure with a few-nm grain size. The obtained results are compared to similar structures fab-
ricated by direct electron and gallium beam nanowriting, demonstrating the full potential of nanopat-
terned Pd-based organometallic thin films under the most common focused charged beams. The practi-
cal applications of combining spin-coated organometallic thin films with focused beam nanowriting in
micro- and nano-lithography modern procedures are also discussed in this contribution.

The term “Helium-Ion Microscope (HIM)” is still unfamiliar to many people. HIM is a type of gas field ion source (GFIS) microscope based on the principle of the projection microscope proposed by E.W. Muller of the University of Pennsylvania in 1951. It utilizes a needle-shaped metal tip, sharpened to the atomic level, as the ion source filament. In 1975, W.H. Escovitz et al. proposed a microscope using hydrogen gas for GFIS, and in 1978, J. Orloff et al. developed the current GFIS. Around the same time, a liquid metal ion source (LMIS) was also developed, enabling more stable beam extraction than GFIS. However, as the research, development, and commercialization of Ga Focused Ion Beam (Ga FIB) microscopes using LMIS progressed, the advancements of GFIS were temporarily overshadowed. In 2006, more than a decade after the maturity of Ga FIB microscopy technology, HIM, which utilizes helium gas for GFIS, was commercialized. Since then, there has been steady progress in the research and development of HIM technology applications, as well as advancements in HIM equipment. These applications include surface imaging using secondary electrons emitted from the near-surface region of the sample irradiated by helium ions, which closely resembles observations made by secondary electron microscopy (SEM). Additionally, analysis techniques such as backscattering spectrometry are employed. Furthermore, HIM technology enables nano-level fabrication and modification of materials, leading to numerous new applications.

The combination of focused electron beam induced deposition (FEBID) and magnetic force microscopy (MFM) has opened up new possibilities in nanoscale magnetic imaging. FEBID offers precise control over the dimensions and magnetic properties of the MFM probes, enabling the development of high-performance magnetic tips with enhanced capabilities compared to conventional ones. These improved tips offer superior resolution, sensitivity, and versatility in nanoscale magnetic surface characterization. Here, we compare the performance of a commercial MFM tip and a FEBID-grown Fe tip in a Ni80Fe20/NdCo5 film. The FEBID tip exhibited superior lateral resolution for topography imaging, likely due to its sharper and well-defined geometry, with a tip diameter of approximately 20 nm. MFM measurements further confirmed this advantage, revealing better-defined magnetic domains and higher magnetic contrast with the FEBID-functionalized probes compared to the commercial tip. This improvement can be attributed to the possibility to optimize the tip-sample magnetic interaction for the FEBID tip. By reducing the lift height of the second pass, we were able to bring the tip closer to the sample, enhancing the magnetic signal without introducing significant topographic artifacts. Overall, these findings highlight the potential of FEBID for creating high-resolution and high-sensitivity MFM tips.

We present the ‘‘First Light Advanced Ignition Model" (FLAIM), a reduced model for the implosion, adiabatic
compression, volume ignition and thermonuclear burn of a spherical DT fuel capsule utilising a high-Z
metal pusher. FLAIM is characterised by a highly modular structure, which makes it an appropriate tool
for optimisations, sensitivity analyses and parameter scans. One of the key features of the code is the 1D
description of the hydrodynamic operator, which has a minor impact on the computational efficiency, but
allows us to gain a major advantage in terms of physical accuracy. We demonstrate that a more accurate
treatment of the hydrodynamics plays a primary role in closing most of the gap between a simple model and
a general 1D rad-hydro code, and that only a residual part of the discrepancy is attributable to the heat losses.
We present a detailed quantitative comparison between FLAIM and 1D rad-hydro simulations, showing good
agreement over a large parameter space in terms of temporal profiles of key physical quantities, ignition maps
and typical burn metrics.

Historical tailings storage facilities (TSFs) are being revisited everywhere in the World for their potential in commodities of recent interest, such as Indium, Lithium or REEs, as well as to mitigate their environmental risks. This interest has sparked the development of methods to quantify their value. In this contribution we present one such method for estimating both the grade and recoverability of target commodities, i.e. not just how much of the component is present in the tailings and where, but also how much is expected to be recovered with a specified minerals processing route. The method exploits (i) particulate data from automated mineralogy systems (such as e.g. mineral liberation analysis, MLA) covering the TSF of interest, plus (ii) MLA analyses of the results of beneficiation tests on a handful of samples. A machine learning method (lasso regularised multinomial logistic regression) is trained on this second data set (ii) for predicting the chances of any particle to be recovered into the concentrate product as a function of its properties as measured by the MLA. This allows to calculate the expected proportion of mass of each component (both commodities and waste components) reporting to each output stream, not only for each MLA sample of the training set (ii) but also of the samples (i) from the TSF. These can then be interpolated with a geostatistical analysis. We applied this framework to a TSF in the Ore Mountains, near Freiberg (Saxony, Germany). We applied an n-fold validation strategy, showing significant agreement between predictions and actually observed behaviour. This supports our claim that the proposed method has a strong predictive power.

Multipoint simulation (MPS) algorithms exploit the dependence structure of the target variable at a series of k-nearest points around each simulation location. Most of the algorithms require the usage of a training image (TI) to either estimate and draw realisations from the conditional distribution of the target variable at an unsampled location, or else directly draw from the TI at the earliest occurrence of a sufficiently similar pattern as the conditioning one. The innovation from the TI (i.e. the ability to produce patterns not strictly found in it) happens because of a certain tolerance embedded into these algorithms. We present an MPS that can be trained on extensive conditioning data as well as on a TI. The method has three steps. In a first step, the training data is so to say "folded"" in a pre-specified series of ways to produce long lists of patterns containing (k+1)-tuples of nearest and near observations to each sample location: not just tuples of the target variable are created, but also information about the constellation of the corresponding (k+1) locations of these tuples is added to the patterns. In a second step, the folded dataset is fed into the training of an artificial neural network (ANN) to predict the target variable at the reference point conditional on the surrounding k-point pattern. Once the ANN is trained, in the third step we follow a random path through the simulation grid, each time finding the k-nearest data points and using the trained ANN to predict the conditional target value at each grid node. In this contribution, we discuss the details of the proposed algorith with an illustration example and discuss its properties and applicability.

Particle or grain size distributions often play an important role in understanding processes in geosciences. Functional data analysis allows applying multivariate methods like principal component analysis directly to such distributions. These are however often observed in the form of samples, and thus with a sampling error. This additional sampling error changes the properties of the multivariate variance and thus the number of relevant principal components and their direction. The result of the principal component analysis becomes an artefact of the sampling error and can negatively affect the following data analysis. This work presents a way of estimating this sampling error and how to confront it in the context of principal component analysis. The effect of the sampling error and the effectiveness of the correction is demonstrated with a series of simulations. It is shown how the interpretability and reproducibility of the principal components improve and become independent of the selection of the basis. The proposed method is then applied on a dataset of grain size distributions in a geometallurgical dataset from Thaba mine in the Bushveld complex.

Several definitions of entropy have been used in literature to assess the efficiency of processes in the raw material industry. These definitions are based on tracking substance- or material concentrations within anthropogenic systems such as processing plants or analyzing partition values for characterizing separation processes. This work presents a common framework for entropy analysis for particulate systems, combining these existing definitions and, for the first time, taking the disperse state of particles, described by size and intergrowth, into account. Consequently, the same characteristic measure can evaluate both comminution and separation processes, allowing for combined optimization.

Electronic structure simulations allow researchers to compute fundamental properties of materials without the need for experimentation. As such, they routinely aid in propelling scientific advancements across materials science and chemical applications. Over the past decades, density functional theory (DFT) has emerged as the most popular technique for electronic structure simulations, due to its excellent balance between accuracy and computational cost. Yet, pressing societal and technological questions demand solutions for problems of ever-increasing complexity. Even the most efficient DFT implementations are no longer capable of providing answers in an adequate amount of time and with available computational resources. Thus, there is a growing interest in machine learning (ML) based approaches within the electronic structure community, aimed at providing models that replicate the predictive power of DFT at negligible cost. Within this work it will be shown that such ML-DFT approaches, up until now, do not succeed in fully encapsulating the level of electronic structure predictions DFT provides. Based on this assessment, a novel approach to ML-DFT models is presented within this thesis. An exhaustive framework for training ML-DFT models based on a local representation of the electronic structure is developed, including minute treatment of technical issues such as data generation techniques and hyperparameter optimization strategies. Models found via this framework recover the wide array of predictive capabilities of DFT simulations at drastically reduced cost, while retaining DFT levels of accuracy. It is further demonstrated how such models can be used across differently sized atomic systems, phase boundaries and temperature ranges, underlining the general usefulness of this approach.

Surgical resection of tumours is a balance between sparing healthy and completely removing cancerous tissue. Fluorescently labelled cancer-specific ligands, such as Fibroblast activation protein (FAP), could aid the surgeon in differentiating healthy from cancerous tissue during surgery. When these compounds can also be radiolabelled, bimodal ligands are the result. These can then also be used for an initial diagnosis, e.g. via molecular imaging using Positron Emission Tomography. Combining both approaches allows for a better alignment of diagnostic and surgical outcomes and ultimately improve the patient’s quality of life.
Development of such bimodal ligands requires careful assessment of binding kinetics. Real-time ligand binding using the LigandTracer® platform, allows to assess binding kinetics either via the radioactive or the fluorescent signal. Together with the industry partner, Ridgeview Instruments AB, we investigated the binding kinetics (association and dissociation) of new bimodal FAP ligands (IRDye800CW and 68Ga via NODA-GA ) in a FAP-expressing cell model. Binding was measured using fluorescence with a new near-infrared detector for LigandTracer Green. This was then simultaneously compared to radioactive detection using LigandTracer Grey/Yellow.
During the first association phase, binding curves from fluorescent and radioactive detection were very
similar. As more timed passed, the fluorescence signal decayed with more than 10% per hour, while the radioactive signal remained stable. This difference might be attributed to internalization and/or degradation of the fluorophore, whereas the radioactive signal is unaffected by such processes. Nevertheless, fitted kinetic parameters still showed a suitable agreement, indicating that both approaches can be utilized for the testing of such bimodal ligands.

A new class of ligands, N,N’-dialkyl-2,6-pyridinediamide (DRPDA), has been designed with the specific intention of exhibiting interchangeable diversity in coordination modes, including organometallic interactions, for the purpose of solvent extraction of elements relevant to the proper treatment of high-level radioactive liquid waste (HLLW) generated after nuclear fuel reprocessing. Consequently, DRPDA has been observed to extract Pd(II) and Zr(IV) from HNO3(aq) to 1-octanol in nearly quantitative yields when the selected ligand is sufficiently hydrophobic. However, concomitance of some of other HLLW components were also found. The extraction selectivity towards Pd(II) and Zr(IV) was markedly enhanced by employing ndodecane instead of 1-octanol as evidenced by good distribution ratios (DM) of Pd(II) (DPd = 72.5) and Zr(IV) (DZr = 12.9), which is several orders of magnitude greater than DM’s of other HLLW components (10−3-10−2), where addition of 20 vol% 1-octanol is still required to accelerate the extraction kinetics. Despite direct contact with the highly acidic aqueous phase, deprotonation from one of the amide NH moieties of DRPDA proceeds to form [Pd(DRPDA−)(NO3)] as a good extractables in the current biphasic system. This Pd(II) complex with a rather unique asymmetric N−^N^O tridentate coordination was characterized by SCXRD, elemental analysis and 1H NMR, and theoretically corroborated by DFT calculations and NBO analysis. In contrast, DRPDA also interacts with Zr4+ in different tridentate O^N^O mode without any deprotonation. Based on mechanistic differences in the extraction chemistry we clarified, Pd(II) and Zr(IV) co-extracted to the organic phase were recovered stepwise by using appropriate stripping agents such as 1.0 M HCl(aq) and 0.10 M HNO3(aq), respectively.

Research into Warm Dense Matter (WDM) has recently become more important with
advances in inertial confinement fusion and astrophysics. The complex nature of matter under
these conditions remains however, making it extremely difficult to describe theoretically, due
to the interplay between quantum degeneracy and Coulomb interactions, and the transition
of condensed and plasma phases. Several methods exist to describe matter at these
conditions, with recent extensions to Path Integral Monte Carlo (PIMC) allowing the
calculation of the Laplace of the dynamic structure factors. This allows quasi-exact calculations
for warm dense hydrogen, but does not give access to other important physical quantities
describing a plasma state, like the ionisation and ionisation potential depression (IPD). Since
both are difficult to measure experimentally, we instead compare the imaginary time
correlation function (ITCF) from PIMC simulations with synthetic X-Ray Thomson Scattering
(XRTS) spectra to obtain a best estimate for the ionisation state. The IPD is then directly
calculated using the Saha equation and compared against other commonly used models. We
expect this work to be relevant for future inertial confinement energy developments,
particularly in validating equation of state models.

Research into Warm Dense Matter (WDM) has become more important with recent advances in inertial confinement fusion and astrophysics. The interplay between quantum degeneracy and Coulomb interactions, and the transition of condensed and plasma phases occurring under these conditions, however, make WDM extremely difficult to describe theoretically. Several methods exist to describe matter at these conditions, with recent extensions to Path Integral Monte Carlo (PIMC) allowing the calculation of the Laplace transform of the dynamic structure factor, i.e. the imaginary time correlation function (ITCF), of warm dense hydrogen [1]. While PIMC is quasi-exact, it does not give access to other important physical quantities describing a plasma state, like the ionisation and ionisation potential depression (IPD). Moreover, both are difficult to measure experimentally. To remedy this, we instead compare the ITCF from PIMC simulations with synthetic X-Ray Thomson Scattering spectra [2], computed from a Chihara decomposition [3], to obtain a best estimate for the ionisation state. The IPD is then directly calculated using the Saha equation and compared against other commonly used models. We expect this work to be relevant for future inertial confinement energy developments, particularly in validating equation of state models, and for the refinement of astrophysical models.

[1] T. Dornheim et.al., arXiv preprint arXiv:2403.08570 (2024)

[2] T. Dornheim et.al., Phys. Plasmas 30, 042707 (2023)

[3] G. Gregori et.al., Phys. Rev. E 67, 026412 (2003)

Warm dense matter (WDM) is now routinely created and probed in laboratories around the world, providing unprecedented insights into conditions achieved in stellar atmospheres, planetary interiors, and inertial confinement fusion experiments. However, the interpretation of these experiments is often filtered through models with systematic errors that are difficult to quantify. Due to the simultaneous presence of quantum degeneracy and thermal excitation, processes in which free electrons are de-excited into thermally unoccupied bound states transferring momentum and energy to a scattered X-ray photon become viable. Here we show that such free-bound transitions are a particular feature of WDM and vanish in the limits of cold and hot temperatures. The inclusion of these processes into the analysis of recent X-ray Thomson Scattering experiments on WDM at the National Ignition Facility and the Linac Coherent Light Source significantly improves model fits, indicating that free-bound transitions have been observed without previously being identified. This interpretation is corroborated by agreement with a recently developed model-free thermometry technique and presents an important step for precisely characterizing and understanding the complex WDM state of matter.

*This work was partly funded by the Center for Advanced Systems Understanding (CASUS) which is financed by Germany's Federal Ministry of Education and Research (BMBF) and by the Saxon Ministry for Science, Culture and Tourism (SMWK) with tax funds on the basis of the budget approved by the Saxon State Parliament.Sandia National Laboratories is a multimission laboratory managed and operated by National Technology and Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy's National Nuclear Security Administration under Contract No. DE-NA0003525.The work of Ti.~D., M.~J.~M, and F.R.G.~was performed under the auspices of the U.S. Department of Energy by Lawrence Livermore National Laboratory under Contract No. DE-AC52-07NA27344.

Matter under extreme densities, temperatures and pressures is ubiquitous throughout our universe
and naturally occurs in a variety of astrophysical objects, including giant planet interiors (e.g.
Jupiter, but also exoplanets), brown dwarfs, white dwarf atmospheres, in the outer layer of neutron
stars and during meteor impacts. On Earth, such extreme states are important for technological
applications such as the discovery and synthesis of novel materials. A particularly important
application is given by inertial fusion energy (IFE), where both the fuel capsule and the ablator
material have to traverse this warm dense matter regime in a controlled way to reach ignition.
Indeed, the recent spectacular news from the National Ignition Facility (NIF) at the Lawrence
Livermore National Laboratory in California, USA, who have reported a net energy gain of the
burning plasma with respect to the compression energy [1], opens up the intriguing possibility to
develop IFE into a clean, safe and nigh abundant source of energy in the future.
In the laboratory, warm dense matter is created in large research facilities such as the European
XFEL in Germany, SACLA in Japan, and the NIF, SLAC, and the OMEGA laser in the USA using a
variety of techniques. Here, a key challenge is given by the accurate diagnostics of the created
samples due to the extreme conditions and the ultrafast time scales. Over the last years, the X-ray
Thomson scattering (XRTS) technique---also known as inelastic X-ray scattering---has emerged as
a promising method of diagnostics as it is, in principle, capable of giving microscopic insights into
the probed sample in the form of the electronic dynamic structure factor [2]. In practice, however,
the interpretation of XRTS measurements has relied on theoretical models that are based on a
number of de-facto uncontrolled assumptions. Consequently, the quality of the thus inferred system
parameters has remained unclear.
Here, I present an overview of a new approach that allows for the model-free interpretation of
XRTS spectra in the imaginary-time domain [3-5]. The latter naturally emerges in Feynman’s
celebrated path integral formulation of statistical mechanics and, by definition, contains the same
information as the usual spectral representation, only in an a-priori unfamiliar representation. At the
same time, working in the imaginary-time allows one to deconvolve the physical information from
effects due to the X-ray source and the detector. This, in turn, opens up the way for the model-free
extraction of important system parameters such as the temperature [3] without the need for any
approximations or simulations.

[1] The Indirect Drive ICF Collaboration, Achievement of Target Gain Larger than Unity in an
Inertial Fusion Experiment, Phys. Rev. Lett. 132, 065102 (2024)
[2] S. H. Glenzer and R. Redmer, X-ray Thomson scattering in high energy density plasmas, Rev.
Mod. Phys. 81, 1625 (2009)
[3] T. Dornheim et al., Accurate temperature diagnostics for matter under extreme conditions,
Nature Commun. 13, 7911 (2022)
[4] T. Dornheim et al., Physical insights from imaginary-time correlation functions, Matt. Radiat.
Extremes 8, 056601 (2023)
[5] T. Dornheim et al., X-ray Thomson scattering absolute intensity from the f-sum rule in the
imaginary-time domain, Sci. Reports 14, 14377 (2024)

Understanding the properties of warm dense hydrogen [1] is of paramount importance for the modeling of astrophysical objects (giant planets, brown dwarfs, etc) and for the development of technological applications such as inertial fusion energy. Yet, the simultaneous presence of Coulomb correlations, partial ionization, quantum degeneracy and strong thermal excitations renders its accurate theoretical description challenging: a holistic approach that takes into account all of these effects without uncontrolled approximations is needed.

Here, I present new ab initio path integral Monte Carlo (PIMC) simulations of warm dense hydrogen [2,3], which have been obtained without the usual fixed-node approximation. While being computationally costly, these simulations give us access to a host of observables, most notably the linear density response and the related local field factors [3]. Finally, I discuss the direct connection between our simulations and upcoming x-ray Thomson scattering (XRTS) experiments with hydrogen, and the potential utility of the static density response function as a physical observable to quantify electronic localization around the ions.

[1] M. Bonitz et al., arXiv:2405.10627

[2] T. Dornheim et al., Journal of Chemical Physics 160, 164111 (2024)

[3] T. Dornheim et al., arXiv:2403.08570

*This work has received funding from the European Union's Just Transition Fund (JTF) within the project "Roentgenlaser-Optimierung der Laserfusion" (ROLF), contract number 5086999001, co-financed by the Saxon state government out of the State budget approved by the Saxon State Parliament.This work has received funding from the European Research Council (ERC) under the European Union’s Horizon 2022 research and innovation programme(Grant agreement No. 101076233, "PREXTREME").Views and opinions expressed are however those of the authors only and do not necessarily reflect those of the European Union or the European Research Council Executive Agency. Neither the European Union nor the granting authority can be held responsible for them

The synthesis and characterization of WYLID, a side product from the original YLID synthesis, was presented. Quantum crystallographical insights into the bonding situation in WYLID were provided based on Hirshfeld-Atom-Refinement (HAR), multipolar modeling (MM), and X-ray restrained wavefunction (XRW) fitting. We compared these results to theoretical calculations on a gas-phase optimized DFT calculation and a Hartee-Fock calculation based on the HAR geometry. In our investigations, we found that the S-C bond in WYLID is best described as an ylid type bond. The -SMe2 fragment showed no influence on the nearest C-O carbonyl/carbonylate equilibrium, which is an ongoing debate in the quantum crystallographic community for YLID.

The HZDR team has harnessed the power of Python, Flask, Dash, ZeroMQ and Kafka in tandem with MongoDB, to create a suite of web-based applications that simplify the extraction of laser shot data and metadata from various distinct, heterogeneous, semi-automated data acquisition systems.

The Shotsheet apps play a central role in manual logging, especially in a facility with highly flexible but manual operation modes. These apps also connect to other data sources like the Mediawiki ELN system. To enable further automation, we’ve developed the Experimental Shot Counter and enrichment app (escape), which handles incoming ZeroMQ messages from the Draco Laser system (experiment driver) and provides tailored ZeroMQ and Kafka messages within the Lab intranet. These messages can automate the readout and processing of measurements, as well as trigger mechanical actions.

In the subsequent 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 the HZDR data management ecosystem , we delve into the intricacies of data fusion, exploring innovative approaches to seamlessly harmonize metadata catalogs, data publications, and archives.

Nanoscale magnetic patterning can lead to the formation of a variety of spin textures, depending on the intrinsic properties of the material and the microstructure. Here we report on the spin textures formed in laterally patterned antiferromagnetic (AF)/ferromagnetic (FM) thin film stripes with a period of 200 nm (100 nm FM/100 nm AF). We make use of the AF to FM phase transition in FeRh thin films at ~100 °C, thereby creating a nanoscale pattern that is thermally switchable between AF/FM stripes and uniformly FM. A combination of spin-resolved photoemission electron microscopy, magnetic force microscopy, and magnetometry measurements allow direct nanoscale observations of the stray magnetic fields emergent from the nanopattern as well as the underlying magnetization. Our measurements reveal pinning centres resistant to temperature cycling that govern the modulated spin-texture as well as a sub-texture consisting of grain-driven nanoscale magnetization structure directed out of the film plane. The nanoscale magnetic structure is thus strongly influenced by the film microstructure. Signatures of exchange bias are not observed, most likely due to the small contact area between the AF and FM regions. These results show that temperature controllable spin textures can be created in FeRh thin films which could find application in domain wall, microwave, or magnonic devices.

Abstract: The 239Pu(n,γ) reaction cross section is very important for operation of both thermal and fast reactors, when loaded with MOX fuels. According to the NEA/OECD High Priority Request List the precision of cross section data for this reaction should be improved. The cross section of (n,f) reaction is much higher compared to (n,γ) for this isotope. In such conditions the fission tagging technique could be applied to identify the fission background. In the past, this technique was successfully used for capture measurements at the n_TOF facility at CERN. The multi-section fission ionization chamber was constructed and used in the combination with Total Absorption Calorimeter (TAC) for detecting gamma rays for the precise measurement of 239Pu(n,γ) reaction cross section at the n_TOF facility.

The coordinate transformation is a mathematical procedure in numerical analysis for solving physical problems in deformed geometries, while using a numerical solver originally derived for regular geometries. This paper presents a method based on coordinate transformation to simulate non-uniform deformation scenarios in a nuclear reactor core and its effect on the reactor physics behavior.
The method was developed for the 3D reactor core simulator DYN3D, although it is equally applicable to any other reactor physics code based on a nodal diffusion solver. The method was tested in four stages using sodium-cooled fast reactor cores: (1) to demonstrate the proof of concept and test code implementation on a simplified core; (2) to verify the feasibility to model lifelike flowering scenarios on a realistic SFR core; (3) to evaluate performance by simulating the core flowering experiment performed in the Phénix reactor; and (4) to assess applicability to dynamic core deformation scenarios such as those occurring during pressure wave propagation.

Online-workshop with focus on overviews. On the one hand, present national research topics are addressed. On the other hand, the diversity of specific aspects is covered by a number of dedicated, short technical presentations that span the evolution of the bentonite from mining to the far future of the barrier.

Detailed knowledge of vegetation patterns allows to evaluate mire ecosystems and their dynamics. The use of hyperspectral information has the benefits of exploring spectral characteristics of species and vegetation modelling. Our study employed multi-scale and multi-source hyperspectral imaging with a handheld camera in the field and an UAV (Unoccupied Aerial Vehicle) sensor covering the wavelengths of 400 – 1000 nm. Plot-level spectra acquired with a UAV and field spectra collected at 1 m height were combined to develop a spectral library for Sphagnum moss species. This library was then used to map dominant Sphagnum species in a Finnish Aapa mire complex using the Spectral Angle Mapper (SAM) classifier. Classification performance assessment was supported by calculating a water index from the UAV-information. Additionally, we examined the transferability of site-specific spectral libraries to an aapa mire with similar vegetation. The results showed little spectral variation in the plot spectrum between the sensors. A fusion of species- and plot-level libraries yielded the highest accuracy of 62 %. For both mires, there was a great variation among the class accuracies. Floating mosses had an accuracy of 86 %, followed by lawn-forming Sphagnum balticum with 77 %. For the test site, the latter species was mapped with an accuracy of 59 %. Red moss species achieved low accuracies of 45 % and 38 %, likely due to effects from sub-pixel and mixed-pixel effects of neighbouring graminoid species and the presence of litter. This might have also enhanced the contrast of adjacent pixels contributing to spectral alterations. Water table depth measurements and the water index revealed a hydrological preference for most species, with classification performance notably improving with higher water index values. We recommend collecting on-site hyperspectral information at varying hydrological circumstances to build a comprehensive spectral library for mire vegetation and modelling.

We consider a ring of fermionic quantum sites, modeled by the Fermi-Hubbard Hamiltonian, in which electrons can move and interact strongly via the Coulomb repulsion. The system is coupled to fermionic cold baths, which by the exchange of particles and energy induce relaxation in the system. We eliminate the
environment and describe the system effectively by Lindblad master equations in various versions valid for different coupling parameter regimes. The early relaxation phase proceeds in a universal way, irrespective of the relative couplings and approximations. The system settles down to its low-energy sector and is consecutively well approximated by the Heisenberg model. We compare different Lindblad approaches, which, in the late relaxation, push the system towards different final states with opposite, extreme spin orders, from ferromagenetic to antiferromagnetic. Due to spin frustration in the trimer (a three site ring), degenerate ground states are formed by spin waves (magnons). The system described by the global coherent version of the Lindblad operators relaxes
towards the final states carrying directed persistent spin currents. We numerically confirm these predictions.

The Julia programming language was designed for scientific computing and with its claimed usability („walks like Python“) and speed („runs like C“), it seems to be a scientists‘ software dream come true. Julia appears to be particularly well-suited for high-energy physics (HEP), where reliable software tools and rapid development cycles are crucial for everyday work. Whether it’s data processing, or the simulation of the whole experiment, or the final data analysis and interactive visualization, the Julia ecosystem — with over ten thousand packages — might be a modern and high-performance software solution and the right set of tools to easily build any missing pieces.
In this talk, we will discuss, if the Julia programming language meets these requirements and can withstand testing on the workbenches of HEP. Additionally, we give an overview of current contributions in Julia to the HEP-related software stack and its potential trajectory. Moreover, we explore how the software development process itself can benefit from Julia, as it strikes an ideal balance between high-performance technology and student-friendly training — an especially valuable combination for the rapidly moving high-energy physics community.

To be successor, every larger software project needs to be tested to verify the correct functionality and to enable its functionality to be extended flawlessly. The type of tests can be very different and depends on the kind of software project. Software projects, that are divided into several sub-projects require integration tests to verify that the individual parts work together correctly.
At JuliaHEP 2023, I gave the talk “Unit and Integration testing in modularized julia package eco-systems” and talked about the problems that need to be solved when developing integration tests for a Julia package ecosystem. With the feedback from the talk, I developed IntegrationTests.jl [1], a framework to dynamically generate GitHub Action or GitLab CI integration jobs for a given Julia Project.toml. The talk explains the different problems to solve when adding integration tests in a Julia project and how IntegrationTests.jl solves them.

[1] https://github.com/QEDjl-project/IntegrationTests.jl

Platinum chalcogenides have received great attention among layered materials due to their peculiar physical properties. The strong layer-dependent electronic properties cause a band gap opening in monolayer PtTe₂, while the system is (semi)metallic otherwise. Here we show that starting with PtTe₂ films, other compositions such as Pt₃Te₄ and P₂Te₂ can be obtained by a post-growth desorption of tellurium or vapor-deposited Pt atoms. The experiments combined with DFT calculations provide insights into these transformation mechanisms and the stabilization of the new phases. The partially converted monolayer flakes exhibit PtTe₂-Pt₂Te₂ heterojunctions, which enable the formation of the in-plane semiconductor-metal interface. We further studied the electronic structure of edges and point defects in PtSe₂ monolayer where metallic 1D states with spin-polarized bands were found. In addition to stoichiometry, combining different Pt-chalcogenides in vertical heterostructures provides an additional degree of engineering of materials properties. Our results showed the variation of the interlayer interaction within the moire structure locally modulates the electronic structure of PtSe₂/PtTe₂ heterostructures.

Calculating differential cross-sections of scattering processes is a crucial observable in high-energy physics, used to predict experimental outcomes and test theoretical models. For perturbative quantum field theories, this involves generating all possible Feynman diagrams for a given scattering process and translating them into computable functions. This becomes cumbersome very rapidly, especially for high-multiplicity processes. In this talk, we introduce a method implemented in Julia for generating these functions for arbitrary scattering processes in perturbative QED, utilizing the ComputableDAGs.jl library. Our approach incorporates novel results and reuse optimizations, which could be extended to other theories or even the entire Standard Model and beyond.

While the response of graphene to ion beams has been studied in detail, much less is known about the effects of ion irradiation on other two-dimensional (2D) materials such as MoS2, h-BN, and CrSBr. We have studied the effects of ion irradiation on free-standing and supported targets using molecular dynamics (MD) combined with density functional theory (DFT) calculations. We characterize the types and assess the abundance of point defects in our structures as a function of ion energy, mass, and incident angle. Our simulations, combined with experimental data, show that controlled production of defects by ion irradiation is an effective tool to tune the electrical properties of MoS2 or add new functionalities to h-BN, such as single-photon generation. In the case of CrSBr, a ferromagnetic phase transition occurs upon intentionally introducing defects via ion irradiation. Our results help to understand the fundamental physical mechanisms underlying ion irradiation of low-dimensional materials and finding optimum parameters for defect engineering of 2D
materials with optimized properties.

Ion beam irradiation has proven to be an efficient technique for introducing defects and impurities to tailor the properties of both bulk and nanomaterials. However, this requires a thorough microscopic understanding of how the target reacts to ion irradiation. The behavior of solids under the influence of energetic ions has been extensively studied over the last 50 years using various theoretical approaches. These methods can provide details on ion ranges, energy losses, as well as on the types, stabilities, and evolution of irradiation-induced defects. We give a brief introduction to the computational methods that are commonly used to simulate the effects of radiation on solids. We discuss the fundamental physics that underlies both binary collision approximation (BCA) and more advanced molecular dynamics (MD) simulation techniques. Finally, the main advantages and limitations of both simulation methods are discussed for studying ion irradiation damage in solids.

Ultrafast electron beam X-ray computed tomography (UFXCT) is a fast tomographic imaging technique used, e.g., for investigations of highly dynamic multiphase flows. In the last years, UFXCT was enhanced with the capability of real-time image acquisition and reconstruction. Using those capabilities, a new feedback-loop to a positioning unit was realized which allows for real-time repositioning of the imaging planes based on the images contents. By traversing the imaging planes vertically, an object moving up- and/or downwards in the imaging region can be tracked and visualized. Using a phantom object moving with predetermined trajectories, we evaluated the tracking latency, trackable object velocities and positioning accuracy. Further, a latency compensation approach is introduced that can be used to enhance tracking performance.

Alkaline hydrogen evolution reaction (HER) is highly desired due to its economic utility as well as its basic significance in the study of all electrocatalytic processes taking place on cathode electrodes. Herein, we report the nickel and cobalt-based bimetallic alloy nanoparticles embedded in nitrogen-doped carbon (NiₓCo₁₋ₓ@NC) starting from novel metal-organic complexes. Among the synthesized alloy nanoparticle catalysts, Ni₁Co₃@NC exhibits the best performance for HER, reaching a current density of 10 mA/cm² merely at an overpotential of 28 mV, outperforming state-of-the-art noble Pt-based, as well as non-noble metal-based catalysts. Remarkably, this catalyst displays a high turnover frequency (TOF) of 32.44 s⁻¹ and even long-term durability at higher current density (50 mA/cm²) up to 175 hours with negligible decay. A series of advanced characterizations reveal that Ni₁Co₃@NC undergoes minimal near-surface restructuring, majorly retaining its structure during longer operations. In order to comprehend the interaction between the inherent HER activity and the metal center, we conducted further experiments for several bimetallic alloy nanoparticles by alloying Co nanoparticles with Mn, Fe, and Zn. This work sheds important light on the structure-function link for bimetallic alloy nanoparticles made of non-noble metals that exhibit electrocatalytic HER activity in an alkaline medium.

Aim: The prostate-specific membrane antigen (PSMA) is overexpressed in prostate cancer at significantly higher levels compared to healthy tissue. Therefore, PSMA has emerged as very suitable target for molecular imaging as well as targeted radionuclide therapy of metastatic castration-resistant prostate cancer (mCRPC). In this study, we have investigated the in vivo behavior of two novel macropa-based PSMA inhibitors, namely [225Ac]Ac-mcp-D-PSMA and [225Ac]Ac-mcp-M-alb-PSMA modified with albumin binding moiety. The main motivation behind this project was to improve tumor uptake and thus therapeutic efficacy of those novel 225Ac-labeled PSMA inhibitors.
Materials and methods: We have performed in vivo studies involving long-term toxicity study in healthy mice with subsequent immunohistochemical examinations of kidneys and salivary glands. We have also done therapeutic efficacy study in LNCaP-tumor bearing animals employing three different doses (5/15/45 kBq/mouse). Kidneys, livers and tumors were examined using immunohistochemical staining methods to detect PSMA expression, DNA damage (γH2AX), proliferation status (Ki67) and necrosis (H&E).
Results: The toxicity study have not revealed any significant toxic effect in studied parameters. Insignificant DNA damage was observed in the kidney tissue compared to the untreated controls. The therapy study showed no significant effect of two lower doses (5 and 15 kBq/animal) onto tumor volume or survival. The dose of 45 kBq/mouse had significant impact to both mentioned parameters, whereas [225Ac]Ac-mcp-M-alb-PSMA performed better than other two 225Ac-labeled PSMA inhibitors.
Conclusion: In vivo experiments in healthy mice showed very low toxicity of tested PSMA inhibitors. Histological examination of the organs in therapy study confirmed substantial DNA damage in the tumor tissue of mice injected with both studied novel 225Ac-compounds, on the other hand the same parameter revealed only low DNA harm in the kidneys. The therapeutic efficacy of novel compounds was comparable to gold standard [225Ac]Ac-PSMA-617, in case of [225Ac]Ac-mcp-M-alb-PSMA seemed to be even higher.

Aim: The radium isotopes radium-223/-224 with their diagnostic gamma emitter barium-131 (SPECT) are ideal candidates for targeted alpha therapy. However, in order to use radium as + 2 metal ion in radioconjugates, it must be stably bound. The chelator macropa (mcp) has been found to form the most stable complexes so far, but they are not stable enough for in vivo applications.[1,2] Therefore, novel macrocyclic chelators based on macropa were developed with an additional application for lanthanum, actinium, and lead radionuclides.
Materials and methods: Starting from the diazamacrocycle K2.2, 4 new chelators were prepared in which the picolinic acid side arm was replaced by 3 regioiosomeric diazabenzenes with carboxylic acid moiety. All new tendentate chelators and nonradioactive metal complexes were synthesized and characterized by NMR spectroscopy. The stability of the complexes was determined using ITC and radiolabeling was performed with barium-131, lanthanum-133, actinium-225 and lead-212.
Results: The 4 pym chelators were obtained in yields ranging from 19 to 74% including deprotection. Compared to Ba-mcp, a higher stability was found for all Ba-pym complexes. For barium-131, quantitative radiolabeling of all pym chelators was possible down to c = 10 µM, and for actinium-225, lanthanum-133, and lead-212 down to c = 0.1 µM. In competition experiments with the new radiometal complexes using 50 mM EDTA, consistently higher complex stabilities were found in contrast to the respective mcp complexes (barium-131: > 99% intact complex down to 0.1 mM; actinium-225, lanthanum-133 and lead-212: > 99% intact complex down to 0.1 µM).
Conclusion: Four new pym chelators were synthesized, which show a higher stability than macropa due to their modification. They are therefore better suited for complexation with barium-131, as well as for actinium-225, lanthanum-133 and lead-212 and thus also have the potential to form more stable radium-223 complexes.

The cementitious properties of natural Mg-rich olivine when reacted with a phosphoric acid solution are investigated, as a function of acid concentration and liquid/solid mass ratio. The obtained cements are composed of residual olivine crystals and amorphous silica nanoparticles dispersed in a dense and compact newberyite (MgHPO4∙3H2O) matrix. The latter was mostly formed by packed micrometric tabular crystals, although evidence of the presence of a fraction of amorphous MgHPO4 was also found. Water content in the raw mix was observed to play a pivotal role on the reaction pathway, either promoting porosity or hindering the crystallization of the products. Up to 57 % of olivine reactivity, whose dissolution was promoted by the curing temperature (60 °C) and low pH, was achieved. All in all, these results indicate that the industrial mineral olivine may serve a viable source of Mg for the production of phosphate cements.

Complexes of N,N,N′,N′-tetramethyl diglycolamide (TMDGA), a hydrophilic diglycolamide (DGA) proposed as an aqueous phase holdback reagent, have been crystallizedfor the majority of the lanthanide series (excluding promethium), yttrium, and americium to deepen our structural understanding of trivalent metal ion (M³⁺) DGA coordination compounds in the presence of nitrate counter-anions. The presented collection of 16 complexes with accompanying single-crystal structures, taking formulas M(TMDGA)₃][M(NO₃)₆] (M = La, Ce, Pr, Nd, Sm, Am), [M(TMDGA)₃][M(NO₃)₅(H₂O)]₁₋ₓ[M(NO₃)₄(H₂O)₂]ₓ(NO₃)₁₊ₓ (M = Eu, Gd, Tb, Dy, Ho, Er, Tm, Yb), [M(TMDGA)₃]₂[M(NO₃)₄(H₂O)₂]₀.₇₅[M(NO₃)₅(H₂O)]₁.₂₅(NO₃)₂.₇₅·H₂O (M = Lu), and [M(TMDGA)₃][M(NO₃)₅(H₂O); whereas the remaining smaller lanthanides did not possess sufficiently large ionic radii to coordinate six bidentate nitrate anions, instead, one or two nitrate anions are situated in the outer sphere. The systematic progression of changes in the anionic environments of these complexes outlines the changing coordination habits afforded by the lanthanide contraction.

Technetium (Tc) is a radioelement very relevant in nuclear waste. Its isotope T-99 is a long-lived (t½ = 2.13×105 y) fission product of U-235 and Pu-239 and is generated in high yield (ca. 6%) [1]. Hence, its contribution to overall doses in nuclear waste is high and long lasting. [1].
The emission of Tc-99 in the environment is a matter of concern since it is related to cancer and other health conditions due to long exposures [2]. Therefore, remediation strategies to immobilize Tc need to be developed not only to offer a safe long-term nuclear waste storage, but also to promote the remediation of Tc-polluted areas.
Most Tc immobilization strategies are based on redox state changes. The high mobility of Tc(VII) (as TcO₄⁻) is overcome when reduced to Tc(IV) upon formation of insoluble species (e.g., TcO₂ or TcSₓ) or interaction with minerals through different mechanisms (e.g., incorporation or surface complexation) [3]. This reduction is mediated by reducing agents, such as Fe(II) minerals (e.g., pyrite (FeS₂) [4], or magnetite (Fe(III)₂Fe(II)O₄) [5]).
Accordingly, Tc migration should not be studied only in simple systems. Our aim is, therefore, to study the biogeochemical behavior of Tc upon interaction with: i) microorganisms, ii) metabolites, iii) Fe(II) minerals, and iv) Fe(II) minerals in presence of metabolites. Taking into account these features, we are trying to provide a more realistic scenario of how Tc can be immobilized under conditions that resemble environmental surroundings.
In this talk, I will give an overview of the recent research carried out in this frame in my research group [6]. This includes: i) a comparison of Tc immobilization by biogenic and synthetic vivianite, ii) structural information about Tc(IV) and Tc(III) carbonate complexes, and iii) the influence of metabolites on the removal of Tc by pyrite.

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

References.
[1] A.H. Meena, Y. Arai, Env. Chem Lett. 15 (2017) 241–263.
[2] EPA about Tc, (n.d.). https://www.epa.gov/radiation/radionuclide-basics-technetium-99.
[3] C.I. Pearce, et al. Sci. Total Environ. (2019) 136167.
[4] D.M. Rodríguez, et al. Environ. Sci. Technol. 54 (2020) 2678–2687.
[5] E. Yalçintas, et al. Dalt. Trans. 45 (2016) 17874–17885. doi:10.1039/C6DT02872A.
[6] TecRad group, (n.d.). https://www.hzdr.de/db/Cms?pOid=67099&pNid=1375&pLang=en.

We investigate the dynamics of convergent shock compression in solid cylindrical targets irradiated by an ultrafast relativistic laser pulse. Our particle-in-cell simulations and coupled hydrodynamic simulations reveal that the compression process is initiated by both magnetic pressure and surface ablation associated with a strong transient surface return current with density of the order of 1017 A/m2 and lifetime of 100 fs. The results show that the dominant compression mechanism is governed by the plasma β, i.e., the ratio of thermal pressure to magnetic pressure. For targets with small radius and low atomic number Z, the magnetic pressure is the dominant shock compression mechanism. According to a scaling law, as the target radius and Z increase, the surface ablation pressure becomes the main mechanism generating convergent shocks. Furthermore, an indirect experimental indication of shocked hydrogen compression is provided by optical shadowgraphy measurements of the evolution of the plasma expansion diameter. The results presented here provide a novel basis for the generation of extremely high pressures exceeding Gbar (100 TPa) to enable the investigation of high-pressure physics using femtosecond J-level laser pulses, offering an alternative to nanosecond kJ-laser pulse-driven and pulsed power Z-pinch compression methods.

Growing environmental concerns have driven the switch from lead-containing dielectric perovskite ceramics to lead-free alternatives such as silver niobate tantalate (Ag(Nb1-xTax)O3), where tantalum (Ta) substitution for niobium (Nb) enhances energy storage density. Thin film deposition presents a promising way for fabricating these materials for the use in capacitors. In this study, Ag(Nb1-xTax)O3 (0 ≤ x ≤ 0.5) thin films are synthesised via combinatorial reactive d.c. magnetron sputtering from metallic targets. The chemical and phase composition of the films are comprehensively analysed using scanning electron microscopy coupled with energy dispersive X-ray spectroscopy, elastic recoil detection analysis, Rutherford backscattering spectrometry, X-ray diffraction, Raman spectroscopy and X-ray photoelectron spectroscopy. The findings demonstrate that reactive d.c. magnetron sputtering is a feasible technique for producing complex perovskite oxide thin films with customised chemical composition and microstructure. By enhancing the understanding of the Ag(Nb1-xTax)O3 material system, this study aims to contribute to the development of environmentally benign high-performance dielectrics that could replace lead-based ceramics in energy-storage applications.

Background and purpose
Disregarding the increase of relative biological effectiveness (RBE) may raise the risk of acute and late adverse events after proton beam therapy (PBT). This study aims to explore the relationship between variable RBE (above 1.1)-induced normal tissue complication probabilities (NTCP) and patient-specific factors, identify patients at high risk of RBE-induced NTCP increase, and assess risk mitigation by incorporating RBE variability into treatment planning.
Materials and methods
We retrospectively analyzed 105 primary brain tumor patients treated with PBT (RBE=1.1). We calculated differences in estimated NTCP (ΔNTCP) using a variable RBE-weighted dose (DRBE, Wedenberg model) and a constant RBE-weighted dose (DRBE=1.1), across 16 NTCP models. These differences were correlated with patient-specific characteristics. Based on ΔNTCP, patients were classified as high risk (32%) or low risk (68%) for adverse events due to RBE-induced NTCP. This classification was compared with alternative classifications based on (a) relevant patient-specific characteristics, (b) DRBE=1.1, and (c) the difference between DRBE and DRBE=1.1 (ΔD), assessing the balanced accuracy. The potential to reduce RBE-induced NTCP through track-end and linear energy transfer (LET) optimization was evaluated in six example patients.
Results
Using a variable RBE instead of a constant one resulted in NTCP increases (up to 32 percentage points). Variable-RBE-induced NTCP increases were strongly negatively correlated with the distance between the clinical target volume (CTV) and the organ at risk (OAR) for most side-effects, and positively correlated with CTV volume for certain side-effects. High increases were associated with (a) specific patient factors, particularly the proximity of the CTV to OARs, (b) DRBE=1.1, and (c) ΔD, with a balanced accuracy of 0.88, 0.94, and 0.86, respectively. Optimization of track-ends and LET considerably reduced NTCP values, achieving a mean reduction of 31% for optimized OARs.
Conclusion
The risk of variable-RBE-induced NTCP strongly depends on patient-specific factors and the considered side-effect. A small distance between the tumor and OARs notably increases the risk. Integrating biologically-guided objectives into treatment planning can effectively mitigate the risk.

Determining the neutron activation in the single components is an important task in the
decommissioning process of NPPs. Therefore, neutron fluences are the most fundamental and important
parameter on which every decommissioning planning is based. The aim of this study is to estimate this
accurately using Monte Carlo simulations. A detailed 3D model of a PWR was developed, and the
neutron fluence was calculated and validated based on metal foil-activation measurements.

The paper presents the current status and recent applications of the Serpent/DYN3D/ATHLET code system to various Sodium-cooled Fast Reactor (SFR) designs. It emphasizes the system’s capability for coupled DYN3D and ATHLET transient simulations that account for all significant reactivity effects inherent to SFR, in particular those related to thermal expansion of core and primary system structural elements. Recent applications to transient analysis across SFRs of various sizes and power outputs demonstrates robustness of the implemented approaches and provides a solid validation basis for the developed methodology.

This study explores the bulk crystal growth, structural characterization, and physical property measurements of the cubic double perovskite Ba₂CoWO₆ (BCWO). In BCWO, Co²⁺ ions form a face-centred cubic lattice with non-distorted cobalt octahedra. The compound exhibits long-range antiferromagnetic order below T_N = 14 K. Magnetization data indicated a slight anisotropy along with a spin-flop transition at 10 kOe, a saturation field of 310 kOe and an ordered moment of 2.17 μ_B at T = 1.6 K. Heat capacity measurements indicate an effective j = 1/2 ground state configuration, resulting from the combined effects of the crystal electric field and spin-orbit interaction. Surface photovoltage analysis reveals two optical gaps in the UV–Visible region, suggesting potential applications in photocatalysis and photovoltaics. The magnetic and optical properties highlight the significant role of orbital contributions within BCWO, indicating various other potential applications.

The first-order transition line in the H-T phase diagram of itinerant electron metamagnets terminates at the critical end point—analogous to the critical point on the gas-liquid condensation line in the p-T phase diagram. To unravel the impact of critical magnetic fluctuations on the crystal lattice of a metamagnet at the critical end point, we performed an ultrasonic study of the itinerant electron metamagnet UTe₂ across varying temperatures and magnetic fields. At temperatures exceeding 9 K, a distinct V-shaped anomaly emerges, precisely centered at the critical field of the metamagnetic transition in the isothermal field dependence of elastic constants. This anomaly arises from lattice instability, triggered by critical magnetic fluctuations via strong magnetoelastic interactions. Remarkably, this effect is maximized precisely at the critical-end-point temperature. Comparative measurements of another itinerant metamagnet, UCoAl, reveal intriguing commonalities. Despite significant differences in the paramagnetic ground state, lattice symmetry, and the expected metamagnetic transition process between UTe₂ and UCoAl, both exhibit similar anomalies in elastic properties near the critical end point.

Magnetic refrigeration, which utilizes the magnetocaloric effect, can provide a viable alternative to the ubiquitous vapor compression or Joule-Thompson expansion methods of refrigeration. For applications such as hydrogen gas liquefaction, the development of magnetocaloric materials that perform well in moderate magnetic fields without using rare-earth elements is highly desirable. Here we present a thorough investigation of the structural and magnetocaloric properties of a novel layered organic-inorganic hybrid coordination polymer Co₄(OH)₆(SO₄)₂[enH₂] (enH₂ = ethylenediammonium). Heat capacity, magnetometry and direct adiabatic temperature change measurements using pulsed magnetic fields reveal a field-dependent ferromagnetic second-order phase transition at 10 K < T_C < 15 K. Near the hydrogen liquefaction temperature and in a magnetic field change of 1 T, a large maximum value of the magnetic entropy change, ΔS^Pk _M = − 6.31 J kg⁻¹ K⁻¹, and an adiabatic temperature change, ΔT_ad = 1.98K, areobserved. These values are exceptional for rare-earth-free materials and competitive with many rare-earth-containing alloys that have been proposed for magnetic cooling around the hydrogen liquefaction range.

The interface of common III-V semiconductors InAs and GaSb can be utilized to realize a two-dimensional (2D) topological insulator state. The 2D electronic gas at this interface can yield Hall quantization from coexisting electrons and holes. This anomaly is a determining factor in the fundamental origin of the topological state in InAs/GaSb. Here, the coexistence of electrons and holes in InAs/GaSb is tied to the chemical sharpness of the interface. Magnetotransport, in samples of Mn-doped InAs/GaSb cleaved from wafers grown at a spatially inhomogeneous substrate temperature, is studied. It is reported that the observation of quantum oscillations and a quantized Hall effect whose behavior, exhibiting coexisting electrons and holes, is tuned by this spatial nonuniformity. Through transmission electron microscopy measurements, it is additionally found that samples that host this co-existence exhibit a chemical intermixing between group III and group V atoms that extends over a larger thickness about the interface. The issue of intermixing at the interface is systematically overlooked in electronic transport studies of topological InAs/GaSb. These findings address this gap in knowledge and shed important light on the origin of the anomalous behavior of quantum oscillations seen in this 2D topological insulator.

Bimetallic nanostructures are promising candidates for the development of enzyme-mimics, yet the deciphering of the structural impact on their catalytic properties poses significant challenges. By leveraging the structural versatility of nanocrystal aerogels, this study reports a precise control of Au-Pt bimetallic structures in three representative structural configurations, including segregated, alloy, and core-shell structures. Benefiting from a synergistic effect, these bimetallic aerogels demonstrate improved peroxidase- and glucose oxidase-like catalytic performances compared to their monometallic counterparts, unleashing tremendous potential in catalyzing the glucose cascade reaction. Notably, the segregated Au-Pt aerogel shows optimal catalytic activity, which is 2.80 and 3.35 times higher than that of the alloy and core-shell variants, respectively. This enhanced activity is attributed to the high-density Au-Pt interface boundaries within the segregated structure, which foster greater substrate affinity and superior catalytic efficiency. This work not only sheds light on the structure-property relationship of bimetallic catalysts but also broadens the application scope of aerogels in biosensing and biological detections.

Polaritons, i.e., hybrid quasi-particles of light and matter resonances, have been extensively investigated due to their potential to enhance light–matter interactions. Although polaritonic applications thrive in the mid-infrared range, their extension to the terahertz (THz) range remains limited. Here, we present paratellurite (α-TeO2) nanowires, a versatile material acting as a platform for different types of phonon polaritons. Utilizing synchrotron infrared nanospectroscopy from 10 to 24 THz, we uncover the polaritonic properties of α-TeO2 nanowires, showcasing their dual functionality as both a Fabry–Pérot cavity and a waveguide for surface phonon polaritons. Furthermore, near-field measurements with a free-electron laser as a THz source reveal a localized optical contrast down to 5.5 THz, an indication of hyperbolic bands. Our findings complement the repertoire of polaritonic materials, with significant implications for advancing THz technologies.

External control of optical excitations is key for manipulating light–matter coupling and is highly desirable for photonic technologies. Excitons in monolayer semiconductors emerged as a unique nanoscale platform in this context, offering strong light–matter coupling, spin–valley locking and exceptional tunability. Crucially, they allow electrical switching of their optical response due to efficient interactions of excitonic emitters with free charge carriers, forming new quasiparticles known as trions and Fermi polarons. However, there are major limitations to how fast the light emission of these states can be tuned, restricting the majority of applications to an essentially static regime. Here we demonstrate switching of excitonic light
emitters in monolayer semiconductors on ultrafast picosecond time scales by applying short pulses in the terahertz spectral range following optical injection. The process is based on a rapid conversion of trions to excitons by absorption of terahertz photons inducing photo detachment. Monitoring time-resolved emission dynamics in optical-pump/terahertz-push
experiments, we achieve the required resonance conditions as well as demonstrate tunability of the process with delay time and terahertz pulse power. Our results introduce a versatile experimental tool for fundamental research of light-emitting excitations of composite Bose–Fermi mixtures and open up pathways towards technological developments of new types of nanophotonic device based on atomically thin materials.

Curvilinear magnetism is a framework, which helps understanding the impact of geometric curvature on complex magnetic responses of curved 1D wires and 2D shells [1-3]. This approach provides means to modify conventional or to launch novel functionalities by tailoring curvature and 3D shape of magnetic thin films and nanowires [3]. In this talk, we will address fundamentals of curvature-induced effects in magnetism and review the envisioned application scenarios. In particular, we will demonstrate that curvature allows tailoring fundamental anisotropic and chiral magnetic interactions and enables fundamentally new nonlocal chiral symmetry breaking effect [4]. The topology of the geometry of 3D shaped magnetic objects allows stabilizing multiple solitons within a confined nanoarchitecture [5]. Those are relevant for numerous research and technology fields ranging from non-conventional computing and spin-wave splitters for low-energy magnonics. The application potential of geometrically curved magnetic architectures is being explored as mechanically reshapeable magnetic field sensors for automotive applications, spin-wave filters, high-speed racetrack memory devices, magnetic soft robots [6] as well as on-skin interactive electronics relying on thin films [7-9] as well as printed magnetic composites [10,11] with appealing self-healing performance [12]. This opens perspectives for magnetoelectronics in smart wearables, interactive printed electronics and motivates further explorations towards the realization of eco-sustainable magnetic field sensing relying on biocompatible and biodegradable materials [13-15].

[1] P. Gentile et al., Electronic materials with nanoscale curved geometries. Nature Electronics (Review) 5, 551 (2022).
[2] P. Makushko et al., A tunable room-temperature nonlinear Hall effect in elemental bismuth thin films. Nature Electronics 7, 207 (2024).
[3] D. Makarov et al., New Dimension in Magnetism and Superconductivity: 3D and Curvilinear Nanoarchitectures. Advanced Materials (Review) 34, 2101758 (2022).
[4] O. M. Volkov et al., Chirality coupling in topological magnetic textures with multiple magnetochiral parameters. Nature Communications 14, 1491 (2023).
[5] O. Volkov et al., Three-dimensional magnetic nanotextures with high-order vorticity in soft magnetic wireframes. Nature Communications 15, 2193 (2024).
[6] M. Ha et al., Reconfigurable Magnetic Origami Actuators with On-Board Sensing for Guided Assembly. Advanced Materials 33, 2008751 (2021).
[7] G. S. Canon Bermudez et al., Magnetosensitive e-skins for interactive devices. Advanced Functional Materials (Review) 31, 2007788 (2021).
[8] J. Ge et al., A bimodal soft electronic skin for tactile and touchless interaction in real time. Nature Communications 10, 4405 (2019).
[9] G. S. Canon Bermudez et al., Electronic-skin compasses for geomagnetic field driven artificial magnetoception and interactive electronics. Nature Electronics 1, 589 (2018).
[10] M. Ha et al., Printable and Stretchable Giant Magnetoresistive Sensors for Highly Compliant and Skin-Conformal Electronics. Advanced Materials 33, 2005521 (2021).
[11] E. S. Oliveros Mata et al., Dispenser printed bismuth-based magnetic field sensors with non-saturating large magnetoresistance for touchless interactive surfaces. Advanced Materials Technologies 7, 2200227 (2022).
[12] R. Xu et al., Self-healable printed magnetic field sensors using alternating magnetic fields. Nature Communications 13, 6587 (2022).
[13] X. Wang et al., Printed magnetoresistive sensors for recyclable magnetoelectronics. J. Mater. Chem. A 12, 24906 (2024).
[14] E. S. Oliveros Mata et al., Magnetically aware actuating composites: Sensing features as inspiration for the next step in advanced magnetic soft robotics. Phys. Rev. Appl. (Review) 20, 060501 (2023).
[15] L. Guo et al., Printable magnetoresistive sensors: A crucial step toward unconventional magnetoelectronics. Chinese Journal of Structural Chemistry (Review) 100428 (2024).

Presentation at "International Workshop on Baryon and Lepton Number Violation", Karlsruhe (Germany), Ovtober 8-11, 2024

In this presentation, I will discuss our recent advancements in utilizing machine learning to significantly enhance the efficiency of electronic structure calculations [1]. Specifically, I will focus on our efforts to accelerate Kohn-Sham density functional theory calculations by incorporating deep neural networks within the Materials Learning Algorithms framework [2,3]. Our results demonstrate substantial gains in calculation speed for metals across their melting point. Additionally, our implementation of automated machine learning has resulted in significant savings in computational resources when identifying optimal neural network architectures, laying the foundation for large-scale investigations [4]. Furthermore, I will present our most recent breakthrough, which enables neural-network-driven electronic structure calculations for systems containing over 100,000 atoms [5]. This achievement opens up new avenues for studying complex materials systems that were previously computationally intractable.

[1] L. Fiedler, K. Shah, M. Bussmann, A. Cangi, Phys. Rev. Materials, 6, 040301 (2022)
[2] A. Cangi, J. A. Ellis, L. Fiedler, D. Kotik, N. A. Modine, V. Oles, G. A. Popoola, S. Rajamanickam, S. Schmerler, J. A. Stephens, A. P. Thompson, Phys. Rev. B 104, 035120 (2021).
[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. Hoffmann, P. Mohammed, G. Popoola, T. Yovell, V. Oles, J. Austin Ellis, S. Rajamanickam, A. Cangi, Mach. Learn.: Sci. Technol., 3, 045008 (2022)
[5] L. Fiedler, N. Modine, S. Schmerler, D. Vogel, G. Popoola, A. Thompson, S. Rajamanickam, A. Cangi, npj. Comput. Mater., 9, 115 (2023)

Unmanned Aerial Vehicles (UAVs), commonly known as drones, are omnipresent and have grown in popularity due to their wide potential use in many civilian sectors. Equipped with sophisticated sensors and communication devices, drones can potentially form a multi-UAV system, also called an autonomous swarm, in which UAVs work together with little or no operator control. According to the complexity of the mission and coverage area, swarm operations require important considerations regarding the intelligence and self-organization of the UAVs. Factors including the types of drones, the communication protocol and architecture, task planning, consensus control, and many other swarm mobility considerations must be investigated. While several papers highlight the use cases for UAV swarms, there is a lack of research that addresses in depth the challenges posed by deploying an intelligent UAV swarm. Against this backdrop, we propose a computation framework of a self-organized swarm for autonomous and collaborative missions. The proposed approach is based on the Leader–Followers paradigm, which involves the distribution of ROS nodes among follower UAVs, while leaders perform supervision. Additionally, we have integrated background services that autonomously manage the complexities relating to task coordination, control policy, and failure management. In comparison with several research efforts, the proposed multi-UAV system is more autonomous and resilient since it can recover swiftly from system failure. It is also reliable and has been deployed on real UAVs for outdoor survey missions. This validates the applicability of the theoretical underpinnings of the proposed swarming concept. Experimental tests carried out as part of an area coverage mission with 6 quadcopters (2 leaders and 4 followers) reveal that the proposed swarming concept is very promising and inspiring for aerial vehicle technology. Compared with the conventional planning approach, the results are highly satisfactory, highlighting a significant gain in terms of flight time, and enabling missions to be achieved rapidly while optimizing energy consumption. This gives the advantage of exploring large areas without having to make frequent downtime to recharge and/or charge the batteries. This manuscript has the potential to be extremely useful for future research into the application of unmanned swarms for autonomous missions.

In this manuscript we demonstrate the successful implementation of reconfigurable field-programmable gate array (FPGA) technology into a pulse-resolved data acquisition (DAQ) system to achieve a femtosecond temporal resolution in ultrafast pump-probe experiments in real-time at large scale facilities. As a proof of a concept, electro-optic sampling (EOS) of terahertz waveforms radiated by a superradiant emitter of a quasi-cw accelerator operating at 50 kHz repetition rate and probed by external laser system is performed. Options for up-scaling the developed technique to a MHz range repetition rates are discussed.