Publications Repository - Helmholtz-Zentrum Dresden-Rossendorf

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.

A novel Y-shaped membraneless flow-through electrolyzer is introduced to achieve ahomogeneous electrochemical reaction across the entire electrode in a cost-efficient cell de-sign with effective product separation. Numerical simulations of the electrolyte flow andelectrical current within the already known I- and T-shaped cells motivate the newly pro-posed Y-shape cell. Furthermore, a new design criterion is developed based on the balancebetween bubble removal and gas generation. As proof-of-concept experimental results us-ing the Y-shaped electrolyzer are presented, showing homogeneous gas distributions across the electrode and efficient product separation by the electrolyte flow.

The transition to renewable energies and electric vehicles has triggered an unprecedented demand for metals.
Sustainable development of these technologies relies on effectively managing the lifecycle of critical raw materials, including their responsible sourcing, efficient use, and recycling. Metal recycling from electronic waste
(e-waste) is of paramount importance owing to ore-exceeding amounts of critical elements and high toxicity of
heavy metals and organic pollutants in e-waste to the natural ecosystem and human body. Heterotrophic microbes secrete numerous metal-binding biomolecules such as organic acids, amino acids, cyanide, siderophores,
peptides, and biosurfactants which can be utilized for eco-friendly and profitable metal recycling. In this review
paper, we presented a critical review of heterotrophic organisms in biomining, and current barriers hampering
the industrial application of organic acid bioleaching and biocyanide leaching. We also discussed how these
challenges can be surmounted with simple methods (e.g., culture media optimization, separation of microbial
growth and metal extraction process) and state-of-the-art biological approaches (e.g., artificial microbial community, synthetic biology, metabolic engineering, advanced fermentation strategies, and biofilm engineering).
Lastly, we showcased emerging technologies (e.g., artificially synthesized peptides, siderophores, and biosurfactants) derived from heterotrophs with the potential for inexpensive, low-impact, selective and advanced
metal recovery from bioleaching solutions

This publication presents a study on the mineral chemistry and luminescence properties of quartz samples from pegmatites of the Tørdal region in Norway. A total of 12 samples were analyzed using Secondary Ion Mass Spectrometry (SIMS), Electron Paramagnetic Resonance Spectroscopy (EPR), and Cathodoluminescence (CL) to gain insights into their trace element concentration and distribution as well as their luminescence behavior. The samples are characterized by different Cl emissions at 450 nm, 500 nm 650 nm and an additional shoulder at 390 nm, which is only partially visible due to the absorption of the glass optics. Of these luminescence bands, the 500 nm band is the most dominant in most samples and it is characterized by an initial blue-green luminescence, which is not stable under electron irradiation. Moreover, it is characterized by a heterogeneous distribution within the samples. This luminescence can be mostly assigned to [AlO4/M+]0 defects, with charge compensation mostly achieved by Li+. Analyses by EPR spectroscopy prove the dominance of structurally bound Al, Li, and Ti ions in the investigated samples. Further analyses using SIMS mapping demonstrate that Na and K are mainly bound to micro fractures or inclusions, suggesting a limited role in the compensation of the luminescence centers. Additionally, the SIMS mappings show that some samples contain Al-rich clusters of 10 to 20 μm in diameter, whereas other trace elements are characterized by a homogeneous distribution. These clusters correspond to bright luminescence areas in size and shape and could potentially indicate H+ compensated [AlO4/M+]0 defects.

The GeoPT proficiency testing scheme (IAG 2020) managed by the International Association of Geoanalyst (IAG) has proven to be a valuable tool for geochemical laboratories performing routine analyses of silicate rocks and related materials. It has also been shown that this proficiency testing programme can be used as a certification protocol in accordance with ISO Guide 35:2017 (Potts, et al. 2019).The GeoPT programme focuses exclusively on geochemical compositional data. However, there is extensive evidence (Meisel, et al. 2022) that the mineralogical composition of geological materials can have a strong influence on the accuracy of the analytical data. This led to the proposal presented at GEOANALYSIS 2022 to establish a mineralogical proficiency testing scheme aligned with the GeoPT programme (Möckel).
Based on the generally positive and supportive feedback from the geoanalytical community, combined with many indications of methodological problems, we developed a proposal for a coordinated geochemical and mineralogical proficiency testing scheme.
While this scheme will be available as a regular GeoPT round to all GeoPT participants according to the GeoPT protocol, the exact same material will also be accessible to laboratories that determine the quantitative mineralogical phase inventory. This applies for both classical bulk methods and automated image analysis techniques, including scanning electron microscopes or µ-XRF devices, commonly known as "automated mineralogy."
The approach initially ensures that the same rock material is used in both parallel PT rounds. The fact that the different analysis methods require different sample preparation procedures and particle size distribution is taken into account by specific sample treatment, possibly at the expense of a correct correlation to the initial rock. Furthermore, we propose a reporting system for the mineralogical data, which allows an assessment comparable to the GeoPT protocol. It will be based on the defined set of minerals according to the classification in the “Rock-Forming Minerals” book series.

The importance of the immune system in regulating tumor growth by inducing immune cell-mediated cytotoxicity associated with patients’ outcomes has been highlighted in patients with cancer on treatment with different immunotherapeutics. However, tumors often escape immune surveillance, which is accomplished by different mechanisms. Recent studies demonstrated an essential role of small non-coding RNAs, such as microRNAs (miRNAs), in the post-transcriptional control of immune modulatory molecules. Multiple methods have been used to identify miRNAs targeting genes involved in escaping immune recognition including miRNAs targeting CTLA-4, PD-L1, HLA-G, components of the major histocompatibility class I antigen processing machinery (APM) as well as other immune response-relevant genes in tumors. Due to their function, these immune modulatory miRNAs can be used as (1) diagnostic and prognostic biomarkers allowing to discriminate between tumor stages and to predict the patients’ outcome as well as response and resistance to (immuno) therapies and as (2) therapeutic targets for the treatment of tumor patients. This review summarizes the role of miRNAs in tumor-mediated immune escape, discuss their potential as diagnostic, prognostic and predictive tools as well as their use as therapeutics including alternative application methods, such as chimeric antigen receptor T cells.

A highly efficient reconstruction method has been developed for the direct computation of Hamiltonian matrices in the atomic orbital basis from density functional theory calculations originally performed in the plane wave basis. This enables machine learning calculations of electronic structures on a large scale, which are otherwise not feasible with standard methods, and thus fills a methodological gap in terms of accessible length scales.

Ion acceleration through compact laser-plasma sources holds great potential for diverse applications, from medical treatments to fusion experiments. Achieving the required beam quality parameters demands a deep understanding and precise control of the laser-plasma interaction process. Our ongoing collaborative research at DRACO PW (HZDR) and J-KAREN-P (KPSI) laser systems focuses on exploring the promising regime of Relativistically Induced Transparency (RIT).
In previous studies [1], we observed high-performance proton beams (>60 MeV) in an expanded foil case, showcasing an optimum at the onset of target transparency. Subsequent experiments revealed even higher proton energies beyond 100 MeV [2], emphasizing the important role of the transparency onset time in optimizing beam parameters and enhancing process robustness. We employ a combination of particle and laser diagnostics to explore the correlation between transparency onset and acceleration performance.
This contribution highlights our recent investigations into spectral and spatial components of transmission and emission arising from the laser-plasma interaction. Building upon established methodologies [3,4], our approach involves spectral interferometry, using the unperturbed laser beam as a reference, and correlating findings with proton acceleration performance. Our results suggest a promising avenue for a focused analysis of spectral and spatial distribution, offering additional insights into the complexities of the laser-plasma interaction process. By emphasizing these aspects, we aim to deepen our understanding of factors influencing ion acceleration, contributing to the optimization of beam quality parameters.
[1] Dover, N.P. et al.: Light Sci. Appl. 12, 71 (2023).
[2] Ziegler, T. et al.: Nat. Phys. accepted (2024).
[3] Bagnoud, V. et al.: Phys. Rev. Lett. 118, 255003 (2017).
[4] Williamson, S.D.R. et al.: Phys. Rev. Appl. 14, 034018 (2020).

The 13C(α,n)16O reaction is the main neutron source of the s-process taking place in thermally pulsing AGB stars and it is one of the main candidate sources of neutrons for the i-process in the astrophysical sites proposed so far. Therefore, its rate is crucial to understand the production of the nuclei heavier than iron in the Universe. For the first time, the LUNA collaboration was able to measure the 13C(α,n)16O cross section at E(c.m.) = 0.23−0.3 MeV drastically reducing the uncertainty of the S(E)-factor in the astrophysically relevant energy range. In this paper, we provide details and critical thoughts about the LUNA measurement and compare them with the current understanding of the 13C(α,n)16O reaction in view of future prospect for higher energy measurements. The two very recent results (from the University of Notre Dame and the JUNA collaboration) published after the LUNA data represent an important step forward. There is, however, still room for a lot of improvement in the experimental study of the 13C(α,n)16O reaction, as emphasized in the present manuscript. We conclude that to provide significantly better constraints on the low-energy extrapolation, experimental data need to be provided over a wide energy range, which overlaps with the energy range of current measurements. Furthermore, future experiments need to focus on the proper target characterisation, the determination of neutron detection efficiency having more nuclear physics input, such as angular distribution of the 13C(α,n)16O reaction below Eα < 0.8 MeV and study of nuclear properties of monoenergetic neutron sources and/or via the study of sharp resonances of 13C(α,n)16O. Moreover, comprehensive, multichannel R-matrix analysis with a proper estimate of uncertainty budget of experimental data are still required.

In this manuscript we evaluate the X-ray structure of five new pertechnetate derivatives of general formula [M(H₂O)₄(TcO₄)₂], M=Mg, Co, Ni, Cu, Zn (compounds 1–5) and one perrhenate compound Zn(H₂O)₄(ReO₄)₂ (6). In these complexes the metal center exhibits an octahedral coordination with the pertechnetate units as axial ligands. All compounds exhibit the formation of directional Tc⋅⋅⋅O Matere bonds (MaBs) that propagate the [M(H₂O)₄(TcO₄)₂], into 1D supramolecular polymers in the solid state. Such 1D polymers are linked, generating 2D layers, by combining additional MaBs and hydrogen bonds (HBs). Such concurrent motifs have been analyzed theoretically, suggesting the noncovalent σ-hole nature of the MaBs. The interaction energies range from weak (~ −2 kcal/mol) for the MaBs to strong (~ −30 kcal/mol) for the MaB+HB assemblies, where HB dominates. In case of M=Zn, the corresponding perrhenate Zn(H₂O)₄(ReO₄)₂ complex, has been also synthesized for comparison purposes, resulting in the formation of an isostructural X-ray structure, corroborating the structure-directing role of Matere bonds.

This study aimed to find a rapid extraction system for the preparation of a Seaborgium (Sg) aqueous chemistry experiment in the future. A new approach for extraction of ¹⁸¹W tracer as a lighter homolog of (Sg) by ionic liquids is explored. A natural tantalum target was activated by a beam of 9 MeV proton at Cologne University to produce carrier-free ¹⁸¹W. The preliminary batch extraction experiments of the carrier-free ¹⁸¹W from HCl and H₂SO₄ solutions have been evaluated. Different batch extraction parameters such as feed acidity, diluent type, ionic strength (KCl feed) and reducing agent as a function of time were explored. The obtained results demonstrated that the highest distribution of carrier-free ¹⁸¹W from 0.001 M acidic solutions using the used ionic liquid is observed. A significant rapid kinetic for the extraction of trace-scale using the used ionic liquid is achieved within 5 sec. The preliminary results are necessary to design the upcoming aqueous experiments of Sg. The next goal will be on-line experiments with the centrifuge system SISAK to develop the aqueous chemistry extraction of Sg using the most promising and adequate experimental setup.

Recent advancements in free electron lasing at UV wavelengths have been been demonstrated using the COXINEL beamline driven by HZDR plasma accelerator in a seeded configuration. To optimize FEL radiation, it is crucial to address the complex, multivariate parameters involved in laser-plasma acceleration, electron beam transport, and radiation generation. These challenges can be understood by solving an ill-posed inverse problem in finding matching parameters of the simulation to reproduce the experiments. Machine learning-based methods offer potential solutions by accelerating theoretical understanding, enabling design space exploration, and providing reliable in-situ analysis of experimental data. In our previous work, we employed manual feature extraction methods that proved effective but would require domain expertise. Currently, we are focused on developing automated feature extraction techniques employing deep representation learning to extract input-domain features. This approach enhances adaptability, allowing the models to be applied to similar problems, such as those encountered in COXINEL, without the need for manual, domain-specific feature extraction.

The number of crystal structures of pertechnetates derived from aqueous solutions has been expanded from seven to over 30. We report the conversion of NH₄TcO₄ to aqueous HTcO₄ via acidic cation exchange. This is followed by the synthesis and structural elucidation of pertechnetate salts of alkaline earth (AE), transition metal I and lanthanoids (Ln) elements. Various degrees of hydration and coordination are discussed. Where possible, a comparison with the perrhenate homologues is made. The described syntheses and materials may be used as novel starting materials for extended technetium research.

We present a robust computational method to calculate vibrational spectra for two-dimensional framework materials, specifically for covalent-organic frameworks (COFs). Conventional methods like harmonic approximation fails to capture anharmonic modes and solvent bands which are often observed in the vibrational spectra of these materials. In this study, we employ an AIMD (ab initio molecular dynamics) based approach where we compute the IR and Raman intensities from the time-correlation functions of dipole moments and polarizabilities, which aids us in the investigation of host-guest interactions. We present the AIMD-based IR and Raman spectra of COF-1 with and without 1,4-dioxane solvent molecules inside the pores. We dissect the obtained spectra into contributions coming from individual molecular units and solvent molecules in order to facilitate assignment of the peaks. Moreover, we explore the
influence of different methods for calculating dipole moments and polarizability tensors on the IR and Raman intensities. We compare our AIMD-based spectra with the experimental data, and we show that our results reach an excellent agreement with experiment.

Exotic band features, such as Dirac cones and flat bands, arise directly from the lattice symmetry of materials. The Lieb lattice is one of the most intriguing topologies, because it possesses both Dirac cones and flat bands which intersect at the Fermi level. However, the synthesis of Lieb lattice materials remains a challenging task. Here, we explore two-dimensional polymers (2DPs) derived from zinc-phthalocyanine (ZnPc) building blocks with a square lattice (sql) as potential electronic Lieb lattice materials. By systematically varying the linker length (ZnPc-xP), we found that some ZnPc-xP exhibit a characteristic Lieb lattice band structure. Interestingly though, fes bands are also observed in ZnPc-xP. The coexistence of fes and Lieb in sql 2DPs challenges the conventional perception of the structure–electronic structure relationship. In addition, we show that manipulation of the Fermi level, achieved by electron removal or atom substitution, effectively preserves the unique characteristics of Lieb bands. The Lieb Dirac bands of ZnPc-4P shows a non-zero Chern number. Our discoveries provide a fresh perspective on 2DPs and redefine the search for Lieb lattice materials into a well-defined chemical synthesis task.

Plasma-wakefield-based acceleration technology has the potential to revolutionize the field of particle accelerators. By providing acceleration gradients orders of magnitude larger than conventional radiofrequency particle accelerators, this technology allows accelerators to be reduced to the centimetre length scale. It also provides a new compact approach for driving free-electron lasers, a valuable source of high-brilliance ultrashort coherent radiation within the infrared to X-ray spectral range for the study of subatomic matter, ultrafast dynamics of complex systems and X-ray nonlinear optics, among other applications. Several laboratories around the world are working on the realization of these new light sources, exploring different configurations for the plasma wakefield driver beam, plasma stage design and operational regime. This Review describes the operating principles of plasma accelerators, an overview of recent experimental milestones for plasma-driven free-electron lasers in self-amplified spontaneous emission and seeded configurations, and highlights the remaining major challenges in the field.

In this study, the dissolution of a single oxygen bubble on a solid surface, here Titanium alloy Ti64, in ultrapure water with different oxygen undersaturation levels is investigated. For that purpose, a combination of shadowgraph technique and planar laser-induced fluorescence is used to measure simultaneously the changes in bubble geometry and in the dissolved oxygen concentration around the bubble. Two different wettabilities of the Ti64 surface are adjusted by using plasma-enhanced chemical vapor deposition. The dissolution process on the solid surface involves two distinct phases, namely bouncing of the oxygen bubble at the Ti64 surface and the subsequent dissolution of the bubble, primarily by diffusion. By investigating the features of oxygen bubbles bouncing, it was found that the boundary layer of dissolved oxygen surrounding the bubble surface is redistributed by the vortices emerging during bouncing. This establishes the initial conditions for the subsequent second dissolution phase of the oxygen bubbles on the Ti64 surfaces. In this phase, the mass transfer of O2 proceeds non-homogeneously across the bubble surface, leading to an oxygen accumulation close to the Ti64 surface. We further show that the main factor influencing the differences in the dynamics of O2 bubble dissolution is the variation in the surface area of the bubbles available for mass transfer, which is determined by the substrate wettability. As a result, dissolution proceeds faster at the hydrophilic Ti64 surface due to the smaller contact angle, which provokes a larger surface area.

At the electron accelerator for beams with high brilliance and low emittance (ELBE), the second version of a superconducting radio-frequency (SRF) photoinjector was brought into operation in 2014. After a period of commissioning, a gradual transfer to routine operation took place in 2017, so that now more than 1800h of user beam are generated every year. In addition to this routine operation with a few tens of microamperes, another important goal, the generation of an average current of 1 mA, which is high for electron linear accelerators, could now be demonstrated with our SRF gun. At the same time, this beam was already accelerated to almost 30 MeV by the ELBE LINAC and irradiated in one of the IR-FELs. This is particularly important with regard to the successor of the ELBE accelerator called DALI, which will be also fed by an SRF gun with a high average current. The contribution presents the most important steps for achieving the full beam current and summarizes related measurement results and findings. No fundamental difficulties were identified.

Bilayer graphene (BLG) has recently been used as a tool to stabilize the encapsulated single sheets of various layered materials and tune their properties. It was also discovered that the protecting action of graphene sheets makes it possible to synthesize completely new two-dimensional materials (2DMs) inside BLG by intercalating
various atoms and molecules. In comparison to the bulk graphite, BLG allows for easier intercalation and much larger increase in the inter-layer separation of the sheets. Moreover, it enables studying the atomic structure of the intercalated 2DM using high-resolution transmission electron microscopy. In this review, we summarize the recent
progress in this area, with a special focus on new materials created inside BLG. We compare the experimental findings with the theoretical predictions, pay special attention to the discrepancies and outline the challenges in the field. Finally, we discuss unique opportunities offered by the intercalation into 2DMs beyond graphene and their
heterostructures.

Uranium (U) mining has left a legacy of environmental contamination in the Federal States of Saxony and Thuringia (Germany). High concentrations of U and other heavy metals pose a potential threat to both the environment and human health, through contamination of soil and water. Additionally, it is well documented that other human activities, such as agronomic practices and military conflicts, have contributed to increasing the concentration of these contaminants. However, U has become one of the world's most important elements in the last 60 years due to its potential use in nuclear energy production. Therefore, it is essential to develop environmental rehabilitation programs in affected areas, along with adopting waste management practices that promote sustainability, including the possibility of recovering U from waste for reuse within the concept of circular economy.

Traditionally, physicochemical based conventional technologies have been used to remediate environments contaminated with U. However, these approaches tend to be costly, complex to apply, and ineffective for low concentrations of U. Hence, a promising alternative, less expensive, easy to implement, and effective for low U concentrations is bioremediation, based on the interaction mechanisms of biological systems with U. Based on extensive available literature, the main suggested strategies for U bioremediation include two approaches: biomineralization of U(VI) phosphates under oxic conditions and enzymatic reduction under anoxic conditions from soluble, highly mobile, and bioavailable U(VI) to insoluble, less mobile, and thus less bioavailable U(IV).

The aim of this PhD thesis was to characterize, through a multidisciplinary approach, two former German mine waters contaminated with U, Schlema-Alberoda and Pöhla (Wismut GmbH), in order to design a future U bioremediation strategy based on biostimulation of the native U-reducing microbial community.

The bioremediation of contaminated waters with low U concentrations shows a significant challenge, which can be addressed by stimulating U-reducing bacterial activity, as described in this PhD thesis. Moreover, this study not only provides new insights on the reduction of U(VI) to U(IV) but also emphasizes that the resulting product, U(V), is more stable than uraninite, thus increasing the potential of this strategy, considering the risk of U reoxidation.

Many inverse problems in physics are particularly challenging due to their ill-posed nature and high complexity. We tackle these challenges using physics-informed machine learning (ML) algorithms, invertible neural networks (INNs), and likelihood-based generative models, including conditional normalizing flows (cNFs).

First, the physics-informed ML incorporates physical models into neural networks (NNs) to address the challenge of limited experimental ground-truth datasets. For instance, in phase retrieval for X-ray holography, integrating the physics of image formation or wave propagation into calculating the loss function allows for automatic optimization to produce the desired solution.

Second, cNFs enable us to learn the full distribution of target parameters, capturing all possible solutions. This contrasts with classical neural networks and conventional algorithms, which often struggle with undetermined inverse problems, leading to ambiguities by predicting only a single or an average solution. In X-Ray and Neutron Reflectometry (XRR and NR), this helps distinguish between different thin film parameter sets that produce identical reflectivity curves caused by limited phase information.

We demonstrate, that our approaches successfully integrate ML to guide experimental design, optimize parameters, and enhance solutions for inverse problems, with applications in laser-plasma interactions, X-ray imaging, and related techniques. This highlights the potential of ML to advance research and overcome limitations in complex physical simulations and experiments.

Mosaic crystals, with their high integrated reflectivities, are widely employed in spectrometers used to diagnose high energy density systems. X-ray Thomson scattering (XRTS) has emerged as a powerful diagnostic tool of these systems, providing in principle direct access to important properties such as the temperature via detailed balance. However, the measured XRTS spectrum is broadened by the spectrometer instrument function (IF), and without careful consideration of the IF one risks misdiagnosing system conditions. Here, we consider in detail the IF of 40 and 100 μm mosaic Highly Annealed Pyrolytic Graphite crystals, and how the broadening varies across the spectrometer in an energy range of 6.7–8.6 keV. Notably, we find a strong asymmetry in the shape of the IF toward higher energies. As an example, we consider the effect of the asymmetry in the IF on the temperature inferred via XRTS for simulated 80 eV CH plasmas and find that the temperature can be overestimated if an approximate symmetric IF is used. We, therefore, expect a detailed consideration of the full IF will have an important impact on system properties inferred via XRTS in both forward modeling and model-free approaches.

At the technical colloquium on September 5th, Antonio Newman will present the findings of his PhD thesis. This project was developed in collaboration between the University of Granada (Spain) and the Helmholtz-Zentrum Dresden-Rossendorf (Germany), in collaboration with Wismut GmbH.
The project first geochemically characterized the mine water from Schlema-Alberoda and Pöhla using Inductively Coupled Plasma Mass Spectrometry (ICP-MS) and High Pressure Ion Chromatography (HPIC). Simultaneously, it analysed the microbial community through sequencing of bacterial 16S rRNA and fungal ITS genes. Additionally, this work explored key metabolic pathways involved in the biogeochemical cycles of sulphur, nitrogen, and carbon using metatranscriptomic analysis to understand the differences in U concentrations between the two mine waters. The study also involved isolating, identifying, and biochemically characterizing fungi from these waters, searching for strains with U immobilization potential. Finally, a complementary bioremediation strategy was designed and optimized to reduce U in the Schlema-Alberoda mine water, using the native bacterial community and glycerol as an electron donor, while characterizing the reduced U products with spectroscopic (e.g., High-Energy-Resolution Fluorescence Detected X-Ray Absorption Near Edge Structure (HERFD-XANES) and (Extended X-Ray Absorption Fine Structure (EXAFS)) and microscopic techniques (e.g., HRTEM).
The most notable findings of this PhD thesis include the effectiveness of using glycerol as an electron donor to stimulate the native microbial community involved in reducing soluble U in the Schlema-Alberoda mine water as a bioremediation strategy. Additionally, the study reports not only the reduction of U(IV) but also surprisingly high proportions of biogenic stable U(V), which had not been previously documented in the literature.

The former mining activity of U ores in Saxony and Thuringia (Germany) has led to the generation of U contaminated areas. Nowadays, conventional remediation methodologies are not able to remove soluble U entirely. Microorganisms offer an environmental friendly water remediation strategy for U through bioreduction or biomineralization. The present study describes the biostimulation of the native U reducing microbial community in a U contaminated mine water as an efficient and eco-friendly strategy for in situ bioremediation to prospectively support or outperform chemical water treatments. In our study, a multidisciplinary approach of analytical and spectroscopical methods were used. The microbial community was characterized by 16S and ITS1 rRNA gene analyses, showing a relative abundance of native microbial groups with the ability to alter the speciation and redox state of soluble U. A set of anerobic microcosms, supplemented with glycerol (10mM) as electron donor to stimulate U reducing bacteria, were designed as basis of an in situ bioremediation strategy for uranium contaminated waters. The black precipitate formed at the bottom of the microcosm was analyzed by High Energy Resolution Fluorescence Detected Near-edge X-ray absorption fine structure (HERFD-XANES) and Extended X-ray absorption fine structure (EXAFS). The results obtained revealed that microbial cycling processes have a significant impact on the complete enzymatic reduction of soluble U(VI) to U(IV) and U(V) by the addition of an electron donor in low U concentration contaminated mine water.

The former mining activity of U ores in Saxony and Thuringia (Germany) has led to the generation of U contaminated areas. Nowadays, conventional remediation methodologies are not able to remove soluble U entirely. Microorganisms offer an environmental friendly water remediation strategy for U through bioreduction or biomineralization. The present study describes the biostimulation of the native U reducing microbial community in a U contaminated mine water as an efficient and eco-friendly strategy for in situ bioremediation to prospectively support or outperform chemical water treatments. In our study, a multidisciplinary approach of analytical and spectroscopical methods were used. The microbial community was characterized by 16S and ITS1 rRNA gene analyses, showing a relative abundance of native microbial groups with the ability to alter the speciation and redox state of soluble U. A set of anerobic microcosms, supplemented with glycerol (10mM) as electron donor to stimulate U reducing bacteria, were designed as basis of an in situ bioremediation strategy for uranium contaminated waters. The black precipitate formed at the bottom of the microcosm was analyzed by High Energy Resolution Fluorescence Detected Near-edge X-ray absorption fine structure (HERFD-XANES) and Extended X-ray absorption fine structure (EXAFS). The results obtained revealed that microbial cycling processes have a significant impact on the complete enzymatic reduction of soluble U(VI) to U(IV) and U(V) by the addition of an electron donor in low U concentration contaminated mine water.

Aerosol particle separation is essential in diverse industrial and medical applications. In the present context, the separation of particles in a rising Taylor bubble is investigated. The distinctive elongated shape, bullet-shaped nose, and flat tail of Taylor bubbles make their application particularly interesting for investigating interfacial effects. The aerosols present in the gas Taylor bubble migrate to the water, where they are eventually trapped. Experimental 8 mm circular test sections with constriction ratios ranging from 10 % to 30 % are used to induce flow and bubble interface perturbations. With a particle size ranging from about 1 to 5 μm, the separation takes place in the inertia-dominated regime, where the particle inertia is strongly dependent on the air flow. First, we show how the constriction affects the dynamics of the Taylor bubble as it moves through the constriction. Second, we investigate the particle separation results in tubes with and without constrictions.

Gallium (Ga) recovery from the red mud, though important has never been successful due to several technical and economic reasons such as contaminant interference and the high cost of membranes due to their faster saturation resulting in the clogging of membranes with contaminants. This study demonstrated the recovery of Ga by a combination of HCl-based leaching, Fe/Al/Ti separation, and recovery of Ga using Cyphos IL 104-based solvent extraction and complexation of Ga with desferrioxamine B as a proof-of-principle of the GaLIophore technology. The main leaching parameters such as concentrations of acids, time and temperature of the reaction, and solid-to-liquid ratio have been systematically investigated. The optimal leaching conditions were determined as 4 mol/L HCl, 2 h time, 80 °C temperature, and solid-to-liquid ratio 1:20 (g/mL) attaining a more than 90% leaching of Ga. Subsequently, more than 99% Ga was extracted from the leachate using 0.05 mol/L Cyphos IL 104 at A:O ratio 1 and stripped by 0.01 mol/L H2SO4 at O:A ratio 1 from the organic phase. Desferrioxamine B (DFOB) demonstrated selectivity by complexing with more than 90% Ga in a stripped solution. The interaction between extractable species of Ga and Cyphos IL 104 was studied by Density Functional Theory (DFT) calculations and infrared spectroscopy. The whole process demonstrated the recovery of Ga by more than 80% present in the red mud. Further, the preliminary economic analysis suggests that the process can be profitable when Fe, Al, Sc, and Ga are recovered at a minimum rate of 50, 50, 75, and 75%.

The CNO cycle is one of the most important nuclear energy sources in stars. At temperatures of hydrostatic H-burning (20 MK < T < 80 MK) the ¹⁷O⁡(p,γ)⁢¹⁸F reaction rate is dominated by the poorly constrained 64.5 keV resonance. Here, we report on the first direct measurements of its resonance strength and of the direct capture contribution at 142 keV, performed with a new high sensitivity setup at LUNA.

The present resonance strength of ωγ^(bare)_⁡(p,γ)⁢ = (30 ± 6(stat.) ± 2(syst.) peV is about a factor of 2 higher than the values in literature, leading to a Γ(bare)_(p) = (34 ± 7(stat.) ± 3(syst.)) neV, in agreement with the LUNA result from the (p,α) channel. Such agreement strengthens our understanding of the oxygen isotopic ratios measured in red giant stars and in O-rich presolar grains

As the physicochemical properties of ultrafine bubble systems are governed by their size, it is crucial to determine the size and distribution of such bubble systems. At present, the size or size distribution of nanometer-sized bubbles in suspension is often measured by either dynamic light scattering or the nanoparticle tracking analysis. Both techniques determine the bubble size via the Einstein–Stokes equation based on the theory of the Brownian motion. However, it is not yet clear to which extent the Einstein–Stokes equation is applicable for such ultrafine bubbles. In this work, using atomic molecular dynamics simulation, we evaluate the applicability of the Einstein–Stokes equation for gas nanobubbles with a diameter less than 10 nm, and for a comparative analysis, both vacuum nanobubbles and copper nanoparticles are also considered. The simulation results demonstrate that the diffusion coefficient for rigid nanoparticles in water is found to be highly consistent with the Einstein–Stokes equation, with slight deviation only found for nanoparticle with a radius less than 1 nm. For nanobubbles, including both methane and vacuum nanobubbles, however, large deviation from the Einstein–Stokes equation is found for the bubble radius larger than 3 nm. The deviation is attributed to the deformability of large nanobubbles that leads to a cushioning effect for collision-induced bubble diffusion.

Nuclear reactions are responsible for the chemical evolution of stars, galaxies and the Universe. Unfortunately, at temperatures of interest for nuclear astrophysics, the cross-sections of the thermonuclear reactions are in the pico- to femto-barn range and thus measuring them in the laboratory is extremely challenging. In this framework, major steps forward were made with the advent of underground nuclear astrophysics, pioneered by the Laboratory for Underground Nuclear Astrophysics (LUNA). The cosmic background reduction by several orders of magnitude obtained at LUNA, however, needs to be combined with high-performance detectors and dedicated shieldings to obtain the required sensitivity. In the present paper, we report on the recent and future detector-shielding designs at LUNA.

We provide an extended lattice study of the SU(2) gauge theory coupled to one Dirac fermion flavour (Nf=1Nf​=1) transforming in the adjoint representation as the continuum limit is approached. This investigation is supplemented by numerical results obtained for the SU(2) gauge theory with two Dirac fermion flavours (Nf=2Nf​=2) transforming in the adjoint representation, for which we perform numerical investigations at a single lattice spacing value, which is analysed together with earlier calculations. The purpose of our study is to advance the characterisation of the infrared properties of both theories, which previous investigations have concluded to be in the conformal window. For both, we determine the mass spectrum and the anomalous dimension of the fermion condensate using finite-size hyperscaling of the spectrum, mode number analysis of the Dirac operator (for which we improve on our previous proposal) and the ratio of masses of the lightest spin-2 particle over the lightest scalar. All methods provide a consistent picture, with the anomalous dimension of the condensate γ∗γ∗​ decreasing significantly as one approaches the continuum limit for the Nf=1Nf​=1 theory towards a value consistent with γ∗=0.174(6)γ∗​=0.174(6), while for Nf=2Nf​=2 the anomalous dimension decreases more slowly with ββ. A chiral perturbation theory analysis show that the infrared behaviour of both theories is incompatible with the breaking of chiral symmetry.

The Dresden laser acceleration source (DRACO) is a state-of-the-art high-power ultra-short pulse laser system[1,2],
that uses an Amplitude Technologies Pulsar architecture to form main and diagnostics beams at different focal lengths and target density conditions.
The setup can deliver from 6J to 45J of pulse energy at a typical pulse duration of 30fs and a typical frequency of 1Hz.
During the diagnostic phase, the beam characteristics are recorded in the form of images and several instrument parameters,
that shape the beam to desired characteristics.

In this talk, we present our approach of implementing FAIR principles to DRACO
operations and monitoring using our in-house guidance system HELIPORT[3],
with the goal of making them reusable irrespective of the downstream experiment.
We employ FAIR workflows[4] to post-process data collected by DRACO's built-in data
acquisition system and enrich it with metadata for subsequent utilization in
machine-learning and optimization algorithms for accurate control of the beam characteristics.
The intergration of DRACO and HELIPORT demonstrates the first step towards establishing
a digital twin for the laser source facility at HZDR.

[1] First results with the novel Petawatt laser acceleration facility in Dresden, U. Schramm et al, J. Phys. Conf. Ser. 874 012028 (2017)
[2] High dynamic, high resolution and wide range single shot temporal pulse contrast measurement, T. Oksenhendler et. al., Opt. Express 25, 12588-12600 (2017)
[3] HELIPORT: A Portable Platform for FAIR {Workflow | Metadata | Scientific Project Lifecycle} Management and Everything, O. Knodel et. al., P-RECS (2021)
[4] FAIR Computational workflows, C. Goble et. al., Data Intelligence (2020) 2, 108 (2020)

The very limited number of structurally known thionitrosyl complexes of technetium was increased by the synthesis of [Tcᴵᴵ(NS)Cl₃(PPh₃)₂] (3) and [Tcᴵᴵ(NS)Cl₃(PPh₃)(OPPh₃)] (4) and their reaction products with hydrotris(pyrazolyl)borates, {HB(pzᴿ)₃}⁻. Similar reactions were conducted with [Tcᴵ(NO)Cl₂(PPh₃)₂(CH₃CN)] and related rhenium thionitrosyls. Remarkably, most such reactions result in a rapid cleavage of the boron–nitrogen bonds of the ligands and the formation of pyrazole complexes of the two group 7 metals. Only one compound with an intact {HB(pzᴿ)₃}⁻ ligand could be isolated: the technetium(I) complex [Tcᴵ(NO)Cl(PPh₃){HB(pz)₃}] (2). Other products show the coordination of one or four neutral pyrazole ligand(s) in the coordination spheres of technetium generated by thermal decomposition of the pyrazolylborates [Tcᴵ(NO)Cl₂(PPh₃)₂(pzᴴ)] (1) and [Tcᴵ(NS)Cl(pzᴴᴹᵉ²)₄]⁺ (5). Reactions with the corresponding thionitrosylrhenium complex [Reᴵᴵ(NS)Cl₃(PPh₃)₂] require higher temperatures and only compounds with one pyrazole ligand, [Reᴵ(NS)Cl₂(PPh₃)(pzᴴᴿ)] (6a–6c), were isolated. The products were studied spectroscopically and by X-ray diffraction.

We present the experimental results of a 2-D scintillator-based detector developed at the Centro de Laseres Pulsados (CLPU) aiming at the spatiospectral characterization of proton beams driven by ultrarelativistic laser pulses at a high repetition rate (HRR). We report its implementation in laser-driven proton acceleration at the VEGA (CLPU) laser facility to demonstrate its operation. The analysis of the obtained results shows the relevance of the presented diagnostic for HRR acquisition of laser-driven proton sources promoting it as an essential tool for large parametric studies in the emerging field of laser-driven accelerators. A validation of the spectral and divergence reconstruction method is also presented together with the scintillator calibration performed at the conventional accelerator Centro de Micro-Análisis de Materiales (CMAM) in Madrid, Spain.

Amonton's law of friction states that the friction force is proportional to the normal force in magnitude, and the slope gives a constant friction coefficient. In this work, with molecular dynamics simulation, we study how the kinetic friction at the nanoscale deviates qualitatively from the relation. Our simulation demonstrates that the friction behavior between a nanoscale AFM tip and an elastic graphene surface is regulated by the coupling of the applied normal force and the substrate deformability. First, it is found that the normal load-induced substrate deformation could lower friction at low load while increasing it at high load. In addition, when the applied force exceeds a certain threshold another abrupt change in friction behavior is observed, i.e., the stick–slip friction changes to the paired stick–slip friction. The unexpected change in friction behavior is then ascribed to the change of the microscopic contact states between the two surfaces: the increase in normal force and the substrate deformability together lead to a change in the energy landscape experienced by the tip. Finally, the Prandtl–Tomlinson model also validates that the change in friction behavior can be interpreted in terms of the energy landscape.

The structural and magnetic properties of sputter-deposited Fe_100−xRu_x films were studied for x < 50. The crystal structure of Fe_100−xRu_x is shown to be predominantly body-centered cubic for x < 13 and to undergo a gradual transition to hexagonal close-packed in the Ru concentration range 13 < x < 20. Magnetic measurements indicate that the addition of Ru to Fe gives rise to a noncollinear magnetic alignment between Fe atoms in the body-centered cubic FeRu alloys, while the hexagonal close-packed FeRu alloys exhibit paramagnetic behavior. A simple atomistic model was used to show that the competition between ferromagnetic coupling of neighboring Fe atoms and antiferromagnetic coupling of Fe atoms across Ru atoms in cubic FeRu structures can induce noncollinear magnetic order. Magnetic multilayer structures used in thin-film magnetic devices make extensive use of both Fe and Ru layers. Our results reveal that the presence of even a small amount of Ru in Fe influences the magnetic order of Fe, which could impact the performance of these devices.

Composites consisting of magnetic fillers in polymers and elastomers enable new types of applications in soft robotics, reconfigurable actuation and sensorics. In particular, soft-bodied robots emerge as the closest synthetic system analogous to living organisms mimicking their mechanical behavior and going beyond in performance. 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], which help to assess the magnetic state of the actuator (magnetized vs. non-magnetized), decide on its actuation pattern and control sequentiality and quality of the folding process. The on-board sensing adds awareness to soft-bodied magnetic actuators enabling them to act and be controlled similar to conventional robotic devices [6].
Magnetic composites can be readily used to realise not only actuators but also magnetic field sensors [7]. We demonstrate that printed magnetoelectronics can be stretchable, skin-conformal, capable of detection in low magnetic fields and withstand extreme mechanical deformations [8,9]. We feature the potential of our skin-conformal sensors in augmented reality settings [10,11], where a sensor-functionalized finger conducts remote and touchless control of virtual objects manageable for scrolling electronic documents and zooming maps under tiny permanent magnet [8].
Furthermore, we put forth technology to realise magnetic field sensors, which can be printed and self-heal upon mechanical damage [12]. This opens exciting perspectives for magnetoelectronics in smart wearables, interactive printed electronics and motivates further explorations towards the realisation of recyclable magnetoelectronics [13]. 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] J. Ge et al., A bimodal soft electronic skin for tactile and touchless interaction in real time. Nature Communications 10, 4405 (2019).
[11] P. Makushko et al., Flexible magnetoreceptor with tunable intrinsic logic for on-skin touchless human-machine interfaces. Adv. Funct. Mater. 31, 2101089 (2021).
[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).

Despite remarkable efficacy in hematological malignancies, chimeric antigen receptor (CAR) T-cell therapy can also lead to life-threatening side effects. To overcome these safety issues, we developed adaptor CAR platforms such as the Universal CAR (UniCAR) system. In this system, T-cells are engineered to express a UniCAR targeting the E5B9 epitope derived from the nuclear La protein. The redirection of UniCAR T-cells to target cells relies on a Target Module (TM), which contains the E5B9 epitope and a tumor-specific binding moiety. Successful UniCAR T-cell activation thus involves two different interactions: between the TM and UniCAR T-cells, and the TM and target cells. Here, we study whether and how changes in the amino acid sequence of the E5B9 epitope influence the interaction between TMs and the UniCAR. We identified the epitope E5B9L, for which the monoclonal antibody 5B9 has the greatest affinity. We then integrated the E5B9L peptide in previously established TMs directed to the Fibroblast Activation Protein (FAP) and we evaluated if such changes in the E5B9 epitope affect UniCAR T-cell potency. Despite a significant variation in the affinity of the TMs to the UniCAR, no substantial differences were observed in the cytotoxic and cytokine-release profiles of the redirected UniCAR T-cells. Finally, in vivo studies revealed that FAP-specific TMs specifically accumulate and effectively redirect UniCAR T-cells to FAP+ tumors, demonstrating their immunotheranostic potential. Our work suggests that increasing affinity of the UniCAR to the TM does not play an essential role in such adaptor CAR platform.

Highly simplified electrolyzer designs in the form of a membraneless alkaline electrolyzer (MAEL) allow higher current densities compared to conventional designs and result as well in lower capital expenditures. In addition, MAELs provide very good access to the electrodes, making them ideal for research to better understand bubble formation and detachment. Since there is no membrane or diaphragm to separate the products, H2 and O2, the cell design to direct the electrolyte flow is critical.

Using CFD and current simulations, an optimized cell geometry was developed to ensure constant conditions for the water splitting reaction over the entire electrode. Particle Image Velocimetry and Shadowgraphy were used to systematically study the influence of the electrolyte flow as driving force for an effective H2 and O2 separation. It is shown that below a critical Recrit the evolving bubbles are stuck on the porous electrodes and lead to a blockage of electrochemical active sites as well as to an increase of the cell potential. On the other hand, high gas purity and overall efficiency were observed at the optimal flow rate to current density ratio. Thus, the present study proves the concept of the newly developed membraneless electrolyzer.

The Geyer tin skarn in the Erzgebirge, Germany, comprises an early skarnoid stage (stage I, ~ 320 Ma) and a younger
metasomatic stage (stage II, ~ 305 Ma), but yet, the source and distribution of Sn and the physicochemical conditions
of skarn alteration were not constrained. Our results illustrate that contact metamorphic skarnoids of stage I contain
only little Sn. REE patterns and elevated concentrations of HFSE indicate that garnet, titanite and vesuvianite of stage I
formed under rock-buffered conditions (low fluid/rock ratios). Prograde assemblages of stage II, in contrast, contain two
generations of stanniferous garnet, titanite-malayaite and vesuvianite. Oscillation between rock-buffered and fluid-buffered
conditions are marked by variable concentrations of HFSE, W, In, and Sn in metasomatic garnet. Trace and REE element
signatures of minerals formed under high fluid/rock ratios appear to mimic the signature of the magmatic-hydrothermal
fluid which gave rise to metasomatic skarn alteration. Concomitantly with lower fluid-rock ratio, tin was remobilized
from Sn-rich silicates and re-precipitated as malayaite. Ingress of meteoric water and decreasing temperatures towards
the end of stage II led to the formation of cassiterite, low-Sn amphibole, chlorite, and sulfide minerals. Minor and trace
element compositions of cassiterite do not show much variation, even if host rock and gangue minerals vary significantly,
suggesting a predominance of a magmatic-hydrothermal fluid and high fluid/rock ratios. The mineral chemistry of major
skarn-forming minerals, hence, records the change in the fluid/rock ratio, and the arrival, distribution, and remobilization
of tin by magmatic fluids in polyphase tin skarn systems.

In laser-ion acceleration experiments, the interaction of the rising flank of a high power laser
pulse with the target can cause pre-ionization and subsequent target pre-expansion long before the arrival of the main laser peak. Exact knowledge of this target pre-expansion is required in order to understand the laser-plasma acceleration mechanisms with the help of numerical simulations.
For dielectric targets, the starting point of target pre-expansion is characterized by the point in time at which the target undergoes laser-induced breakdown (LIB). In this work, we present a method to determine the time of LIB in sub-micron-thick Formvar targets during interaction with a specific high-power laser pulse. The required pulse-duration-dependent LIB threshold of Formvar is measured in a dedicated experiment. A comparison of LIB threshold to previously published data facilitates a generalization to other wide-band-gap dielectric targets for laser-ion acceleration.

Lanthanides (Ln) are crucial in various industrial and scientific applications. Their intense exploitation opens the door to a multitude of possible entry paths into the environment. Plants have the ability to take up and accumulate non-essential metals, so it is vital to understand the fate of Ln in the biosphere and, in particular, their bioaccumulation behavior. This study aimed to elucidate the process of interaction between Ln and plants, from the initial exposure and cellular uptake, through internal distribution, to the translocation into and deposition in aboveground parts.

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

Micropollutants, called MPs, are various anthropogenic contaminants frequently found in trace amounts in several environmental matrices and living organisms. The MPs include pharmaceuticals, personal care products, pesticides, persistent organic pollutants, micro- and nano-plastics, and artificial sweeteners, which all have the potential to cause harm to the ecological environment. Due to their chemical properties, stability and non-biodegradability, conventional water treatments cannot eliminate them. As a result, the advanced oxidation processes (AOP) have been extensively researched as a potential solution. Among AOPs, in this research, hydrodynamic cavitation (HC) combined with dissolved ozone (O3) was evaluated for the rapid removal of succinic acid (SA) by analysing the effect of the mass ratio of ozone-micropollutant, cavitation number (Cv) and inlet pressure (pinlet) of the HC/O3 process. At optimal conditions, the SA removal was about 41.2% at an initial SA concentration of 106.3 mg L‒1, Cv of 0.02, pinlet of 48 bar, the mass ratio of ozone-SA 0.03 mg mg‒1, 20ºC while the used hydraulic power was 20 W. Regarding the proof of concept with real wastewater spiked with SA (106.3 mg L‒1), the total organic carbon (TOC) removal was about 60% at the initial TOC concentration of 35.5 mg L‒1, pinlet of 30 bar, Cv of 0.02, the mass ratio of ozone-TOC of 0.77 mg mg‒1, while the used hydraulic power was 8 W. The electrical energy per order (EEO) calculated was 12.5 kWh m‒3 order‒1, indicating that the HC/O3 could be a promising combination for the high and continuous removal of ozone-resistant MPs.

Despite remarkable efficacy in hematological malignancies, chimeric antigen receptor (CAR) T-cell therapy can also lead to life-threatening side effects. To overcome these safety issues, we developed adaptor CAR platforms such as the Universal CAR (UniCAR) system. In this system, T-cells are engineered to express a UniCAR targeting the E5B9 epitope derived from the nuclear La protein. The redirection of UniCAR T-cells to target cells relies on a Target Module (TM), which contains the E5B9 epitope and a tumor-specific binding moiety. Successful UniCAR T-cell activation thus involves two different interactions: between the TM and UniCAR T-cells, and the TM and target cells. Here, we study whether and how changes in the amino acid sequence of the E5B9 epitope influence the interaction between TMs and the UniCAR. We identified the epitope E5B9L, for which the monoclonal antibody 5B9 has the greatest affinity. We then integrated the E5B9L peptide in previously established TMs directed to the Fibroblast Activation Protein (FAP) and we evaluated if such changes in the E5B9 epitope affect UniCAR T-cell potency. Despite a significant variation in the affinity of the TMs to the UniCAR, no substantial differences were observed in the cytotoxic and cytokine-release profiles of the redirected UniCAR T-cells. Finally, in vivo studies revealed that FAP-specific TMs specifically accumulate and effectively redirect UniCAR T-cells to FAP+ tumors, demonstrating their immunotheranostic potential. Our work suggests that increasing affinity of the UniCAR to the TM does not play an essential role in such adaptor CAR platform.

In recent decades, various strategies have been implemented to reprogram immune effectors against tumour cells. Among them, Chimeric Antigen Receptor (CAR) T-cell therapy has shown remarkable efficacy in haematological malignancies. However, this therapy can also cause severe to life-threatening side effects. To address these safety concerns, we have developed modular CAR platforms, such as the Universal CAR (UniCAR) system. In the UniCAR system, T-cells are genetically modified to express a single-chain fragment variable (scFv) targeting the E5B9 UniCAR epitope derived from the nuclear La protein. UniCAR T-cell redirection to the target cells relies on a Target Module (TM), a bridging molecule that contains the E5B9 epitope and a tumour-specific binding moiety. Appropriate UniCAR-T activation thus involves two interactions with different affinities: between the TM and CAR T-cells, and the TM and target cells. To date, little is known about the role of the affinity between adaptor CARs and adaptor molecules on CAR T-cell functionality. In the UniCAR platform, the interaction between the UniCAR and the TM can easily be fine-tuned by modifying the primary amino acid sequence and size of the original E5B9 UniCAR epitope, without the need to re-engineer the CAR. In this work, we investigate whether and how alterations of the amino acid sequence of the E5B9 UniCAR epitope, including the amino acids flanking the E5B9 epitope in the native La protein, may impact the affinity of the UniCAR to the TM and thereby the functionality of the adaptor CAR system. In this way, we identified potential new UniCAR related epitopes and among them, one named E5B9L, for which the monoclonal antibody 5B9 has the highest affinity. Having replaced the original E5B9 UniCAR epitope with E5B9L in a TM targeting the Fibroblast Activation Protein (FAP), we evaluated how this modification affects UniCAR T-cell functionality. The binding properties of the newly generated anti-FAP-E5B9L TMs to UniCAR and their capacity to redirect UniCAR T-cells were compared directly with those of the original anti-FAP-E5B9 TMs. In spite of the significant variation in the affinity of the different TMs to the UniCAR, no major differences were detected with respect to cytotoxic and cytokine-release properties of the redirected UniCAR T-cells. Altogether, our findings show no significant impact on the in vitro functionality and potency of UniCAR T-cells, suggesting that increasing the affinity between the UniCAR and the TM by changing the amino acid sequence of the E5B9 UniCAR epitope does not play an essential role in this adaptor CAR system.

OncoProTools Annual meeting - An update of the project was given to all the people who belong to the consortium.

Over the past decades, there has been a significant focus on reprogramming immune cells for targeting tumor cells, with Chimeric Antigen Receptor (CAR) T-cells emerging as a highly promising technology. Despite remarkable efficacy in hematologic malignancies, CAR T-cell therapy can cause severe to life-threatening adverse events. To address these safety issues, we and others have developed adaptor CAR platforms, such as the Universal CAR (UniCAR) system. In the UniCAR system, T-cells are engineered to express a UniCAR directed to the non-tumoral peptide epitope E5B9 derived from the nuclear La protein. UniCAR T-cell activation relies on the presence of a Target Module (TM), a bridging molecule that contains the E5B9 epitope and a binding moiety that specifically recognizes antigens on the tumor cells. The redirection of the UniCAR T-cells to target cells thus involves two interactions with different affinities, between (i) the TM and the CAR T-cell or (ii) the TM and the target cell.
So far, little is known about how the affinity between adaptor molecules and adaptor CAR T-cells impacts their functionality. In the case of the UniCAR platform, the interaction between the UniCAR and the TM can easily be tuned by engineering the amino acid sequence of the E5B9 peptide, without the need to re-modify the CAR.
Here, we investigate whether and how the amino acid sequence of the UniCAR epitope, including the amino acids flanking the E5B9 epitope in the native La protein, may affect the interaction between a UniCAR TM and UniCAR T-cells. By engineering the E5B9 peptide in previously published UniCAR TMs directed to the Fibroblast Activation Protein (FAP), we assess whether the modified E5B9 epitope (named E5B9L) affect the potency of UniCAR T-cells.
Overall, our work indicates that the binding affinity between the TM and the UniCAR T-cells does not play a crucial role. This affinity can fluctuate across a broad spectrum, ranging from low picomolar to nanomolar values, without significantly impacting the functionality and/or potency of the UniCAR T-cells.

The discharge of effluents containing emerging contaminants, such as pharmaceuticals, pesticides, and industrial chemicals, into water bodies has recently become a major environmental and public health concern. Addressing this challenge, advanced oxidation processes (AOPs) play an important role by providing effective treatment methods for the removal of these complex, persistent, and non-biodegradable contaminants. AOPs involve the production of highly reactive hydroxyl radicals (HO•), capable of breaking down a wide variety of organic contaminants into simpler, less hazardous products. Among many AOPs, hydrodynamic cavitation (HC) stands out as a promising technology for treating refractory pollutants efficiently. HC is based on the formation and implosion of bubbles in a liquid, creating an intensive chemical and physical environment that produces HO• and other reactive species. In our investigation, HC was coupled with a non-condensable gas, such as ozone (O3), to enhance the generation of HO• and consequently boost the overall oxidative potential of the treatment process. In our research, using a laboratory-scale HC system, we treated aqueous solutions containing succinic acid (SA) by adjusting the nozzle pressure and O3 concentration. From a series of experiments, the results demonstrated that higher nozzle pressure coupled with lower O3 injection led to more efficient SA removal. Concurrently, numerical simulations with varying nozzle pressures were performed using ANSYS CFD software, incorporating the Schnerr-Sauer cavitation model. This approach facilitated a detailed analysis of fluid flow and cavitation characteristics. Notably, increasing the nozzle pressure extended the cavitation jet in the chamber, promoting enhanced mixing. This in turn, facilitated higher bubble implosion, radical production, and increased reaction contact, resulting in more effective pollutant removal in water treatment. The simulation results were qualitatively validated through experimental work, demonstrating good agreement between the two approaches. This integrated study underscores the potential of hydrodynamic cavitation especially when combined with ozone, as an efficient solution for the treatment of challenging pollutants in water systems.

Chimeric Antigen Receptor (CAR) T-cells have shown promising clinical results in hematologic malignancies, although they can cause significant side effects. To address these safety issues, we have developed adaptor CAR platforms, such as the UniCAR system. The redirection of UniCAR T-cells to target cells relies on a Target Module (TM), containing the E5B9 epitope and a tumor-specific binding moiety. Appropriate UniCAR-T activation thus involves two interactions: between the TM and the CAR T-cell, and the TM and the target cell. Here, we investigate whether and how modifications of the amino acid sequence of the E5B9 UniCAR epitope impact the interaction between TMs and the UniCAR. We identify the epitope E5B9L, for which the monoclonal antibody 5B9 has the greatest affinity. We then integrate the E5B9L peptide in previously established TMs directed to Fibroblast Activation Protein (FAP) and evaluate if such changes in the UniCAR epitope of the TMs affect UniCAR T-cell potency. Binding properties of the newly generated anti-FAP-E5B9L TMs to UniCAR and their ability to redirect UniCAR T-cells were directly compared with the ones of anti-FAP-E5B9 TMs. Despite a significant variation in the affinity of the different TMs to the UniCAR, no substantial differences were observed in the cytotoxic and cytokine-release profiles of the redirected T-cells. Overall, our work suggests that increasing affinity of the UniCAR to the TM does not play an essential role in such adaptor CAR platform, as this change does not significantly impact the potency of the UniCAR T-cells.

Water contamination is a crucial environmental concern all around the world. Organic micropollutants (OMPs) have a significant role in contaminating most of water bodies and negatively impacting the environment. OMPs are a group of hazardous and chemically stable contaminants that cannot be entirely eliminated by existing wastewater treatment plants. Advanced oxidation processes (AOPs) based on the formation of hydroxyl radicals (HO) have been successfully used to remove various OMPs from water. In our investigations, we are using hydrodynamic cavitation (HC) with addition of ozone (O3) oxidant as an AOP for oxidation of OMPs. HC is a process that involves the formation and powerful implosion of bubbles as a response of pressure fluctuations in the liquid, resulting in the production of various reactive species. The addition of an oxidant (O3) during HC could facilitate in the enrichment of reactive species. The OMP treatment was carried out using various input variables, such as nozzle pressure and O3 dosage. In parallel, the numerical simulation is carried out by combining computational fluid dynamics (CFD) with an existing cavitation model to capture the cavitation jet and HO formation. The simulation investigation was qualitatively compared to the experimental results, and the main experimental findings are reflected in the simulation results.

Historically, cerium has been attractive for pharmaceutical and industrial applications. The cerium atom has the unique ability to cycle between two chemical states (Ce(III) and Ce(IV)) and drastically adjust its electronic configuration: [Xe] 4f15d16s2 in response to a chemical reaction. Understanding how electrons drive chemical reactions is an important topic. The most direct way of probing the chemical and electronic structure of materials is by X-ray absorption spectroscopy (XAS) or X-ray absorption near-edge structure (XANES) in high energy resolution fluorescence detection (HERFD) mode. Such measurements at the Ce L3 edge have the advantage of a high penetration depth, enabling in-situ reaction studies in a time-resolved manner and investigation of material production or material performance under specific conditions. But how much do we understand Ce L3 XANES? This article provides an overview of the information that can be extracted from experimental Ce L3 XAS/XANES/HERFD data. A collection of XANES data recorded on various cerium systems in HERFD mode is presented here together with detailed discussions on data analysis and the current status of spectral interpretation, including electronic structure calculations.

he preparation of synthetic (Zr,U)SiO4 solid solution is challenging, as the conventional high-temperature
solid-state method limits the solubility of uranium (4 ± 1 mol%) in the orthosilicate phase due to its
thermodynamic instability. However, these compounds are of great interest as a result of (Zr,U)SiO4 solid
solutions, with uranium contents exceeding this concentration, being observed as corium phases formed
during nuclear accidents. It has been identified that hydrothermal synthesis pathways can be used for the
formation of the metastable phase, such as USiO4 . The investigation carried out in this study has indeed
led to the confirmation of metastable (Zr,U)SiO4 compounds with high uranium contents being formed. It
was found that (Zr,U)SiO4 forms a close-to-ideal solid solution with uranium loading of up to 60 mol% by
means of hydrothermal treatment for 7 days at 250 °C, at pH = 3 and starting from an equimolar reactant
concentration equal to 0.2 mol L−1 . A purification procedure was developed to obtain pure silicate com-
pounds. After purification, these compounds were found to be stable up to 1000 °C under an inert atmo-
sphere (argon). The characterisation methods used to explore the synthesis and thermal stability included
powder X-ray diffraction (PXRD), Fourier transform infrared (FTIR) and Raman spectroscopies, scanning
electron microscopy (SEM) and thermogravimetric analysis (TGA).

Micropollutants (MPs) encompass a range of human-made pollutants present in trace amounts in environmental systems. MPs include pharmaceuticals, personal care products, pesticides, persistent organic pollutants, micro- and nano-plastics, and artificial sweeteners, all posing ecological risks. Conventional municipal wastewater treatment methods often face challenges in completely removing MPs due to their chemical characteristics, stability, and resistance to biodegradation. In this research, a novel Advanced Oxidation Process, combining hydrodynamic cavitation (HC) with dissolved ozone (O3), was employed to effectively degrade succinic acid (SA), a representative ozone-resistant compound. The HC/O3 process was run to treat different synthetic effluents, focusing on evaluating the influence of O3-to-total organic carbon (TOC) ratio, cavitation number (Cv) and O3 dosage. Notably, the results from a series of 14 experiments highlighted the critical significance of a low O3-to-TOC ratio value of 0.08 mg/mg and Cv value of 0.056 in HC for achieving efficient SA removal of 41.2% from an initial SA solution (106.3 mg/L). Regarding a series of four proof-of-concept experiments and their replications, the average TOC removal reached 62% when treating wastewater treatment plant effluent spiked with SA. This significant removal rate was achieved under initial conditions: Cv of 0.02, O3-to-TOC ratio set at 0.77 mg/mg, TOC concentration of 47.7 mg/L, 106 mg/L of SA, and a temperature of 25ºC. Notably, the electrical energy per order required for the 62% reduction in TOC was a modest 12.5 kWh/m3/order, indicating the potential of the continuous HC/O3 process as a promising approach for degrading a wide range of MPs.

Background/Aim: Natural compounds such as propolis have gained wide popularity in the last decades. While its antibacterial, antiviral, and antifungal properties are well known, the anticancer properties of propolis are just beginning to be appreciated. Herein, we comparatively investigate the cytotoxic and radiosensitizing potential of four different ethanolic propolis extracts originating from three different countries (Germany, Ireland, South Africa) in human lung cancer cell models. Materials and Methods: Liquid chromatography–mass spectrometry (LC-MS/MS) was applied to characterize the four different propolis extracts. Cytotoxicity and radiation survival were determined by 3D matrix-based clonogenic assays and autophagy was examined by western blotting. Results: We found cytotoxicity in a propolis type-, time- and cell model- dependent manner. In the four ethanolic propolis extracts, Coumaric acid, Caffeic acid phenethyl ester, Pinocembrin and Chrysin presented the major compounds identified. Examining the induction of autophagy using the marker LC3B and autophagy inhibition with chloroquine suggested autophagy to be part of the survival mechanisms upon propolis treatment in a cell model-dependent manner. Combining propolis with X-ray irradiation showed the radiosensitizing potential of propolis in human lung cancer cell models, which clearly presented in a manner dependent on the incubation time of propolis and the cell model treated. Conclusion: Propolis treatment showed cytotoxic and radiosensitizing effects of propolis on human lung cancer cells. Since these effects differ greatly between the four propolis extracts studied and originating from different regions, further studies are urgently needed to differentiate propolis species and their anticancer properties in more detail.

Understanding the electrical conductivity of warm dense hydrogen is critical for both fundamental physics and applications in planetary science and inertial confinement fusion. We demonstrate how to calculate the electrical conductivity using the continuum form of Ohm's law, with the current density obtained from real-time time-dependent density functional theory. This approach simulates the dynamic response of hydrogen under warm dense matter conditions, with temperatures around 30,000 K and mass densities ranging from 0.02 to 0.98 g/cc. We systematically address finite-size errors in real-time time-dependent density functional theory, demonstrating that our calculations are both numerically feasible and reliable. Our results show good agreement with other approaches, highlighting the effectiveness of this method for modeling electronic transport properties from ambient to extreme conditions.

Profile analysis tensiometry (PAT) with drops and bubbles is a successful methodology to characterize liquid–fluid interfaces. Questions about the most suitable size of drops and bubbles have been solved now on the basis of dimensionless numbers. The consideration of the standard deviation between measured and calculated liquid profiles as a sensitive measure for the applicability of PAT provides a tool for its correct use. For solutions of highly surface-active compounds, bulk depletion effects can cause systematic errors in the analysis of adsorption kinetics, equations of state, and the visco-elastic interfacial behavior of liquid adsorption layers. Great progress has been made in measurements of interfacial dilational rheology with large amplitude perturbations providing additional information about structure and dynamics of complex adsorption layers. Also, first attempts are successfully made to use artificial intelligence (AI) to enhance the efficiency of PAT applications. Thus, PAT has established a solid position in surface science.

Elasto-capillary deformation is a phenomenon observed when a single long flexible fibre, due to dominant capillary force, deforms spontaneously upon interacting with a drop. This mechanism is crucial for a wide range of applications such as textile flotation, microfolding of elastic structures, fabrication of stretchable microelectronics, development of portable medical devices, and stabilization of emulsions. The research aims to explore the dynamic interactions between the fibre and the drop, an area with limited existing research. Key objectives include determining the changes in fibre dynamics due to drop and observing fibre-drop deformation upon evaporation.

Magnetism of oxide antiferromagnets (AFMs) has been studied in single crystals and extended thin films. The properties of AFM nanostructures still remain underexplored. Here, we report on the fabrication and magnetic imaging of granular 100-nm-thick magnetoelectric \ch{Cr2O3} films patterned in circular bits with diameters ranging from 500 down to 100\,nm. With the change of the lateral size, the domain structure evolves from a multidomain state for larger bits to a single domain state for the smallest bits. Based on spin-lattice simulations, we show that the physics of the domain pattern formation in granular AFM bits is primarily determined by the energy dissipation upon cooling, which results in motion and expelling of AFM domain walls of the bit. Our results provide a way towards the fabrication of single domain AFM-bit-patterned memory devices and the exploration of the interplay between AFM nanostructures and their geometric shape.

The role of pool scrubbing in attenuating radioactivity release after severe accidents has been explored extensively. It is known that scrubbing efficiency is largely determined by the hydrodynamic phenomenology in pools, which is still insufficiently understood. Aerosol gas forms large globules at the nozzle exit,
which subsequently break up into a swarm of stable bubbles, where the change of bubble size can reach more than two orders depending on the injection rate. Furthermore, with the increase of flow rates, the injection regime changes from globule to jet characterized by a continuous gas structure. The flow field in the pool can be divided into two zones, injection and rise (swarm), according to the gas-liquid interface morphology. In different zones, scrubbing is governed by different mechanisms such as inertial impact, diffusion, and gravity, whereby bubble rise velocity is one major influential parameter. So far, numerical analysis of pool scrubbing is routinely based on system codes, which rely on empirical correlations for the determination of hydrodynamic parameters as well as scrubbing zones. More recently, owing to the increasing availability of computational resources, knowledge is improved through three-dimensional computational fluid dynamics simulations. Nevertheless, morphology and regime change still present a challenge for both two-fluid and interface-tracking models. Because of the limitation of closures, the conventional two-fluid model (TFM) is generally effective for bubble size smaller than cell size while interface-tracking (capturing) methods demand dozens of cells per bubble size. Combining the two kinds of approaches into one simulation is not straightforward. The present work aims to present a hybrid multifield TFM with extensions for capturing the transfer between different morphologies and
for considering the effect of mesh resolution in momentum exchange. The developments are validated by simulating the complex hydrodynamic process in a pool-scrubbing column, which operates in the globule regime with an injection Weber number between 10^3 and 10^5. By comparison with experimental data, the results are shown to be promising, which provides a versatile framework for investigation of particle scrubbing in the future. The most attractive feature of the model is that compared to one-fluid interface-tracking models, it reliably predicts the bubble rise velocity. Furthermore, it is able to capture the lateral gas distribution without the need of applying a population balance model since most large bubbles are resolved.

Over the last decade chimeric antigen receptor (CAR) T cell immunotherapy demonstrated great success in hematological malignancies. On the downside, however, these therapies are also accompanied by various adverse events, such as cytokine release syndrome or on-target off-tumor effects. To overcome these hurdles, we have developed switchable adapter CAR systems, namely the UniCAR and RevCAR technology. T cells modified to express such adapter CARs can be not only directed against a certain tumor specific target but also reversibly switched ON and OFF allowing a steerable therapy. So far, adapter CAR T cells potently eradicated tumor cells of various entities both in vitro and in vivo. For an application in patients, adapter CAR T cells need to be produced according to GMP requirements. In that regard, the CliniMACS Prodigy® represents a powerful closed-system manufacturing instrument enabling an automated production process with reduced risk for contamination and hands-on time. Here, we present successful generation of adapter CAR T cells using a CliniMACS Prodigy® which yielded in high transduction rates and cell numbers. Moreover, CliniMACS Prodigy® produced adapter CAR T cells potently killed tumor cells in a steerable manner demonstrating their high potential for a clinical application.

Chimeric Antigen Receptor (CAR) T cells are effective at targeting tumor cells, particularly in hematological malignancies. A safer, switchable modular system called RevCAR has been developed to address dangerous side-effects. This system includes RevCAR T cells, which cannot bind to targets on their own, and a bispecific target module (RevTM). The functionality of this system depends on the presence of RevTM, which acts as a safety switch. Additionally, different RevTMs can be used with the same T cells to target various antigens, providing greater flexibility. To effectively treat solid tumors, however, it is necessary to overcome the immunosuppressive tumor microenvironment. To address this, new RevTMs were created to target immune checkpoint PD-L1, which cancer cells often upregulate to evade the immune system. Our research demonstrated that these new RevTMs enable RevCAR T cells to specifically target and kill a wide range of PD-L1-expressing cells in both monolayer and 3D models. The RevCAR T cells also released pro-inflammatory cytokines and expressed activation markers after co-culture. Furthermore, we validated an AND-gated targeting approach that simultaneously targets a tumor-associated antigen (TAA) and an immune checkpoint. These findings suggest a promising new strategy for applying the RevCAR platform to the treatment of solid tumors.

At submillimetric scales, a flexible fibre deforms spontaneously upon contact with a drop. This capillary-dominant mechanism of the flexible fibre, known as elasto-capillary deformation, is crucial for a wide range of applications such as textile flotation, microfolding of elastic structures, fabrication of stretchable microelectronics, development of portable medical devices, and stabilization of emulsions. While previous studies have explored the coiling behaviour of such fibres, particularly within rigid and flexible cavities, a comprehensive investigation into the dynamic evolution of fibre deformation upon droplet evaporation on a solid substrate remains lacking.

To address this gap, our study employs a Lagrangian beam model to discretize the fibre into a chain of beads interconnected by a virtual beam, enabling the simulation of stretching, bending, and twisting interactions. This model incorporates crucial factors such as viscous drag acting on individual beads and the capillary force driving deformation. Additionally, the contact interactions between adjacent beads are modelled using Euler-Bernoulli beam theory, while non-adjacent bead interactions are addressed through Hertzian contact theory. Our primary objective is to develop a numerical framework capable of accurately capturing the rapid dynamics of long fibres interacting with droplets, thus shedding light on fundamental mechanisms underlying this phenomenon.

The establishment of inhaled aerosols plays a significant role in risk assessment regarding air pollution and spreading of diseases. It is also of importance for evaluating lung deposition of particles and hence, the effectiveness of inhaled drug delivery systems. When it comes to air pollution or airborne diseases, there is a broad discussion whether ventilation by frequent window opening is sufficient for providing a sufficient amount of fresh air or if technical air purification devices based on e.g. HEPA filters are page better solutions for public spaces. Furthermore, there is another discussion ongoing, whether a well-guided laminar flow or a high degree of mixing within a room is more beneficial. The latter, on the one hand distributes the potentially virus-laden aerosols in the whole room, but on the other hand reduces the peak concentrations of these aerosols clouds by magnitudes.

The objective of this study is to answer to these queries by performing aerosol propagation experiments in order to estimate the potential aerosol inhalation of people in dynamic situations. To achieve this, an aerosol generator is used for aerosolizing a solution of water/MgCl2, which is collected in removible filters located in breathing masks used by the people during the experiment. The quantification of the inhaled aerosol is carried out by extracting the Mg from the mask and measuring it using inductively coupled plasma mass spectromestry technique (ICP-MS). Experiments will be performed in a demonstrator room under different flow conditions. The data from different scenarios will be processed in order to obtain a transference function that can relate the aerosol source with the aerosol receivers.

Heterostructure interfaces of two-dimensional (2D) materials enable the realization of advanced electronic functionalities at the nanoscale. The efficient computational ab initio modelling of these systems is, however, a challenge as it requires the proper lattice matching of the component 2D sheets with minimal strain. This often results in large structures with hundreds to thousands of atoms. Here, we utilize the newly developed hetbuilder tool to automate
the heterotructure cell construction based on coincidence lattice theory [1,2]. It is integrated with the AFLOW materials database and software [3,4] allowing for an efficient workflow for the structure generation from the bulk parent systems. We benchmark the approach by performing ab initio calculations on several different heterostructures of 2D materials and study their electronic properties.
[1] D. S. Koda et al., J. Phys. Chem. C 120, 10895 (2016).
[2] https://zenodo.org/record/4721346.
[3] M. Esters et al., Comput. Mater. Sci. 216, 111808 (2023).
[4] C. Oses et al., Comput. Mater. Sci. 217, 111889 (2023).

Background: Hypoxia remains a challenge for the therapeutic management of head and neck squamous cell carcinoma (HNSCC). The combination of radiotherapy with nimorazole has shown treatment benefit in HNSCC, but the precise underlying molecular mechanisms remain unclear. Purpose: To assess and to characterize the transcriptomic/epigenetic landscape of HNSCC tumor models showing differential therapeutic response to fractionated radiochemotherapy (RCTx) combined with nimorazole. Materials/methods: Bulk RNA-sequencing and DNA methylation experiments were conducted using untreated and treated HNSCC xenografts after 10 fractions of RCTx with and without nimorazole. These tumor models (FaDu, SAS, Cal33, SAT and UT-SCC-45) previously showed a heterogeneous response to RCTx with nimorazole. The prognostic impact of candidate genes was assessed using clinical and gene expression data from HNSCC patients treated with primary RCTx within the DKTK-ROG. Results: Nimorazole responder and non-responder tumor models showed no differences in hypoxia gene signatures However, non-responder models showed upregulation of metabolic pathways. From that, a subset of 15 differentially expressed genes stratified HNSCC patients into low and high-risk groups with distinct outcome. Conclusion: In the present study, we found that nimorazole non-responder models were characterized by upregulation of genes involved in Retinol metabolism and xenobiotic metabolic process pathways, which might contribute to identify mechanisms of resistance to nitroimidazole compounds and potentially expand the repertoire of therapeutic options to treat HNSCC.

I present an overview of current ab initio path integral Monte Carlo (PIMC) capabilities to simulate warm dense matter and related extreme states. In the first part, I introduce the PIMC method and summarize recent developments for the uniform electron gas. In the second part, I show how emerging PIMC simulations of real systems such as warm dense hydrogen and beryllium allow for novel ways to interpret x-ray Thomson scattering (XRTS) measurements. This is demonstrated for an experimental dataset for strongly compressed beryllium measured at the National Ignition Facility (NIF).

The shearing of a particle bed composed of two or more species results in spontaneous
segregation. This poses problems in many industries, where the mixing of granules and powders
is a common process and a homogeneous product is desired. In this work, the segregation
dynamics occurring in a horizontal rotating drum filled with two granular species that only
differ in density is investigated. In this system, radial segregation is relatively fast and occurs
over the course of a few drum rotations. State-of-the art techniques allow the study of
segregation dynamics at the end walls of a drum, as well as the observation of slow axial
dynamics and the steady state of radial mixing inside the drum bulk. They do not allow,
however, continuous observation of the transient radial mixing in the bulk. Using the ultrafast
X-ray computer tomography it is possible to take cross-sectional images through the opaque
granular systems at 1000 frames per second. The high-speed image sequences from intermediate
planes of the drum can reveal the segregation dynamics in the bulk. Here we present
experimental results from the transient state of radial mixing for a binary granular system with
density difference (density ratio 2.8) and equal size (4 mm) spherical beads in a half-filled drum.
Using a dimensionless mixing index (M), we compare the dynamics of radial mixing and
segregation in transverse planes in the bulk of the drum, captured with UFXCT, with the
dynamics from the circular end caps to highlight wall effects. We also compare two dynamic
models for radial mixing and consider the effect of flow on mixing dynamics. We find that
second-order dynamics fit better the data than the commonly used first-order, since it accounts
for the overshooting mixing dynamics occurring at higher drum speeds. We also find that,
compared to the end cap, the dense particle segregation core is larger in the bulk plane and the
overshooting in the mixing index is smaller, suggesting a correlation between mixing and flow
characteristics, such as the dynamic angle of repose. Our results, because of better describing
overmixing, are highly relevant to the pharmaceutical, food and cement industrie

The transient mixing dynamics of an initially segregated binary granular system in a half-filled rotating drum are investigated. The granular system consists of spherical beads having identical size. The density ratio between the two granular phases is 2.8. With its ability to scan three-dimensional opaque systems with a high frequency, the ultrafast X-ray computed tomography is used to capture the transient and steady-state segregation dynamics in the bulk. The segregation dynamics are also compared to those at the circular end-wall caps, which have been captured with a camera. The results show an axial migration of the denser particles towards the bulk and, more importantly, second-order overshooting dynamics in the radial mixing index, which tend to increase with the Froude number. The results will find application in industrial systems, where rapid mixing occurs. We also believe the presented data can serve as validation for future three-dimensional simulations focusing on the transient formation of segregation patterns in the bulk.

In this Letter, we demonstrate terahertz (THz) magnetic field detection in fused silica with sensitivity that can be easily controlled by sample tilting (for both amplitude and polarization). The proposed technique remains in the linear regime at magnetic fields exceeding 0.3 T (0.9 MV/cm of equivalent electric field) and allows the use of low-cost amorphous materials. Furthermore, the demonstrated effects should be present in a wide variety of materials used as substrates in different THz-pump laser–probe experiments and need to be considered in order to disentangle different contributions to the measured signals.

Liquid film flow is an important and safety relevant part of the thermo-hydraulics of nuclear reactors. In this work, we therefore demonstrate the visualization of condensate films in a slightly inclined tube at the thermal-hydraulic test facility COSMEA. That facility is used to investigate high-pressure steam condensation at conditions comparable to those in the emergency condenser of the KERENATM reactor. The facility is equipped with an X-ray imaging system to acquire raw X-ray radioscopic and tomographic projection data. Here, we give a detailed description of the data processing chain for the X-ray image data, which was acquired under harsh conditions e.g. with tube vibrations induced by the liquid flow and with tube displacement due to thermal expansion. Subsequently, we present an evaluation of the resulting reconstructed images with regard to the condensate liquid films.

X-ray radioscopy was used to measure the 2D projected dynamic void fraction in a zero/narrow gap alkaline water electrolyzer at a spatial resolution of 15 m, for narrow gap sizes up to 300 m and current densities up to 0.54 A/cm2. As expected, the void fraction in the bulk was found to increase along the cell height and with increasing current density. The void fraction measured in the gap region (the space between the diaphragm and the electrode and its holes) was always larger than in the bulk. It hardly depended on the gap size at current densities below 0.3 A/cm2. The lowest cell potential was measured for zero gap. No evidence of isolating gas pockets/films in the gaps was found. Liquid crossover and oxygen void fraction exceeding the hydrogen void fraction occurred for porous plate electrodes, but these phenomena were suppressed for perforated foil electrodes.

Bubbles play a crucial role in various industrial reactors and natural processes, garnering intense research interest, while the understanding of their deformation and interaction with surrounding liquid is still not enough. This study combines the Front Tracking (FT) method with a Proportional-Integral-Derivative (PID) controller to achieve precise bubble fixation, enabling an in-depth analysis of bubble dynamics and steady-state variations at moderate Reynolds number (Re), including shape, surface characteristics, drag forces, and surrounding flow fields under various liquid conditions. For the first time the form drag is separated from the skin one by means of direct numerical simulation. Results demonstrate good agreements with empirical equations from the literature for aspect ratios and drag coefficients, validating the effectiveness of the method in replicating bubble forces and deformations. As Re increases, high-velocity regions on the sides of the bubble exhibit accelerated velocities, and the low-velocity region at the rear gradually narrows. Bubble aspect ratio and sphericity vary significantly under different liquid densities, while viscosity notably affects the time required for bubble shape stabilization. The front surface area of a bubble remains consistent across various liquid conditions, while the projected area is more relevant for drag force calculations. Bubbles with larger aspect ratios show smaller projected areas and vice versa. Tangential and normal forces on the bubble surface vary with the circumferential angle, with the maximum near the front center and minimum near 90 degrees. The decreasing and increasing trend around the surface depend on fluid conditions. At moderate Re, form drag is predominant, with a ratio of approximately 7:3 between form and friction drag. Increasing the Re leads to an increase in the proportion of form drag, e.g. by increasing density or decreasing viscosity, but the former is found more effective, although the latter affects the total drag more significantly. It is interesting to notice that the proportion of form drag increases with the surface tension coefficient as well, even if it hardly changes the total drag. Finally, the surface force integration method is shown to be superior to the widely-used force balance method for calculating drag coefficients.

Deuterium insertion was used to tune the magnetic properties of Y_0.9Tb_0.1Fe₂ Laves phase towards an itinerant electron metamagnetic (IEM) behavior. The latter is highly sensitive to chemical changes and external parameters. The structural and magnetic properties of Y_0.9Tb_0.1Fe₂D_4.3 were investigated using various neutron powder diffraction experiments in addition to magnetic measurements under steady and pulsed high magnetic fields up to 60 T. The deuteride crystallizes in a monoclinic structure (P_c space group) with 4.3 D atoms located in 18 tetrahedral interstitial sites. At zero field, it undergoes a ferrimagnetic-antiferromagnetic (FiM-AFM) transition at T_M0 = 90 K, accompanied by an anisotropic magnetostriction and a negative cell volume expansion of 0.6 %. A second AFM-PM transition is observed at 146 K. Under pulsed magnetic field at 4.2 K, the deuteride displays a multistep magnetic behavior from ferrimagnetic to a ferromagnetic state, which can be attributed to a stepwise rotation of the Tb moments. The ZFC-FC magnetization curves at low fields exhibit an irreversibility below 90 K, followed by a sharp decrease in magnetization at the FM-AFM transition. Between 90 K and 130 K, the magnetization curves display an IEM behavior, with the transition field increasing linearly with temperature.

In spatially inverted systems, the complex entanglement of Dzyaloshinskii-Moriya interaction (DMI) and other magnetic anisotropies, mediated by spin-orbit coupling (SOC), influences the emergence and dynamics of the chiral spin textures such as skyrmion. The competing and unified effect of these anisotropies - which is expected to amplify the skyrmionics response in the quantum transport phenomena - is not yet known. Here, we investigate this template and engineer the topological Hall effect (THE) arising from chiral spin texture in a range of La_0.7Sr_0.3MnO₃/CaIrO₃ superlattices. The strength of SOC and interfacial DMI are controlled via the architectural design and charge transfer across the interface. All the superlattices display anomalous Hall effect, accompanied by the hump like feature. In (L₃I_y)₄ (y = 4, 6, and 8) superlattices, the humplike feature that is deemed as the THE is intrinsic in nature and stems from the chiral spin texture. For the intermediate strength of SOC, unique eightfold anisotropic magnetoresistance oscillations manifest owing to the modulation of the magnetic easy axis in the presence of competing anisotropies. For this superlattice, THE shows remarkable enhancement of the order such that it takes complete precedence over anomalous contribution. The thicker superlattice with higher fraction of charge transfer augments ferromagnetic interactions, and the artificial THE appears as a consequence of a dual-channel anomalous Hall effect. This manipulation of the THE is intricately connected to the concurrent presence of magnetic anisotropies, altering the dynamics of chiral spin texture. These findings expand the understanding of the corroborative contributions of competing anisotropies and yield a comprehensive control of chiral properties - a dimension for the utility in next-generation spintronics technologies.

Change detection, an essential application for high-resolution remote sensing (RS) images, aims to monitor and analyze changes in the land surface over time. Due to the rapid increase in the quantity of high-resolution RS data and the complexity of texture features, several quantitative deep learning-based methods have been proposed. These methods outperform traditional change detection (CD) methods by extracting deep features and combining spatial–temporal information. However, reasonable explanations for how deep features improve detection performance are still lacking. In our investigations, we found that modern Hopfield network (MHN) layers significantly enhance semantic understanding. In this article, we propose a deep supervision and feature retrieval network (Dsfer-Net) for bitemporal CD. Specifically, the highly representative deep features of bitemporal images are jointly extracted through a fully convolutional Siamese network. Based on the sequential geographical information of the bitemporal images, we designed a feature retrieval module to extract difference features and leverage discriminative information in a deeply supervised manner. In addition, we observed that the deeply supervised feature retrieval (DSFR) module provides explainable evidence of the semantic understanding of the proposed network in its deep layers. Finally, our end-to-end network establishes a novel framework by aggregating retrieved features and feature pairs from different layers. Experiments conducted on three public datasets (LEVIR-CD, WHU-CD, and CDD) confirm the superiority of the proposed Dsfer-Net over other state-of-the-art methods. Compared to the best-performing DSAMNet, Dsfer-Net demonstrates significant improvements, with $F1$ scores increasing by 4.7%, 5.9%, and 2.3%. Furthermore, compared to our previous FrNet, Dsfer-Net also achieves noteworthy enhancements, with $F1$ scores increasing by 2.0%, 1.4%, and 4.5% on three datasets. The code will be available online ( https://github.com/ShizhenChang/Dsfer-Net ).

Low temperature fuel cells (LTFCs) present
promising technical solutions for enabling broad applications of
green Hydrogen energy. However, the efficiencies and
durability of LTFCs are limited by the dynamic water evolution
and transport, especially when they are operated at high current
densities. Developing water monitoring techniques therefore
presents a crucial strategy for optimizing the designs and
operating schemes of LTFCs, and eventually overcoming such
water management issues. This work explores the possibilities of
using ultrasonic techniques to investigate the water contents in
the gas diffusion layers (GDL), as one of the key components of
the membrane electrode assembly in LTFCs. For this purpose,
we numerically and experimentally investigated the
propagation of longitudinal mode ultrasonic waves in GDLs at
different water saturation levels. The numerical simulations and
experimental investigations both reveal the changes in the speed
of sound and acoustic attenuation coefficient with respect to the
water saturation level of the GDL. These physical effects open
new horizons for developing simplified and cost-effective
ultrasound based water monitoring systems towards
applications in operating LTFCs.

Multimodal image fusion has recently garnered increasing interest in the field of remote sensing. By leveraging the complementary information in different modalities, the fused results may be more favorable in characterizing objects of interest, thereby increasing the chance of a more comprehensive and accurate perception of the scene. Unfortunately, most existing fusion methods tend to extract modality-specific features independently without considering intermodal alignment and complementarity, leading to a suboptimal fusion process. To address this issue, we propose a novel interactive generative adversarial network (IG-GAN), for the task of multimodal image fusion. IG-GAN comprises guided dual streams tailored for enhanced learning of details and content, as well as cross-modal consistency. Specifically, a details-guided interactive running-in module (GIR1) and a content-guided interactive running-in module (GIR2) are developed, with the stronger modality serving as guidance for detail richness or content integrity, and the weaker one assisting. To fully integrate multigranularity features from dual-modality, a hierarchical fusion and reconstruction branch is established. Specifically, a shallow interactive fusion (SIF) module followed by a multilevel interactive fusion (MIF) module is designed to aggregate multilevel local and long-range features. Concerning feature decoding and fused image generation, a high-level interactive fusion and reconstruction module (HRM) is further developed. In addition, to empower the fusion network to generate fused images with complete content, sharp edges, and high fidelity without supervision, a loss function facilitating the mutual game between the generator and two discriminators is also formulated. Comparative experiments with 14 state-of-the-art methods are conducted on three datasets. Qualitative and quantitative results indicate that IG-GAN exhibits obvious superiority in terms of both visual effect and quantitative metrics. Moreover, experiments on two RGB-IR object detection datasets are also conducted, which demonstrate that IG-GAN can enhance the accuracy of object detection by integrating complementary information from different modalities. The code will be available at https://github.com/flower6top .

The Remote Sensing (RS) field continuously grapples with the challenge of transforming satellite data into actionable information. This ongoing issue results in an ever-growing accumulation of unlabeled data, complicating interpretation efforts. The situation becomes even more challenging when satellite data must be used immediately to identify the effects of a natural hazard. Self-supervised learning (SSL) offers a promising approach for learning image representations without labeled data. Once trained, an SSL model can address various tasks with significantly reduced requirements for labeled data. Despite advancements in SSL models, particularly those using contrastive learning methods like MoCo, SimCLR, and SwAV, their potential remains largely unexplored in the context of instance segmentation and semantic segmentation of satellite imagery. This study integrates SwAV within an auto-encoder framework to detect landslides using deca-metric resolution multi-spectral images from the globally-distributed large-scale landslide4sense (L4S) 2022 benchmark dataset, employing only 1% and 10% of the labeled data. Our proposed SSL auto-encoder model features two modules: SwAV, which assigns features to prototype vectors to generate encoder codes, and ResNets, serving as the decoder for the downstream task. With just 1% of labeled data, our SSL model performs comparably to ten state-of-the-art deep learning segmentation models that utilize 100% of the labeled data in a fully supervised manner. With 10% of labeled data, our SSL model outperforms all ten fully supervised counterparts trained with 100% of the labeled data.

In groundbreaking experiments by Geim's group, layered materials such as h-BN and MoS2 have demonstrated a remarkable ability to let hydrogen isotopes pass between their layers.[1] Further theoretical analysis uncovered that it is hydrogen atoms, rather than ions, that travel between these layers, aided by shearing modes within the material.[2] In our earlier research, we revealed that hydrogen transport is significantly affected by stacking configurations and stoichiometry, leading to variations in diffusivity.[3] When it comes to lighter atoms like hydrogen, quantum effects become critical. Yet, previous theoretical studies relying on well-tempered metadynamics (WTMetaD) used a classical approach under the BornOppenheimer approximation.
In this study, we investigate the nuclear component quantum mechanically using Path Integral Molecular Dynamics (PIMD). This combination with metadynamics improves with quantum corrections to the classical model. Although PIMD requires significantly more computational power than classical molecular dynamics, machine-learning potentials (MLPs) offer a solution, improving future calculations.
Here, we first explore how diffusivity changes in classical WTMetaD, both with and without MLPs, using models trained on our previous results[3] and PIMD trajectories. Next, by employing MLPs within PIMD, we directly compare diffusivity to its classical counterpart, understanding the quantum nature of hydrogen transport within layers of 2D materials.

Storage technologies will play a critical role in the medium-term future for the massive integration of renewable sources. Among the most promising storage technologies are Carnot batteries, which are based on the electrothermal conversion of renewable electricity into heat in the charging stage and converting the stored thermal energy into electricity in the discharge. Their optimum operating range depends on the components integrated into the system and the working fluid. This work analyses the partial load operation of an electrothermal and geological energy storage system based on transcritical CO2 cycles. It is based on the concept under study in the CEEGS Horizon Europe project. CEEGS, a CO2-based electrothermal energy and geological storage system, is a cross-sectoral technology for energy transition, with a renewable energy storage system based on the transcritical CO2 cycle, CO2 storage in geological formations and geothermal heat extraction. It is a highly efficient, cost-effective, and scalable (small-to-large-scale) concept for large-capacity renewable energy storage.
This work analyses the partial load operation of a CEEGS system integrated into a MW PV facility under different scenarios. It is a preliminary approach for analysing the impact of main operating conditions on the main components of the systems, turbomachinery and heat exchangers. In this preliminary approach, the analysis is focused on the off-design operation in the charging stage. The analyses are extended throughout the year, collecting the variability in efficiency throughout the integration. Charging efficiency, defined by the COP, can vary up to 32% for specific fixed conditions throughout one day. This effect can be more pronounced in months with higher daily variations. Different systems and operation modes have been considered for the particular application. A first operation mode is based on selecting the optimal design flow rate. It increases the average annual COP by up to 7%. The evolution of this mode consists of using several parallel compressors with different design configurations that are adequate for covering the charging profiles. It allows the system to evolve to maximum performance conditions for the entire working range, increasing COP by around 13% compared to the previous single mode. It extends the daily operation of the system. In the specific case of the PV-CEEGS system located in Seville, it is increased by around 1.5 hours on average. A third mode of operation is defined as an intermediate solution between both. It is based on parallel equal compressors. It increases efficiency by 11% compared to the single-mode operation. The preliminary results for the particular PV-CEEGS case analysed show the relevance of an adequate design and operation definition for the integrated compression system under off-design conditions and its impact on the global system performance.

Electrothermal energy storage is a promising technology in transitioning towards an energy system with high penetration of renewable energy. In recent years, the integration of this energy storage system with geological carbon dioxide storage has been introduced. The system consists of a reversible heat pump formed by transcritical CO2 cycles with thermal storage at two temperature levels, enabling the simultaneous operation of geological CO2 storage and the storage/production of renewable electrical energy. This work focuses on studying high and low-temperature thermal energy storage. Step heating on the high-temperature side allows for better integration of the supercritical and subcritical temperature profiles of the CO2 and the thermal storage fluid. Thermal storage at different temperature levels provides a higher turbine inlet temperature, improving the efficiency of the power production cycle and increasing heating applications such as district heating or domestic hot water. The round-trip efficiency is in the 51-59% range, taking into account four high-temperature tanks. It presents a thermal demand coverage range of about 20-150 ºC, with temperature increases of approximately 30 ºC. The phase change temperature shift on the low-temperature side directly impacts electric power production and enables new cooling applications. The system's round-trip efficiency increases as the LT-TES phase change temperature decreases, reaching a range of 56.6-67.7 % at -40 ºC.

The increased atmospheric carbon dioxide concentrations have led to a growing interest in finding effective solutions to reduce greenhouse gas emissions. Implementing on-site carbon capture systems in industries is emerging as a crucial strategy to address climate change, as it brings significant benefits by reducing emissions at source. Integrating carbon capture systems with energy storage represents an innovative step towards maximising the efficiency and sustainability of the whole system. The captured CO2 becomes a valuable feedstock for the novel CO2-based electrothermal and geological energy storage (CEEGS) system. It uses transcritical CO2 cycles for energy storage, and a part of the CO2 is geologically stored permanently. It is a renewable energy storage system that allows for decreasing the global dependence on fossil fuels and offers a scalable solution for managing the inherent intermittency of renewable energy sources. This work studies the integration of CO2 capture using a calcium looping (CaL) process powered by concentrating solar power and the integration of the technology with the CEEGS systems. Renewables are used in carbon capture and energy storage. The results show the interest and potential of the combination of technologies for renewables integration and industry decarbonisation.