Helmholtz-Zentrum Berlin

Electron beam water treatment (EBWT) is a promising approach for remediating water contaminated with per- and polyfluoroalkyl substances (PFAS). In this study, we assess the feasibility of using a compact, high-average-power superconducting radio-frequency (SRF) photoinjector as a source for delivering the electron beam parameters required to initiate PFAS degradation. Our goals are twofold: first, to determine whether such a system can achieve the necessary dose and dose rate through sufficient beam energy and power; and second, to establish an experimental platform for investigating how different beam conditions affect degradation pathways. We envision a compact and mobile SRF-based accelerator that can be deployed at contamination hotspots - such as the former Berlin airport Tegel - offering significantly faster and potentially more effective treatment than conventional remediation methods. Based on theoretical analysis and computational modeling, we identify the SRF photoinjector at Helmholtz-Zentrum Berlin (HZB) as a suitable R&D platform. To support experimental validation, we developed a proof-of-concept in-air beamline optimized for balancing dose deposition and thermal management. This setup will enable the systematic study of key operational parameters, including dose rate, energy deposition, and thermal stability, under controlled beam conditions.

Superconducting radio frequency cavities with a high quality factor enable energy-efficient accelerator operation but are very sensitive to mechanical disturbances that detune their resonance. Accurate detuning estimation is therefore essential for efficient resonance control and stable beam conditions. This paper introduces Kalman-Inspired Neural Decomposition (KIND), a data-driven estimator that fuses a Dynamic Mode Decomposition model for stationary modal behavior with a Transformer-based predictor for transient dynamics. KIND further outputs learned uncertainty signals that indicate regime changes, enabling anomaly detection. Using operational cavity data, we compare KIND with a classical Kalman filtering baseline and discuss its potential as a foundation for future uncertainty-aware, forecast-based control.

This study investigates size-controlled, quantum-confined CdSe/ZnS core–shell quantum dots using core-hole clock spectroscopy in combination with post-collision interaction (PCI) line shape analysis, providing insights into local charge transfer dynamics and internal continuum states. We observe an acceleration of charge transfer times by almost one order of magnitude in thin-shell quantum dots, comprising only one or three double layers of ZnS, before reaching a size-independent limit. This size-dependence is governed by the existence of a faster charge transfer channel toward the CdSe core, only accessible for the inner-most shell layers, rather than a quantum confinement effect. By extending the traditional PCI model from free-electron systems to bound-state continua, we further establish a framework for interpreting line shape asymmetries and peak shifts that are frequently observed but often overlooked in resonant Auger measurements. We show that the strongly enhanced PCI in the samples with one or three double layers can be attributed to reduced collective electronic screening. This comprehensive experimental approach enables the simultaneous observation of collective electronic properties and atom-specific dynamics within in a single measurement under identical sample conditions, an advance particularly valuable for complex, sensitive materials.

Oleyl-capped nanoparticles have been used in nonpolar dispersions and can form ordered assemblies, for which an understanding of their interactions from a theoretical perspective is relevant. Long-range comprehensive molecular dynamics runs (1000 ns) are performed on oleyl-capped gold nanoclusters in different environments: hexane as a nonpolar solvent, and ethanol and pentanol as polar solvents. The molecular dynamics results in ethanol medium demonstrate that oleyl-capped nanoclusters tend to form attractive interactions with themselves via hydrocarbon interdigitation of their oleyl ligands, which leads to their aggregation. On the contrary, the attractive interactions between these nanoclusters are compensated by the interactions with hexane molecules, so that the nanoclusters keep separated from each other, leading to stable dispersions. The behavior of pentanol with the oleyl-capped nanoclusters indicates presumably more similarities to hexane, despite of being a polar solvent. These three simulation cases provide an insightful overview about the stabilization effects of oleyl-capped nanoparticles in organic solvents.

This study presents a comprehensive computational framework for reproducing the full X‐ray absorption fine structure (XAFS) through quantum‐chemical simulations. The near‐edge region is accurately captured using an efficient implementation of time‐dependent density‐functional perturbation theory applied to core excitations, while ab initio molecular dynamics provides essential sampling of core‐excitation energies and interatomic distance distributions for interpreting extended X‐ray absorption fine structure (EXAFS) features. Owing to the efficiency of the approach, the total spectrum can be decomposed into contributions from bulk, defective, and surface environments, which commonly coexist in experimental systems. The methodology is demonstrated for sodium at the Na K‐edge in NaCl, where the predicted spectra show good agreement with experimental measurements on thin‐film samples. This strategy offers a practical route to generating chemically specific XAFS cross‐section data for elements and species that remain challenging to characterize experimentally, thereby enabling deeper insights into materials of technological importance.