TY - JOUR A1 - Fayis Kalady, Mohammed A1 - Schultz, Johannes A1 - Weinel, Kristina A1 - Wolf, Daniel A1 - Lubk, Axel T1 - Geometry-dependent localization of surface plasmons on random gold nanoparticle assemblies N2 - Assemblies of plasmonic nanoparticles (NPs) support hybridized modes of localized surface plasmons (LSPs), which delocalize in geometrically well-ordered arrangements. Here, the hybridization behavior of LSPs in geometrically completely disordered two-dimensional arrangements of Au NPs fabricated by an e-beam synthesis method is studied. Employing electron energy loss spectroscopy in a scanning transmission electron microscope and numerical simulations, the disorder-driven spatial and spectral localization of the coupled LSP modes that depends on the NP thickness is revealed. Below a NP thickness of 0.4 nm, localization increases toward higher hybridized LSP mode energies. In comparison, above 10 nm thickness, a decrease of localization toward higher mode energies is observed. In the intermediate thickness regime, a transition of the energy dependence of the localization between the two limiting cases, exhibiting a mode energy with minimal localization, is observed. It is shown that this behavior is mainly driven by the energy and thickness dependence of the polarizability of the individual NPs. KW - Gold Nanoparticles KW - Surface plasmons KW - Electron enerdy loss spectroscopy (EELS) KW - scanning transmission electron microscopy PY - 2025 UR - https://nbn-resolving.org/urn:nbn:de:kobv:b43-647230 DO - https://doi.org/10.1103/44nk-6bp2 SN - 2643-1564 VL - 7 IS - 043053 EP - 4 PB - American Physical Society AN - OPUS4-64723 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - JOUR A1 - Homann, Christian A1 - Peeters, Régis A1 - Mirmajidi, Hana A1 - Berg, Jessica A1 - Fay, Michael A1 - Rodrigues, Lucas Carvalho Veloso A1 - Radicchi, Eros A1 - Jain, Akhil A1 - Speghini, Adolfo A1 - Hemmer, Eva T1 - Rapid microwave-assisted synthesis of morphology-controlled luminescent lanthanide-doped Gd2O2S nanostructures N2 - Gadolinium oxysulfide (Gd2O2S) is an attractive material of demonstrated suitability for a variety of imaging applications, leveraging its magnetic, scintillating, and luminescent properties, particularly when doped with optically active lanthanide ions (Ln3+). For many of these applications, control over size and morphology at the nanoscale is crucial. This study demonstrates the rapid microwave-assisted Synthesis of colloidal Ln2O2S (Ln = Gd and dopants Yb, Er, Tb) nanostructures in as little as 20 min. Structural characterization using X-ray diffraction analysis (XRD), Raman spectroscopy, as well as Transmission electron microscopy (TEM), including elemental mapping via energy dispersive X-ray spectroscopy (EDS), unveiled the key role of elemental sulphur (S8) in the reaction mixtures for materials growth. By systematically varying the Ln-to-S ratio from 1 : 0.5 to 1 : 15, controlled morphologies ranging from triangular nanoplatelets to berry- and flower-like shapes were achieved. Doping with Er3+/Yb3+ endowed the nano-triangles with upconverting and near-infrared emitting properties. Tb3+-doped Gd2O2S exhibited the characteristic green Tb3+ emission under UV excitation, while also showing X-ray excited optical luminescence (XEOL), rendering the material interesting as a potential nano-scintillator. KW - Upconversion KW - Microwave-assisted synthesis KW - Synthesis KW - Fluorescence KW - Nano KW - Particle KW - NIR KW - XRD KW - X-ray fluoressence KW - Morphology control KW - Raman PY - 2025 UR - https://nbn-resolving.org/urn:nbn:de:kobv:b43-647907 DO - https://doi.org/10.1039/D5TC01646K SN - 2050-7526 VL - 13 IS - 35 SP - 18492 EP - 18507 PB - Royal Society of Chemistry (RSC) AN - OPUS4-64790 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - JOUR A1 - Adamski, Paweł A1 - Zgrzebnicki, Michał A1 - Albrecht, Aleksander A1 - Jurkowski, Artur A1 - Wojciechowska, Agnieszka A1 - Ekiert, Ewa A1 - Sielicki, Krzysztof A1 - Mijowska, Ewa A1 - Smales, Glen J. A1 - Maximenko, Alexey A1 - Moszyński, Dariusz T1 - Ammonia synthesis over γ-Al2O3 supported Co-Mo catalysts N2 - Novel ammonia synthesis catalysts are sought due to energetic transformation and increasing environmental consciousness. Materials containing cobalt and molybdenum are showing state-of-art activities in ammonia synthesis. The application of γ-alumina support was proposed to enhance the properties of Co-Mo nanoparticles. The wet impregnation of the support was conducted under reduced pressure. The active catalysts were obtained by ammonolysis of precursors. The chemical and phase composition, as well as morphology, porosity, and surface composition of precursors and catalysts, were characterized. The Co-Mo nanoparticles phase composition as well as their size and dispersion were determined using X-ray absorption spectroscopy utilizing synchrotron radiation, electron microscopy, and X-ray scattering. The catalytic activity was tested in the ammonia synthesis process under atmospheric pressure. The activity and stability of the supported catalysts were compared with unsupported cobalt molybdenum nitride Co3Mo3N, revealing the superiority of the present approach. KW - Ammonia synthesis KW - Supported catalyst KW - Cobalt molybdenum nitrides KW - Scattering KW - X-ray scattering KW - Gamma-alumina KW - Stability PY - 2025 DO - https://doi.org/10.1016/j.mcat.2025.114907 SN - 2468-8231 VL - 575 SP - 1 EP - 9 PB - Elsevier B.V. AN - OPUS4-64827 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - JOUR A1 - Voss, Heike A1 - Zahedi-Azad, Setareh A1 - Ernst, Owen C. A1 - Lucaßen, Jan A1 - Mann, Guido A1 - Bonse, Jörn A1 - Boeck, Torsten A1 - Martin, Jens A1 - Schmid, Martina A1 - Krüger, Jörg T1 - Chemical vapor deposition of indium precursors for solar microabsorbers using continuous laser radiation BT - A, Materials science & processing N2 - Localized deposition of indium on an amorphous glass surface covered with a thin molybdenum layer is demonstrated utilizing laser-assisted chemical vapor deposition. A continuous-wave laser causes a temperature rise on the molybdenum layer resulting in the selective aggregation of liquid and ultimately crystalline structures of indium. The formation sites of the indium are determined by the decomposition of gaseous trimethylindium. The deposited indium islands can serve as precursors and could be further processed into compound semiconductors like CuInSe2 for micro-concentrator solar cells. The experimental investigations were supported by theoretical simulations of the laser heating process to calculate the local temperature distribution on the surface of the molybdenum-covered glass substrate. KW - Laser-assisted Chemical Vapor Deposition KW - CW Laser KW - Indium Islands KW - Micro-concentrator Solar Cell PY - 2025 UR - https://nbn-resolving.org/urn:nbn:de:kobv:b43-641069 DO - https://doi.org/10.1007/s00339-025-08895-z SN - 0947-8396 VL - 131 SP - 1 EP - 10 PB - Springer CY - Berlin ; Heidelberg [u.a.] AN - OPUS4-64106 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - JOUR A1 - Xu, Alan A1 - Moschetti, Michael A1 - Miskovic, David A1 - Wei, Tao A1 - Ionescu, Mihail A1 - Wang, Zhiyang A1 - Palmer, Tim A1 - Bhattacharyya, Dhriti A1 - He, Peidong A1 - Li, Xiaopeng A1 - Gludovatz, Bernd A1 - Ferry, Michael T1 - Improved irradiation resistance of a low activation refractory medium entropy alloy, VCrFeW0.2, for fusion applications demonstrated by micro-tensile testing N2 - An, as cast, VCrFeW0.2 refractory medium entropy alloy (RMEA) was designed for fusion reactor divertor applications, focusing on reduced cost, low activation and compositional stability (low transmutation rates). The as-cast alloy was irradiated to a fluence of 5.6 × 10^17 ions/cm^2 at room temperature with 5 MeV helium ions whose energy have been uniformly attenuated to 0.4 MeV and 5 MeV via energy degradation device prior to sample irradiation. Pre and post irradiation, its mechanical properties were evaluated micro-tensile testing. Prior to irradiation, the VCrFeW0.2 alloy demonstrated good strength and ductility, with a yield strength of 1464 MPa and strain to UTS (\sigma_UTS) of 4.6 %, maintaining comparable strength to pure tungsten (1403 MPa) but with greater strain to UTS (1.3 %). Post irradiation, the VCrFeW0.2 alloy exhibited remarkable damage resistance; its strength increased by only ∼160 MPa, and it retained strain to UTS with a \sigma_UTS of 2.9 %. It performed better than pure tungsten tested under identical irradiation conditions where there was ∼1800 MPa increase in yield strength and a complete loss of plasticity. The micro-tensile results were supported by nanoindentation tests and Vickers hardness testing was also undertaken to show the yield strength values are representative of macro scale, bulk behavior. TEM and comparison with existing literature on RMEA/RHEA are presented here to understand the reason for difference in performance between VCrFeW0.2 alloy and pure tungsten. KW - Refractory medium entropy alloys KW - Fusion reactor materials KW - Irradiation resistance KW - Micro-tensile testing KW - Helium ion damage PY - 2025 UR - https://nbn-resolving.org/urn:nbn:de:kobv:b43-645322 DO - https://doi.org/10.1016/j.ijrmhm.2025.107481 SN - 0263-4368 VL - 134 SP - 1 EP - 16 PB - Elsevier Ltd. CY - Netherlands AN - OPUS4-64532 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - George, Janine T1 - Robust data generation, heuristics and machine learning for designing sustainable materials N2 - Despite advances in computational materials design, simulating large systems—such as defects, interfaces, or amorphous states—with quantum-chemical accuracy remains a major challenge.[1] Machine learning (ML) methods are emerging as powerful tools to overcome these limitations, enabling scalable and accurate modeling beyond traditional quantum-chemical approaches.[2] They also open new avenues for discovering non-toxic, earth-abundant alternatives to existing materials and can be combined with self-driving labs. [3] There are nowadays robust data generation strategies that underpin the development and benchmarking of ML models. [4,5]atomate2 I will focus on such strategies for quantum-chemical bonding analysis and ML interatomic potentials in my talk. Quantum-chemical bonding descriptors can be effectively used in ML models to predict phononic properties. [6] ML interatomic potentials offer a powerful approach for predicting energies, forces, and stresses—but their performance hinges on high-quality training data. Our automated framework, autoplex, enables diverse and scalable training workflows, from random structure searches for general-purpose models to phonon-aware pipelines for high-accuracy predictions.[7] While quantum chemistry excels in many domains, properties like magnetism and synthesizability remain elusive. Here, heuristics or leveraging experimental data for ML offer promising alternatives.[8,9] T2 - Advanced Materials Safety 2025 CY - Dresden, Germany DA - 04.11.2025 KW - Nano Particles KW - Machine Learning KW - Automation KW - Materials Design KW - Sustainability KW - Material Safety PY - 2025 AN - OPUS4-64599 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Hörmann, Anja Franziska T1 - extending the MOUSE in spirit: lifecycle of a GIXS experiment N2 - We present the new grazing incidence mode at the MOUSE, which adapts and extends the MOUSE methodology developed for transmission X-ray scattering (Smales and Pauw, 2021). Our methodology begins and ends in discussion with our users and embraces automation for reproducible experiments including sample organisation, instrument configuration, documentation and data processing. This poster presents methodological innovations and challenges. T2 - GISAXS 2025 CY - Hamburg, Germany DA - 27.10.2025 KW - Grazing incidence KW - X-ray scattering KW - Experimental methodology PY - 2025 AN - OPUS4-64694 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - JOUR A1 - Fischer, Tim A1 - Huber, Norbert T1 - Designing microcompression experiments for nanoporous metals via computational plasticity N2 - Micropillar compression testing is essential for understanding bulk metal plasticity at small scales and has emerged as a key technique for evaluating nanoporous metals like nanoporous gold (NPG). To support experimental design, we present a computational plasticity study on single crystal NPG micropillars, systematically examining four extrinsic factors: pillar height-to-diameter ratio, taper angle, friction coefficient, and misalignment angle. The study reveals that NPG exhibits similar trends to its bulk counterpart but is less prone to post-yield buckling in unstable crystal orientations. For optimal NPG pillar stability, an aspect ratio of is recommended and a moderate taper angle to prevent artificial stiffening and yielding. Even minimal friction enhances stability, while buckling is mainly governed by misalignment, requiring to also avoid underestimating the elastic modulus. KW - Nanoporous gold KW - Microcompression KW - Plasticity KW - Finite element method KW - Micromechanics PY - 2025 UR - https://nbn-resolving.org/urn:nbn:de:kobv:b43-645317 DO - https://doi.org/10.1016/j.matdes.2025.114550 SN - 0264-1275 VL - 258 SP - 1 EP - 9 PB - Elsevier Ltd. AN - OPUS4-64531 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Huber, Norbert T1 - Perspectives and pitfalls in modeling of structure-property relationships using machine learning N2 - Machine learning (ML) has been increasingly utilized to support microstructure characterization and predict mechanical properties. A successful ML model typically requires a comprehensive understanding of existing knowledge, expertise in translating this knowledge into meaningful input features, an effective ML architecture, and robust validation of the trained model. Despite the rapid growth in publications incorporating ML methods in recent years, there is limited literature specifically addressing nanoporous metals. The talk will give an overview on perspectives and pitfalls in modeling of structureproperty relationships using machine learning with focus on various challenges that arise from the specific nature of nanoporous metals including randomness of microstructure, image segmentation, lack of tomography data, feature engineering for property prediction, and implications for plasticity including anisotropic flow and arbitrary multiaxial loading on the lower scale of hierarchy. An outlook will be given on the perspectives of establishing a culture of open data, specifically towards curated data sets needed for training and validation of ML models. Potential use cases are the comparison of data from different sources, mining of more general relationships, and validation of models trained with computer generated data using experimental data. T2 - 5th International Symposium on Nanoporous Materials by Alloy Corrosion CY - Sendai, Japan DA - 06.10.2025 KW - Nanoporous metals KW - Machine learning KW - Structure-properties relationship KW - Materials design PY - 2025 AN - OPUS4-64536 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - JOUR A1 - Li, Yong A1 - Hu, Kaixiong A1 - Lilleodden, Erica T. A1 - Huber, Norbert T1 - Datasets for structural and mechanical properties of nanoporous networks from FIB reconstruction N2 - This dataset paper presents a comprehensive archive of 3D tomographic reconstruction image files, volume mesh files for finite element simulations, and tabulated structural and mechanical properties data of nanoporous gold structures. The base material is nanoporous gold, fabricated using a dealloying process, with a solid fraction of approximately 0.30. The NPG samples with ligament sizes ranging from 20 nm to 400 nm were prepared by dealloying and by controlling the thermal annealing process. The original data consist of tomographic TIFF files acquired through Focused Ion Beam/Scanning Electron Microscopy (FIB/SEM) 3D reconstruction, as detailed in Philosophical Magazine 2016 96 (32-34), 3322-3335. At each ligament size, six sets of 3D tomographic images were obtained from different regions of the same sample to ensure representative data. New simulations and analyses were conducted based on the 3D image data. The resulting structural and mechanical property data of nanoporous gold are reported for the first time in this dataset paper. Volume meshing of the 3D reconstructed data was performed using Simpleware software. Structural parameters, including surface area, solid volume, and solid volume fraction of the nanoporous network, were extracted from the meshed volumes. Structural connectivity was assessed from the 3D microstructures. The meshed volumes were then used as input for finite element simulations performed in Abaqus to evaluate mechanical responses under uniaxial compression along all three principal axes respectively. From the resulting stress–strain curves, the Young’s modulus and yield strength of each structure were determined. Both elastic and plastic Poisson’s ratios were analyzed from true strain increments. This dataset includes the 3D tomographic images, corresponding volume mesh files, mechanical behavior data and tables summarizing the structural and mechanical properties. The archived data serve as a database for nanoporous network materials and can be reused for numerical simulations, additive manufacturing, and machine learning applications within the materials science community. All files are openly accessible via the TORE repository at https://doi.org/10.15480/882.15230 KW - Nanoporous gold KW - Dealloying KW - FIB/SEM tomography KW - Finite element KW - Volume mesh KW - Young’s modulus KW - Yield stress KW - Poisson’s ratio PY - 2025 UR - https://nbn-resolving.org/urn:nbn:de:kobv:b43-645330 DO - https://doi.org/10.1016/j.dib.2025.112152 SN - 2352-3409 VL - 63 SP - 1 EP - 14 PB - Elsevier Inc. AN - OPUS4-64533 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER -