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 - CONF A1 - Alasonati, E A1 - Bartczak, D A1 - Altmann, Korinna A1 - Giovannozzi, A T1 - Towards Standardised Micro and Nanoplastics Analysis via Interlaboratory Comparisons: First Outlook of the VAMAS TWA 45 P3 Project N2 - This talk is part of the stakeholder workshop of the PlasticTrace project held in September 2025 in Oslo. The presentation shows first results of the VAMAS ILC on nanoplastics. PP nanoparticles were given to the participants. These were asked to measure the mass or particle number or size of the PP nanoplastics. Various techniques such as DLS, FFF, Py-GC/MS, TED-GC/MS, PTA were used. T2 - Stakeholder Workshop PlasticsTrace CY - Online meeting DA - 09.09.2025 KW - Nanoplastics KW - ILC KW - DLS KW - Polypropylene PY - 2025 AN - OPUS4-64714 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Altmann, Korinna T1 - Production of reference materials using a quality by design approach N2 - Accurate analysis of microplastics is based on validated methods and the use of standardized protocols. Therefore, reference materials are essential to determine recovery rates and optimise the existing workflows. The reference materials should mimic the reality in terms of particle properties and concentration and are intended for a special use. The Quality-by-Design approach helps to select the users need and defines a target product profile with mandatory and desired particle properties. We will address different reference material top-down production processes with their limits and challenges for production of materials varying in size ranges of micro- and nanoplastics. T2 - OECD Workshop on Nanoplastics CY - Paris, France DA - 12.11.2025 KW - Microplastics KW - Reference materials KW - Nanoplastics KW - Quality-by-Design PY - 2025 AN - OPUS4-64717 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 - TY - GEN 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 includes 3D tomographic reconstruction image files, volume mesh files for finite element simulations, and data on the structural and mechanical properties of nanoporous gold (NPG) structures. It serves as a supplement to a dataset paper, with the corresponding DOI provided in the “Related Identifiers” section. Detailed descriptions of the data, as well as the procedures for their preparation and curation, are presented in that paper. The base material, nanoporous gold, was fabricated via a dealloying process and has a solid fraction of approximately 0.30. NPG samples with ligament sizes ranging from 20 nm to 400 nm were prepared through dealloying and subsequent thermal annealing. Tomographic TIFF files were obtained via Focused Ion Beam/Scanning Electron Microscopy (FIB/SEM) 3D reconstruction, with the procedure detailed in Philosophical Magazine (2016, 96(32–34), 3322–3335). Based on the 3D image data, new simulations and analyses were performed. The resulting structural and mechanical property data of nanoporous gold are reported for the first time in the dataset paper and are archived here. This dataset provides a valuable database for the study of nanoporous network materials and can be reused for numerical simulations, additive manufacturing, and machine learning applications within the materials science community. KW - Nanoporous gold KW - Dealloying KW - Coarsening KW - FIB/SEM tomography KW - Connectivity KW - Finite element KW - Volume mesh KW - Young’s modulus KW - Yield stress KW - Poisson’s ratio PY - 2025 DO - https://doi.org/10.15480/882.15230 PB - Technische Universität Hamburg Open Research CY - Hamburg AN - OPUS4-64534 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - JOUR A1 - Altmann, Korinna A1 - Portela, Raquel A1 - Barbero, Francesco A1 - Breuninger, Esther A1 - Camassa, Laura Maria Azzurra A1 - Velickovic, Tanja Cirkovic A1 - Charitidis, Costas A1 - Costa, Anna A1 - Fadda, Marta A1 - Fengler, Petra A1 - Fenoglio, Ivana A1 - Giovannozzi, Andrea M. A1 - Haugen, Øyvind Pernell A1 - Kainourgios, Panagiotis A1 - von der Kammer, Frank A1 - Kirchner, Markus J. A1 - Lomax-Vogt, Madeleine A1 - Lujic, Tamara A1 - Milczewski, Frank A1 - Moussawi, Mhamad Aly A1 - Ortelli, Simona A1 - Parac-Vogt, Tatjana N. A1 - Potthoff, Annegret A1 - Jimenez Reinosa, Julian J. A1 - Röschter, Sophie A1 - Sacco, Alessio A1 - Wimmer, Lukas A1 - Zanoni, Ilaria A1 - Dailey, Lea Ann T1 - Characterizing nanoplastic suspensions of increasing complexity: inter-laboratory comparison of size measurements using dynamic light scattering N2 - Understanding the potential human health risks associated with micro- and nanoplastic exposure is currently a priority research area. Nanoplastic toxicity studies are complicated by the lack of available, well-characterized test and reference materials. Further, many nanoplastic test materials are inherently more polydisperse and heterogenous in shape compared to polystyrene beads, making accurate and representative size distribution measurements particularly challenging. The aim of this study was to conduct an inter-laboratory comparison of dynamic light scattering measurements, the most commonly used particle sizing method for nanomaterials. Using a published standard operating procedure, size measurements in water and a standardized cell culture medium (CCM) were generated for spherical, carboxy-functionalized polystyrene nanoparticles (PS-COOH; 50 nm; benchmark material), and for increasingly complex in-house produced spherical poly(ethylene terephthalate) (nanoPET) and irregular shaped polypropylene (nanoPP) test materials. The weighted mean of hydrodynamic diameters of PS-COOH dispersed in water (55 ± 5 nm) showed moderate variation between labs (coefficient of variation, CV = 8.2%) and were similar to literature reports. Measurements of nanoPET (82 ± 6 nm) and nanoPP (182 ± 12 nm) in water exhibited similar CV values (nanoPET: 7.3% and nanoPP; 6.8%). Dispersion of PS-COOH and nanoPET in CCM increased the CV to 15.1 and 14.2%, respectively, which is lower than literature reports (CV = 30%). We conclude with a series of practical recommendations for robust size measurements of nanoplastics in both water and complex media highlighting that strict adherence to a standard operating procedure is required to prevent particle agglomeration in CCM KW - Nanoplastics KW - Reference materials KW - Polypropylene PY - 2025 UR - https://nbn-resolving.org/urn:nbn:de:kobv:b43-644571 DO - https://doi.org/10.1039/d5en00645g SN - 2051-8153 SP - 1 EP - 15 PB - Royal Society of Chemistry (RSC) AN - OPUS4-64457 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER -