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 -