TY - RPRT A1 - Falkenhagen, Jana A1 - Beskers, Timo. F. A1 - Myxa, Anett A1 - Pursch, Matthias T1 - Round-robin test for size exclusion chromatography – Data summary N2 - Size exclusion chromatography (SEC or GPC) is one critical component of polymer analysis to meet the increasing requirements in regulatory context – namely, determination of Mn, as well as oligomers of less than 500 g mol-1 and 1000 g mol-1. The underlying test methods (OECD 118/119 and DIN EN ISO 13885 1 to 3) provide a framework for SEC measurements; however, they lack sufficient specificity to obtain accurate results. Previous SEC round robin tests were mostly performed on homopolymers and did not collect data on oligomer contents. A new round robin test was initiated and conceptualized within the Task force “Method Evaluation for Polymer REACh (MeEP)”, an initiative of “Industrieforum Analytik” within the German Chemical Society (GDCh). Samples for this study were selected to represent both easy benchmark polymers as well as real-life, industry-relevant polymer materials. Data collection focused on the regulatory requirements. Distribution of samples, gathering of individual results and evaluation were carried out by BAM. A data summary as initial result is reported here. Further evaluation and interpretation are a part of ongoing research. KW - Size exclusion chromatography KW - Polymers KW - Oligomer content KW - Round-robin test PY - 2026 DO - https://doi.org/10.26272/opus4-65587 SP - 1 EP - 84 PB - Bundesanstalt für Materialforschung und -prüfung (BAM) CY - Berlin AN - OPUS4-65587 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Zaki, Mohammad T1 - Nano-And Advanced Materials Synthesis In A Self-Driving Lab (SDL) N2 - Nano- and advanced materials are recognized as key enabling technologies of the 21st century, offering exceptional potential to drive innovation and tackle pressing challenges in materials science. To fully realize this potential, it is essential to develop and improve tools that accelerate their design, development, and optimization. Recognizing this pressing need, we present a Self-Driving Lab (SDL) that integrates robotics for batched autonomous synthesis – from molecular precursors to fully purified nanomaterials, with automated characterization and data analysis, for a complete and reliable nanomaterial synthesis workflow. By fully automating these three process steps for seven different materials from five representative, completely different classes of nano- and advanced materials (metal, metal oxide, silica, metal organic framework, and core–shell particles) that follow different reaction mechanisms, we demonstrate the great versatility and flexibility of the platform. The system also exhibits modularity, impressive adaptability in terms of reactions scales and incorporates in-line characterization measurement of hydrodynamic diameter, zeta potential, and optical properties (absorbance, fluorescence) of the nanomaterials, along with automating data analysis of at-line or off-line characterization techniques such as electron microscopy image analyses. Automated characterization and data analysis is complemented by a machine learning–driven feedback loop employing active learning algorithms (e.g., Bayesian optimization, artificial neural networks, and downhill simplex methods) to iteratively suggest new experimental parameters toward desired material properties. Therefore, the excellent reproducibility for material syntheses when run on the SDL platform multiple times, the material agnostic behavior, the adaptability, and modularity, underscore the SDL’s reliability and potential as a transformative tool for advancing the development and applications of nano- and advanced materials, offering solutions for a sustainable future. T2 - Gordon Research Seminar and Conference, Multifunctional Materials and Structures-conference CY - Ventura, CA, USA DA - 24.01.2026 KW - Self-Driving Laboratories KW - Materials Acceleration Platforms KW - Nanomaterials PY - 2026 AN - OPUS4-65597 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Zaki, Mohammad T1 - Nano- and Advanced Materials Synthesis in a Self-Driving Lab N2 - Nano- and advanced materials are recognized as key enabling technologies of the 21st century, offering exceptional potential to drive innovation and tackle pressing challenges in materials science [1]. To fully realize this potential, it is essential to develop and improve tools that accelerate their design, development, and optimization. Recognizing this pressing need, we present a Self-Driving Lab (SDL) [2] that integrates robotics for batched autonomous synthesis – from molecular precursors to fully purified nanomaterials, with automated characterization and data analysis, for a complete and reliable nanomaterial synthesis workflow. By fully automating these three process steps for seven different materials from five representative, completely different classes of nano- and advanced materials (metal, metal oxide, silica, metal organic framework, and core–shell particles) that follow different reaction mechanisms, we demonstrate the great versatility and flexibility of the platform. The system also exhibits modularity, impressive adaptability in terms of reactions scales and incorporates in-line characterization measurement of hydrodynamic diameter, zeta potential, and optical properties (absorbance, fluorescence) of the nanomaterials, along with automating data analysis of at-line or off-line characterization techniques such as electron microscopy image analyses [3]. Automated characterization and data analysis is complemented by a machine learning–driven feedback loop employing active learning algorithms (e.g., Bayesian optimization, artificial neural networks, and downhill simplex methods) to iteratively suggest new experimental parameters toward desired material properties. Therefore, the excellent reproducibility for material syntheses when run on the SDL platform multiple times, the material agnostic behavior, the adaptability, and modularity, underscore the SDL’s reliability and potential as a transformative tool for advancing the development and applications of nano- and advanced materials, offering solutions for a sustainable future. T2 - Gordon Research Seminar and Conference CY - Ventura, CA, USA DA - 24.01.2026 KW - Self-Driving Laboratories KW - Materials Acceleration Platforms KW - Nanomaterials PY - 2026 AN - OPUS4-65596 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - George, Janine T1 - Crossing Scientific Disciplines with Materials Informatics:� From Atoms to Algorithms N2 - Within this talk, I introduced students from Physics to Materials Informatics. To provide a context for this research, I have introduced the students to BAM and its tasks. I then started to introduce our activity field materials design, including materials acceleration platforms. Then, I explained how simulations speed up the materials searches as parf of materials acceleration platforms. T2 - jDPG Jena Meeting - Poland exchange CY - Jena, Germany DA - 26.02.2026 KW - Automation KW - Machine Learning KW - Materials Design KW - Batteries KW - Workflows PY - 2026 AN - OPUS4-65589 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Kumar, Sourabh T1 - Grain Boundary Transformation Induced by Boron Segregation N2 - The segregation of solute atoms at grain boundaries (GBs) plays a critical role in defining the mechanical properties of materials, including corrosion resistance and fracture toughness. This study investigates the structural transformations induced by minimal boron concentrations at Σ13 GBs in ferrite thin films synthesized. Two sample protocols were examined: one with carbon as the sole solute and the other with carbon and boron co-segregation. To understand the thermodynamics of such phases, we employed ab initio calculations to meticulously examine the competing Σ13 GB phases that coexist in the presence of defects and stacking faults. Building on our findings regarding these competing GB phases, we analyzed the energetic aspects of solute segregation at the GB interface. Furthermore, we constructed a defect phase diagram to gain insights into the influence of Boron concentration on the evolution of GB structure. We reveal that boron segregation transforms the GB structure from flat to zigzag trigonal prisms by forming new chemical bonds, ultimately enhancing bonding strength between boron and iron atoms by 5%. This transformation doubles steel's resistance to fracture and provides valuable insights into the thermodynamic and energetic aspects of solute-driven GB phase evolution. These findings contribute to developing innovative strategies for designing high-performance steel with enhanced mechanical integrity and durability. T2 - DPG 2025 Regensburg CY - Regensburg, Germany DA - 16.03.2025 KW - Defect Phases KW - Grain Boundary KW - Steel PY - 2025 AN - OPUS4-65580 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - JOUR A1 - Liu, Yuanbin A1 - Zhou, Yuxing A1 - Ademuwagun, Richard A1 - Walterbos, Luc A1 - George, Janine A1 - Elliott, Stephen R. A1 - Deringer, Volker L. T1 - Medium-Range Structural Order in Amorphous Arsenic N2 - Medium-range order (MRO) is a key structural feature of amorphous materials, but its origin and nature remain elusive. Here, we reveal the MRO in amorphous arsenic (a-As) using advanced atomistic simulations, based on machine-learned potentials derived using automated workflows. Our simulations accurately reproduce the experimental structure factor of a-As, especially the first sharp diffraction peak (FSDP), which is a signature of MRO. We compare and contrast the structure of a-As with that of its lighter homologue, red amorphous phosphorus (a-P): we find that a-As has a more uniform dihedral-angle distribution, and so we confirm that its structure can be thought of as a 3-fold coordinated continuous random network in first approximation, in contrast to the more molecular-cluster-like structure of a-P. The pressure-dependent structural behaviors of a-As and a-P differ as well, and the origin of the FSDP is closely correlated with the size and spatial distribution of voids in the amorphous networks. Our work provides fundamental insights into MRO in an amorphous elemental system, and more widely it illustrates the usefulness of automation for machine-learning-driven atomistic simulations. KW - Machine Learned Interatomic Potentials KW - Amorphous KW - Advanced Materials KW - Automation KW - Digitalisation KW - Structure-Property- Relationships PY - 2026 UR - https://nbn-resolving.org/urn:nbn:de:kobv:b43-655952 DO - https://doi.org/10.1021/jacs.5c18688 SN - 0002-7863 SP - 1 EP - 13 PB - American Chemical Society (ACS) AN - OPUS4-65595 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - JOUR A1 - Frechilla, A. A1 - Martínez, E. A1 - del Moral, J. A1 - López-Santos, C. A1 - Frechilla, J. A1 - Nuñez-Gálvez, F. A1 - López-Flores, V. A1 - de la Fuente, G.F. A1 - Hülagü, Deniz A1 - Bonse, Jörn A1 - González-Elipe, A.R. A1 - Borrás, A. A1 - Angurel, L.A. T1 - Influence of near-edge Laser-Induced Periodic Surface Structures (LIPSS) on the electrical properties of fs-laser-machined ITO microcircuits N2 - Scalable, cost-effective methods for processing transparent electrodes at the microscale are pivotal to advancing in electrochemistry, optoelectronics, microfluidics, and energy harvesting. In these fields, the precise fabrication of micrometric circuits and patterns plays a critical role in determining device performance, material compatibility, and integration with added-value substrates. In this context, Laser Subtractive Manufacturing stands out as a suitable microfabrication technique for its adaptability to diverse materials and complex configurations, as well as its straightforward scalability, affordability, and eco-friendly nature. However, a challenge in micromachining metals and metal oxides is the inherent formation of Laser-Induced Periodic Surface Structures (LIPSS), which can significantly impair electrical conductivity, particularly when circuit dimensions fall within the micrometer range. Herein, we investigate the micromachining of electrical microcircuits using ultrashort pulse laser systems applied to transparent indium tin oxide (ITO) thin films. We analyze the formation of LIPSS at the edges of the micromachined regions associated with the Gaussian distribution of the energy within the laser spot, and the impact of these structures on the electrical properties of the circuits. Thus, we systematically evaluate the influence of LIPSS orientation and periodicity by fabricating various circuit patterns using femtosecond lasers at green (515 nm) and ultraviolet (UV) (343 nm) wavelengths. A correlation between electrical resistivity measurements and microstructure analysis, as determined by field emission scanning electron and transmission electron microscopy, reveals distinct effects of the formed nanostructures depending on the laser source and its polarization. For the green wavelength, the edge side regions where LIPSS are oriented perpendicular to the ITO track exhibit a resistance higher by a factor just above two compared to those where LIPSS are parallel. Additionally, UV laser processing results in a pronounced reduction of ITO thickness at the boundary between the LIPSS region and the substrate. The mechanisms for the formation of LIPSS with both wavelengths are also discussed. Furthermore, we have determined that in narrow conductive tracks with a width ranging from 6 to 8 µm, the impact of LIPSS is particularly significant because the LIPSS structured region occupies a dominant fraction of the total width. KW - ITO KW - Laser-induced periodic surface structures (LIPSS) KW - Laser subtractive manufacturing KW - fs-laser processing KW - Electrical properties PY - 2026 UR - https://nbn-resolving.org/urn:nbn:de:kobv:b43-655921 DO - https://doi.org/10.1016/j.apsusc.2026.166415 SN - 0169-4332 VL - 731 SP - 1 EP - 13 PB - Elsevier B.V. AN - OPUS4-65592 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - JOUR A1 - Kumar, Sourabh A1 - Hickel, Tilmann T1 - Grain Boundary Transformation Induced by Boron Segregation N2 - Boron enhances the hardenability of low-alloyed steel and reduces embrittlement at low temperatures, at parts-per-million concentration levels. Ist effectiveness arises from segregation to grain boundaries (GBs)-planar defects- between crystals-yet atomic-scale evidence remains limited.We addressed this gap by synthesizing GBs with controllable geometry and orientation, enabling reproducible comparison with and without boron segregation. Differential phase-contrast imaging directly reveals boron at iron GBs, and in-situ TEM heating (20 °C to 800 °C) allows us to track the dynamic evolution of GB structures. We found that boron segregation induces local structural changes and triggers GB phase transformations, as corroborated by calculated GB defect phase diagrams spanning broad ranges of carbon and boron content. Our findings not only bridge a gap in understanding the interplay between GB structure and chemistry but also lay the groundwork for targeted design and passivation strategies in steel, potentially transforming its resistance to hydrogen embrittlement, corrosion, and mechanical failure. KW - Steel KW - Defect Phases KW - Grain Boundary PY - 2025 UR - https://nbn-resolving.org/urn:nbn:de:kobv:b43-655812 DO - https://doi.org/10.1038/s41467-025-62264-1 VL - 16 SP - 1 EP - 14 PB - Nature Communications AN - OPUS4-65581 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - JOUR A1 - Atila, Achraf A1 - Bakhouch, Yasser A1 - Xie, Zhuocheng T1 - Revealing the void-size distribution of silica glass using persistent homology N2 - Oxide glasses have proven to be useful across a wide range of technological applications. Nevertheless, their medium-range structure has remained elusive. Previous studies focused on ring statistics as a metric of the medium-range structure, but this metric provides an incomplete picture of the glassy structure. Here, we use atomistic simulations and state-of-the-art topological analysis tools, namely persistent homology (PH), to analyze the medium-range structure of the archetypal oxide glass (Silica) at ambient temperatures and with varying pressures. PH presents an unbiased definition of loops and voids, providing an advantage over other methods for studying the structure and topology of complex materials, such as glasses, across multiple length scales. We captured subtle topological transitions in medium-range order and cavity distributions, providing new insights into glass structure. Our work provides a robust way for extracting the void distribution of oxide glasses based on PH. KW - Medium-range KW - Voids KW - Topology KW - Silica glass KW - Atomistic simulations KW - Persistent homology PY - 2025 UR - https://nbn-resolving.org/urn:nbn:de:kobv:b43-655690 DO - https://doi.org/10.1016/j.mtla.2025.102613 VL - 44 SP - 1 EP - 11 PB - Elsevier Inc. AN - OPUS4-65569 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - JOUR A1 - Hickel, Tilmann A1 - Waske, Anja A1 - Tehranchi, Ali A1 - Bhattacharya, Biswajit A1 - Stawski, Tomasz M. A1 - Fellinger, Tim-Patrick A1 - Mehmood, Asad A1 - Witt, Julia A1 - Ozcan, Ozlem A1 - Guilherme Buzanich, Ana A1 - Kumar, Sourabh A1 - Mishra, Rajesh Kumar A1 - Holzer, Marco A1 - Stucchi de Camargo, Andrea Simone A1 - Agudo Jácome, Leonardo A1 - Manzoni, Anna A1 - Fantin, Andrea A1 - John, Elisabeth A1 - Hodoroaba, Vasile-Dan A1 - Bührig, Sophia A1 - Murugan, Jegatheesan A1 - Marschall, Niklas A1 - George, Janine A1 - Darvishi Kamachali, Reza A1 - Maaß, Robert A1 - Emmerling, Franziska T1 - Chemically complex materials enable sustainable high-performance materials N2 - Chemically complex materials (CCMats) 􀀀 including high-entropy alloys, oxides, and related multi-principal element systems 􀀀 offer a paradigm shift in materials design by leveraging chemical diversity to simultaneously optimize functional, structural, and sustainability criteria. The vastness of the compositional and structural space in CCMats propels the field into an expanding exploratory state. To reconcile functional and structural performance across this immense parameter space remains an open challenge. This Perspective evaluates the opportunities and challenges associated with harnessing chemical complexity across a broad spectrum of applications, such as hydrogen storage, ionic conductors, catalysis, magnetics, dielectrics, semiconductors, optical materials, and multifunctional structural systems. It is delineated how three central design strategies: targeted substitution (SUB), defect engineering (DEF), and diversity management (DIV) enable the reconciliation of high functional performance with long-term structural stability and environmental responsibility. Advances in computational thermodynamics, microstructure simulations, machine learning, and multimodal characterization are accelerating the exploration and optimization of CCMats, while robust data infrastructures and automated synthesis workflows are emerging as essential tools for navigating their complex compositional space. By fostering cross-disciplinary knowledge transfer and embracing data-driven design, CCMats are poised to deliver next-generation materials solutions that address urgent technological, energy, and environmental demands. KW - Chemically complex materials KW - Structural stability KW - Functional performance KW - Design strategies KW - Sustainability PY - 2026 UR - https://nbn-resolving.org/urn:nbn:de:kobv:b43-655598 UR - https://www.sciencedirect.com/science/article/pii/S1359028626000033?via%3Dihub DO - https://doi.org/10.1016/j.cossms.2026.101256 SN - 1359-0286 VL - 42 SP - 1 EP - 26 PB - Elsevier Ltd. CY - Amsterdam AN - OPUS4-65559 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER -