TY - GEN A1 - Pauw, Brian Richard A1 - Laskina, Sofya A1 - Naik, Aakash A1 - Smales, Glen Jacob A1 - George, Janine A1 - Breßler, Ingo A1 - Benner, Philipp T1 - Jupyter notebook and VASP calculation details accompanying the manuscript: "Ultima Ratio: Simulating wide-range X-ray scattering and diffraction" N2 - Summary: This notebook and associated datasets (including VASP details) accompany a manuscript available on the ArXiv (https://doi.org/10.48550/arXiv.2303.13435) and hopefully soon in a journal as short communication as well. Most of the details needed to understand this notebook are explained in that paper with the same title as above. For convenience, the abstract is repeated here: Paper abstract: We demonstrate a strategy for simulating wide-range X-ray scattering patterns, which spans the small- and wide scattering angles as well as the scattering angles typically used for Pair Distribution Function (PDF) analysis. Such simulated patterns can be used to test holistic analysis models, and, since the diffraction intensity is presented coupled to the scattering intensity, may offer a novel pathway for determining the degree of crystallinity. The "Ultima Ratio" strategy is demonstrated on a 64-nm Metal Organic Framework (MOF) particle, calculated from $Q<0.01$\,$\mathrm{nm}^{-1}$ up to $Q\approx150$\,$\mathrm{nm}^{-1}$, with a resolution of 0.16\,\AA. The computations exploit a modified 3D Fast Fourier Transform (3D-FFT), whose modifications enable the transformations of matrices at least up to $8000^3$ voxels in size. Multiple of these modified 3D-FFTs are combined to improve the low-$Q$ behaviour. The resulting curve is compared to a wide-range scattering pattern measured on a polydisperse MOF powder. While computationally intensive, the approach is expected to be useful for simulating scattering from a wide range of realistic, complex structures, from (poly-)crystalline particles to hierarchical, multicomponent structures such as viruses and catalysts. KW - X-ray KW - Simulation KW - Scattering KW - MOUSE KW - Nanomaterials KW - XRD KW - SAXS KW - PDF KW - Total scattering KW - 3D Fourier transform KW - High resolution KW - FFT PY - 2023 DO - https://doi.org/10.5281/zenodo.7764044 PB - Zenodo CY - Geneva AN - OPUS4-57207 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Hülagü, Deniz A1 - Hertwig, Andreas T1 - Correlative analysis of graphene: Advancing ellipsometry as a fast routine method N2 - Graphene (G) and graphene oxide (GO) are key materials for various applications, yet their structural and thickness inhomogeneities calls for rapid, reliable characterization. In this work, we performed a correlative analysis, combining spectroscopic (SE) and imaging ellipsometry (IE) with complementary microscopy techniques to investigate monolayer graphene and GO flakes on SiO₂/Si substrates. SEM, owing to its high resolution and excellent contrast, delivered a comprehensive overview of the monolayer graphene (Figure 1a) and enabled the clear identification of individual GO flakes (c). However, SEM does not provide layer-thickness information. In this case, SE served as a fast and non-destructive method capable of quantitative thickness determination through optical modeling, revealing a graphene layer thickness of 0.7 nm (b), corresponding to a monolayer. The GO flake identified by SEM was subsequently analyzed by AFM, a well-established technique providing nanoscale height profiles with high accuracy (d–f). AFM results further revealed flake thicknesses of a few monolayers. However, AFM is time-consuming, restricted to small scan areas, and does not offer a full overview of the sample. WLIM complemented these results by providing large-area imaging, enabling the visualization of multiple flakes simultaneously. Nevertheless, it is not able to quantify the exact thickness (e). In contrast, IE enabled non-destructive, substrate-independent thickness of GO flakes with single-atomic-layer precision and improved sensitivity, once the ellipsometer settings were optimized for material and thickness contrast and fixed during imaging, bridging the gap between overview imaging and quantitative nanoscale analysis (g–h). While SE provides non-destructive, quantitative thickness information for homogeneous monolayer graphene, GO flakes require imaging-based methods. Therefore, IE represents an attractive alternative, offering large-area maps of GO flakes together with local layer-thickness information. This correlative approach establishes a foundation for standardized, large-area quality assessment of such 2D materials. T2 - 13th Workshop on Spectroscopic Ellipsometry WSE 2026 CY - Genova, Italy DA - 09.02.2026 KW - Monolayer graphene KW - Graphene oxide KW - Correlative Analysis KW - SEM KW - Spectroscopic ellipsometry KW - Imaging ellipsometry KW - AFM PY - 2026 AN - OPUS4-65708 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 Materials Design N2 - Despite significant progress, computational materials design still faces major challenges—particularly when simulating advanced and chemically complex materials with the accuracy of density functional theory (DFT) or beyond.[1] To overcome these limitations, machine learning (ML) methods have gained considerable traction in recent years. We have developed robust data-generation strategies to support the creation and benchmarking of new ML models.[2] In this talk, I will highlight methods for large-scale quantum-chemical bonding analysis and workflows for ML interatomic potentials. Our work demonstrates that quantum-chemical bonding properties can be incorporated into ML models to predict phononic properties.[3] This approach enables large-scale validation of expected correlations—such as the link between bonding strength and force constants or thermal conductivities. Furthermore, we have built an automated training framework for machine-learned interatomic potentials (autoplex).[4] Initial workflows include random structure searches, suitable for general-purpose potentials, as well as specialized workflows targeting ML potentials with accurate phonon properties. While atomistic simulations are highly effective for certain material properties, others—such as magnetism or synthesizability—remain challenging. In these cases, promising strategies include benchmarking established ab initio methods against chemical heuristics or developing new ML models primarily based on experimental data.[5,6] T2 - MATSUS Spring 2026 CY - Barcelona, Spain DA - 24.03.2026 KW - Materials Design KW - High-througput KW - Bonding properties KW - Thermal conductivity KW - Amorphous materials KW - Crystallisation PY - 2026 AN - OPUS4-65734 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - JOUR A1 - Pütz, E. A1 - Smales, Glen Jacob A1 - Jegel, O. A1 - Emmerling, Franziska A1 - Tremel, W. T1 - Tuning ceria catalysts in aqueous media at the nanoscale: how do surface charge and surface defects determine peroxidase- and haloperoxidase-like reactivity N2 - Designing the shape and size of catalyst particles, and their interfacial charge, at the nanometer scale can radically change their performance. We demonstrate this with ceria nanoparticles. In aqueous media, nanoceria is a functional mimic of haloperoxidases, a group of enzymes that oxidize organic substrates, or of peroxidases that can degrade reactive oxygen species (ROS) such as H2O2 by oxidizing an organic substrate. We show that the chemical activity of CeO2−x nanoparticles in haloperoxidase- and peroxidaselike reactions scales with their active surface area, their surface charge, given by the ζ-potential, and their surface defects (via the Ce3+/Ce4+ ratio). Haloperoxidase-like reactions are controlled through the ζ-potential as they involve the adsorption of charged halide anions to the CeO2 surface, whereas peroxidase-like reactions without charged substrates are controlled through the specific surface area SBET. Mesoporous CeO2−x particles, with large surface areas, were prepared via template-free hydrothermal reactions and characterized by small-angle X-ray scattering. Surface area, ζ-potential and the Ce3+/Ce4+ ratio are controlled in a simple and predictable manner by the synthesis time of the hydrothermal reaction as demonstrated by X-ray photoelectron spectroscopy, sorption and ζ-potential measurements. The surface area increased with synthesis time, whilst the Ce3+/Ce4+ ratio scales inversely with decreasing ζ-potential. In this way the catalytic activity of mesoporous CeO2−x particles could be tailored selectively for haloperoxidase- and peroxidase-like reactions. The ease of tuning the surface properties of mesoporous CeO2x particles by varying the synthesis time makes the synthesis a powerful general tool for the preparation of nanocatalysts according to individual needs. KW - SAXS KW - Ceria KW - Zeta potential PY - 2022 DO - https://doi.org/10.1039/D2NR03172H SP - 1 EP - 12 PB - Royal Society of Chemistry AN - OPUS4-55649 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Gugin, Nikita T1 - Advancing Industrial Mechanochemistry: Real-Time Insights for Sustainable, Solvent-Free Manufacturing N2 - Mechanochemistry is an environmentally friendly synthetic approach that enables the sustainable production of a wide range of chemicals while reducing or eliminating the need for solvents. Reactive extrusion aims to move mechanochemistry from its conventional gram-scale batch reactions, typically performed in laboratory ball mills, to a continuous, large-scale process. Meeting this challenge requires in situ monitoring techniques to gain insights into reactive extrusion and its underlying processes. While the effectiveness of in situ Raman spectroscopy in providing molecular-level information has been demonstrated, our study uses energy-dispersive X-ray diffraction to monitor reactive extrusion in real time at the crystalline level. Our results provide previously unavailable control over thereactiveextrusion process, promoting its perception as an industrially feasible green alternative to traditional solventbased syntheses. T2 - #RSCPoster 2025 CY - Online meeting DA - 04.03.2025 KW - Mechanochemistry PY - 2025 AN - OPUS4-63803 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Pauw, Brian Richard T1 - Getting down to business: pragmatic solutions for laboratory automation N2 - A chemical engineer by training, Brian drifted towards physics and now focuses on a broad spectrum of activities with the aim to improve scientific reproducibility. This includes studies on holistically improving data quality, data collection efficiency and traceability, as well as concomitant laboratory automation for the preparation of consistent, well-documented sample series. The need for pragmatism led to an inexpensive, flexible laboratory automation platform that can be implemented in a modest amount of time. This talk presents that effort. T2 - Future Labs Live 2024 CY - Basel, Switzerland DA - 25.06.2024 KW - Laboratory automation KW - Experiment tracking KW - Holistic experimentation KW - Experimental traceability KW - Data visualisation KW - Parameter correlation. PY - 2024 AN - OPUS4-60583 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Pauw, Brian Richard T1 - Glimpses of the future: a “full stack”, highly automated materials research laboratory N2 - In our (dramatically understaffed) X-ray scattering laboratory, developing a systematic, holistic methodology let us provide scattering and diffraction information for more than 2100 samples for 200+ projects led by 120+ collaborators. Combined with automated data correction pipelines, and our analysis and simulation software, this led to more than 40 papers in the last 5 years with just over 2 full-time staff members. This year, our new, modular synthesis platform has made more than 1000 additional samples for us to analyse and catalogue. By virtue of the automation, the synthesis of these samples is automatically documented in excruciating detail, preparing them for upload and exploitation in large-scale materials databases. Having developed these proof-of-concepts, we find that materials research itself is changed dramatically by automating dull tasks in a laboratory. This talk is intended to spark ideas and collaborations by providing an overview of: 1) the current improvements in our scattering laboratory methodology, 2) introducing our open, modular robotic platform that is used for systematic sample preparation, and 3) demonstrating the data structure of the synthesis logs and measurements. Finally, the remaining bottlenecks and points of attention across all three are highlighted. T2 - FAIRmat seminar CY - Berlin, Germany DA - 28.09.2023 KW - Data stewartship KW - Metadata collection KW - Laboratory methodology KW - MOUSE KW - Robotics KW - Lab automation KW - Holistic science PY - 2023 UR - https://www.fairmat-nfdi.eu/events/brian-pauw AN - OPUS4-58464 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Pauw, Brian Richard T1 - Chasing perfection: A holistic approach to materials science scattering experiments N2 - The materials scientists we work with do not want (or need) to learn the ways of the scatterer; they are primarily interested in obtaining trustworthy answers. In particular, they need structural understanding in light of the wider framework of their experiment(s). Our interest, therefore, lies in helping them attain this this interconnected understanding, while using such investigations to further hone our methodology to approximate perfection. While perfection is by definition an unattainable goal, we have spent the last 15+ years exploring and expanding on many of its constituent aspects (often together with likeminded people) [1]. These aspects include: - developing various visualization and simulation tools, - deconstructing data corrections and uncertainty estimation, - advancing analysis methods, - quantifying questions on traceability, documentation, - reproducible automation of synthesis-, measurement- and data pipelines, - data visualization, exploration and education, - and many more… T2 - XIX International Small Angle Scattering Conference CY - Taipei, Taiwan DA - 04.11.2024 KW - Methodology KW - X-ray scattering KW - Data quality KW - Data provenance KW - Data stewardship KW - Lab automation KW - Perfection PY - 2024 AN - OPUS4-61625 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - GEN A1 - Smales, Glen Jacob A1 - Pauw, Brian Richard T1 - DACHS/MOFs/AutoMOFs_2/Synthesis N2 - The DACHS (Database for Automation, Characterization and Holistic Synthesis) project aims to create completely traceable experimental data, covering syntheses, measurements, analyses, and interpretations. DACHS_MOFs focuses on the synthesis and characterisation of metal-organic frameworks, across multiple, automation-assisted experimental series (AutoMOFs), with the overall goal of producing reproducible MOF samples through tracking of the synthesis parameters. DACHS_MOFs is simultaneously used to test the DACHS principles. This upload contain synthesis data from AutoMOFs_2 in HDF5 format (.h5). Each .h5 file contains detailed information on the chemical, experimenal, and synthesis parameters used during the synthesis of a single AutoMOF sample. KW - Automation KW - Procedure KW - Synthesis KW - Traceability PY - 2024 DO - https://doi.org/10.5281/zenodo.11236074 PB - Zenodo CY - Geneva AN - OPUS4-60611 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Pauw, Brian Richard T1 - A holistic experiment chain for scattering-powered materials science investigations N2 - In our (dramatically understaffed) X-ray scattering laboratory, developing a systematic, holistic methodology1 let us provide scattering and diffraction information for more than 2100 samples for 200+ projects led by 120+ collaborators over the last five years. Combined with universal, automat-ed data correction pipelines, as well as our analysis and simulation software, this led to more than 40 papers2 in the last 5 years with just over 2 full-time staff members. While this approach greatly improved the consistency of the results, the consistency of the samples and sample series provided by the users was less reliable nor necessarily reproducible. To address this issue, we built an EPICS-controlled, modular synthesis platform to add to our laboratory. To date, this has prepared over 1200 additional (Metal-Organic Framework) samples for us to meas-ure, analyse and catalogue. By virtue of the automation, the synthesis of these samples is automat-ically documented in excruciating detail, preparing them for upload and exploitation in large-scale materials databases alongside the morphological results obtained from the automated X-ray scat-tering analysis. Having developed these proof-of-concepts, we find that the consistency of results are greatly im-proved by virtue of their reproducibility, hopefully adding to the reliability of the scientific findings as well. Additionally, the nature of the experiments has changed greatly, with much more emphasis on preparation and careful planning. This talk will discuss the advantages and disadvantages of this highly integrated approach and will touch upon upcoming developments. T2 - canSAS-XIII CY - Grenoble, France DA - 16.10.2023 KW - Methodology KW - Lab automation KW - X-ray scattering KW - Automated synthesis KW - Data stewardship KW - Holistic experimental procedures KW - Scicat PY - 2023 AN - OPUS4-58643 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Gugin, Nikita T1 - ZIF-8-Based Biocomposites via Reactive Extrusion: Towards Industrial-Scale Manufacturing N2 - Mechanochemistry offers a solvent-free, sustainable alternative to conventional synthesis of metal-organic framework (MOF) biocomposites, which hold great promise for applications in drug delivery, biocatalysis, and biosensing,[1] yet the field remains limited to batch-type, gram-scale processes that restrict industrial application. To overcome these limitations, we present a scalable solid-state method for producing MOF-based biocomposites via continuous reactive extrusion. The process begins with rapid model reactions using hand-mixing[2] to encapsulate a variety of biomolecules into zeolitic imidazolate framework-8 (ZIF-8), including proteins, carbohydrates, and enzymes, thereby enabling rapid screening and optimization of reaction conditions. The mild synthesis conditions preserve the catalytic activity of glucose oxidase, confirming the suitability of the method to sensitive biomaterials. Building on this, we translated the batch protocol to twin-screw extrusion,[3] enabling continuous and scalable synthesis of biocomposites such as bovine serum albumin (BSA)@ZIF-8 with tunable protein content. The extrusion process yielded highly crystalline, porous materials with protein loadings of up to 26 wt% and encapsulation efficiencies as high as 96%. The production rate reached 1.2 kg d⁻¹, significantly exceeding previously reported continuous methods.[4] To demonstrate the industrial viability of the method, we extended the approach to produce shaped ZIF-8 monoliths loaded with hyaluronic acid (HA) in a single-step extrusion. These monoliths retained their structural integrity during washing and released HA without measurable degradation, as confirmed by size-exclusion chromatography. Our study opens new avenues for the industrial implementation of MOF biocomposites and establishes reactive extrusion as a robust platform for their scalable synthesis and shaping, expanding the toolkit for drug delivery and biocatalytical applications. T2 - Tag der Chemie 2025 CY - Berlin, Germany DA - 03.07.2025 KW - Mechanochemistry PY - 2025 AN - OPUS4-63802 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - JOUR A1 - Bustamante, Joana A1 - Ghata, Anupama A1 - Naik, Aakash A. A1 - Ertural, Christina A1 - Ueltzen, Katharina A1 - Zeier, Wolfgang G. A1 - George, Janine T1 - Thermal transport in Ag8T S6(T = Si, Ge, Sn) argyrodites: an integrated experimental, quantum-chemical, and computational modelling study N2 - Argyrodite-type Ag-based sulfides combine exceptionally low lattice thermal and high ionic conductivity, making them promising candidates for thermoelectric and solid-state energy applications. In this work, we studied Ag8TS6 (T = Si, Ge, Sn) argyrodite family by combining chemical-bonding analysis, lattice vibrational properties simulation, and experimental measurements to investigate their structural and thermal transport properties. Furthermore, we propose a two-channel lattice-dynamics model based on Grüneisen-derived phonon lifetimes and compare it to an approach using machine-learned interatomic potentials. Both approaches are able to predict thermal conductivity in agreement with experimental lattice thermal conductivities along the whole temperature range, highlighting their potential suitability for future high-throughput predictions. Our findings also reveal a relationship between bond heterogeneity arising from weakly bonded Ag+ ions and occupied antibonding states in Ag–S and Ag–Ag interactions and strong anharmonicity, including large Grüneisen parameters, and low sound velocities, which are responsible for the low lattice thermal conductivity of Ag8SnS6, Ag8GeS6, and Ag8SiS6. We furthermore show that thermal and ionic conductivities in all three compounds are independent of each other and can likely be tuned individually. KW - Thermal Conductivity KW - Ionic Conductivity KW - Machine Learning KW - Materials Design KW - Microstructure KW - Bonding Analysis KW - Anharmonicity PY - 2026 UR - https://nbn-resolving.org/urn:nbn:de:kobv:b43-657076 DO - https://doi.org/10.1039/D5TA08709K SN - 2050-7488 SP - 1 EP - 13 PB - Royal Society of Chemistry (RSC) AN - OPUS4-65707 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - JOUR A1 - Miyata, Ayana A1 - Tokuda, Shun A1 - Kuzumoto, Mako A1 - Lee, Guan-Sian A1 - Yamashita, Masataka A1 - Nishiguchi, Taichi A1 - Negoro, Masaki A1 - Pauw, Brian Richard A1 - Chan, Yi-Tsu A1 - Kanamori, Kazuyoshi A1 - Urayama, Kenji A1 - Sugimoto, Kunihisa A1 - Furukawa, Shuhei T1 - One-Dimensional van der Waals Porous Fibrils Assembled from Metal–Organic Polyhedra N2 - Supramolecular systems exhibit collective functions that emerge from the hierarchical assembly of individual molecular building blocks. Metal−organic polyhedra (MOPs) are a class of functional supramolecular architectures with well-defined molecular geometry and an intrinsic cavity. In recent years, considerable progress has been made in assembling MOPs into extended networks to create porous solids. However, most reported MOP assemblies are limited to three-dimensional networks, which, owing to their high-dimensional connectivity, hinder effective stress dissipation and render them brittle under mechanical stress. Here, we report the one-dimensional (1D) self-assembly of MOPs into supramolecular polymeric aerogels that combine permanent microporosity with exceptional mechanical flexibility. The reaction between amino acid-functionalized naphthalenediimide (NDI) linkers and copper salts led to the synthesis of octahedral copper-based MOPs, followed by their spontaneous self-assembly to form supramolecular gels. The corresponding aerogels converted from the gels possessed uniform 1D fibrillar networks (14.8 ± 2.2 nm in width) with intrinsic microporosity derived from individual MOP cavities. The aerogel endured 87% compressive strain without fracture, demonstrating distinct ductility. Furthermore, these fibrils in the supramolecular gels were converted to crystals after 2 weeks. Single-crystal X-ray diffraction revealed that MOPs are arranged via face-to-face interaction between octahedral MOPs to form a 1D helical chain structure. An analysis of the self-assembly process using Hansen solubility parameters unveiled that solvent conditions with high polarity and low dispersion interaction drive the formation of anisotropic assemblies. This work provides a new strategy for tailoring the mechanical properties of supramolecular materials through dimensional control of their assemblies. KW - Aerogels KW - Crystals KW - Metal organic frameworks KW - Nanofibers KW - Solvents KW - X-ray scattering KW - SAXS KW - Nanostructure KW - Small-angle X-ray scattering PY - 2026 DO - https://doi.org/10.1021/jacs.5c21654 SN - 0002-7863 SP - 1 EP - 13 PB - American Chemical Society (ACS) AN - OPUS4-65776 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Ruehle, Bastian T1 - The Role of Analytics for Closing the Loop in Self-Driving Labs N2 - The recent emergence of self-driving laboratories (SDL) and material acceleration plat-forms (MAPs) demonstrates the ability of these systems to change the way chemistry and material syntheses will be performed in the future. Especially in conjunction with nano- and advanced materials which are generally recognized for their great potential in solving current material science challenges, such systems can make disrupting con-tributions. Consequently, new tools that enhance the development and optimization cycle of nano- and advanced materials are crucial. In this contribution, we present our Self-Driving Lab (SDL) for Nano and Advanced Materials [1], that integrates robotics for batched autonomous synthesis – from molecular precursors to fully purified nano-materials – with automated characterization and data analysis, for a complete and reli-able nanomaterial synthesis workflow. By automating the processing and characteriza-tion 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, reproducibility, and flexibility of the platform. The system also incorporates in-line characterization measurement of hydrodynamic diameter, zeta potential, and optical properties (absorbance, fluorescence). In general, the interface with data analysis algorithms from in-line, at-line, and off-line measure-ments is of great importance for closing the design-make-test-analyze cycle and using these platforms efficiently. Here, we will give examples of how automatic image seg-mentation of electron microscopy images with the help of AI [2] can be used for reduc-ing the “data analysis bottleneck” from an off-line measurement. We will also discuss various machine learning (ML) algorithms that are currently implemented in the backend and can be used for ML-guided, closed-loop material optimization in our SDL. Lastly, we will show our recent efforts [3] in making the workflow generation on SDLs more user-friendly by using large language models to generate executable workflows automatically from synthesis procedures given in natural language and user-friendly graphical user interfaces based on node editors that also allow for knowledge graph extraction from the workflows. In this context, we are currently also working on a com-mon description or ontology for representing the process steps and parameters of the workflows, which will greatly facilitate the semantic description and interoperability of workflows between different SDL hardware and software platforms. These features underscore the SDL’s potential as a transformative tool for advancing and accelerating the development of nano- and advanced materials, offering solutions for a sustainable and environmentally responsible future. T2 - Analytica Conference 2026 CY - Munich, Germany DA - 24.03.2026 KW - Self-Driving Labs KW - Materials Acceleration Platforms KW - Advanced Materials KW - Nanomaterials KW - Automation KW - Digitalization KW - Ontologies PY - 2026 AN - OPUS4-65760 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Meier, F. A1 - Drexel, R. A1 - Wiesner, Yosri A1 - Altmann, Korinna A1 - Bartczak, D. A1 - Alasonati, E. T1 - Nano-sized Polypropylene as a Promising Candidate Reference Material: Preparation, Characterization and Stability in Complex Matrices N2 - The lack of nanoplastic (NPs) reference materials capable of mimicking real-world scenarios is currently hampering the development of validated extraction techniques from complex matrices, the development of analytical approaches for robust identification and quantification, and the ability to use environmentally relevant test materials in (eco)toxicity testing and hazard assessment. Here, we present a strategy towards the development of a potential NP reference material based on nano-sized polyproplyene particles (nanoPP) developed within the EURAMET-funded PlasticTrace project (https://plastictrace.eu/). The strategy includes the preparation, the physicochemical characterization and the stability assessment of nanoPP in suspension both in its pristine state, but also when spiked into complex matrices like mineral water and milk. NanoPP was produced reproducibly in a top-down approach by crushing in acetone with an UltraTurrax, filtering and change of solvent to MilliQ water. The prepared nanoPP material was subjected to a comprehensive physicochemical characterization including e.g., DLS, PTA and AF4-MALS for particle size distribution assessment, PTA and SEM for particle number concentration determination, SEM and AFM for shape analysis and pyrolysis GC-MS for chemical identification. Performed studies showed that the prepared nanoPP material is irregularly shaped and highly polydisperse with a particle size of around 180 nm (e.g., Dh,z-ave from DLS) and a particle size distribution from around 15 nm up to 135 nm (radius of gyration Rg from AF4-MALS). Storage stability studies using DLS, PTA and AF4-MALS revealed nanoPP in aqueous suspension to be stable for at least 22 months with respect to particle size distribution and number concentration rendering it a promising NP candidate reference material. However, conducted spiking experiments in mineral water and milk showed a time-dependent agglomeration of nanoPP that needs further investigation. T2 - MICROPLASTICdays CY - Ljubliana, Slovenia DA - 03.02.2026 KW - Nanoplastics KW - Reference materials PY - 2026 AN - OPUS4-65769 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Meier, F. A1 - Altmann, Korinna T1 - Challenges in nanoplastic analysis: Reference materials, complex matrices, and limits of detection N2 - The growing concern over nanoplastic particles (< 1 µm) in food and the environment has intensified the need for robust analytical approaches to detect, quantify, and characterize these particles. But the lack is high of standardized and well-characterized reference materials that reflect environmentally relevant nanoplastics according to: • Size distribution • Low abundance • Chemical diversity • Surface properties • Behavior in complex matrices. This poster shows different methods like FFF and AF4-MALS and their results when measuring a nanoPP reference materials candidate. T2 - Analytica Conference 2026 CY - Munich, Germany DA - 24.03.2026 KW - Nanoplastics KW - Reference materials KW - AF4-MALS KW - FFF PY - 2026 AN - OPUS4-65770 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Hodoroaba, Vasile-Dan T1 - Capacity building and Knowledge Exchange in Research Management from the Perspective of a Project Coordinator N2 - In the Seminar "Capacity building and Knowledge Exchange in Research Management" following three points are presented in detail: - Example of a successfully completed international project, - Role of institutional support in project success, and - Practical challenges and lessons learned from a coordinator‘s perspective. T2 - Seminar "Capacity building and Knowledge Exchange in Research Management" CY - Online meeting DA - 25.03.2026 KW - Research management KW - Institutional support KW - Project coordination KW - European projects PY - 2026 AN - OPUS4-65811 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER -