TY - GEN A1 - Naik, Aakash Ashok A1 - Ertural, Christina A1 - Dhamrait, Nidal A1 - Benner, Phillip A1 - George, Janine T1 - Quantum-Chemical Bonding Database (Unprocessed data : Part 2) N2 - This data is associated with the manuscript "A Quantum-Chemical Bonding Database for Solid-State Materials." Refer to mpids.txt to see data related to which compounds are available in the tar file. (mp-xxx refer to Materials Project ID) KW - Bonding analysis KW - Automation KW - Materials Informatics KW - Computational Chemistry KW - Database PY - 2023 DO - https://doi.org/10.5281/zenodo.7852107 PB - Zenodo CY - Geneva AN - OPUS4-57442 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - GEN A1 - George, Janine T1 - Raw data for "Automated bonding analysis with crystal orbital Hamilton populations" N2 - Raw data corresponding to the following paper: 10.1002/cplu.202200123. KW - Automation KW - High-throughput computations KW - Bonding analysis PY - 2022 UR - https://doi.org/10.5281/zenodo.6373369 DO - https://doi.org/10.5281/zenodo.6373368 PB - Zenodo CY - Geneva AN - OPUS4-55175 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - George, Janine T1 - Data-driven chemical understanding N2 - Chemical heuristics are essential to understanding molecules and materials in chemistry. The periodic table, atomic radii, and electronegativities are only a few examples. Initially, they have been developed by a combination of physical insight and a limited amount of data. It is now possible to test these heuristics and generate new ones using automation based on Materials Informatic tools like pymatgen and greater amounts of data from databases such as a Materials Project. In this session, I'll speak about heuristics and design rules based on coordination environments and the concept of chemical bonding. For example, we have tested the Pauling rules which describe the stability of materials based on coordination environments and their connections on 5000 oxides from the Materials Project. In addition, we have created automated processes for analyzing the chemical bonding situation in crystalline materials with Lobster (www.cohp.de) in order to discover new heuristics and design rules. T2 - Materials Project Seminar Series CY - Online meeting DA - 18.05.2022 KW - DFT KW - Chemical heuristics KW - Crystal Orbital Hamilton Populations KW - Machine learning KW - Phonons PY - 2022 UR - https://www.youtube.com/watch?v=e7zYrz6fgog UR - https://next-gen.materialsproject.org/community/seminar AN - OPUS4-55008 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Amariamir, Sasan A1 - Benner, Philipp A1 - George, Janine T1 - Prediction of materials synthesizability N2 - In the pursuit of discovering materials with desirable properties, extending the available material libraries is crucial. High-throughput simulations have become an integral part in designing new materials in the past decades. However, there is no straightforward way of distinguishing synthesizable materials from all the proposed candidates. This project focuses on employing AI-driven methods to estimate synthesizability of materials. Up to now, material scientists and engineers have relied on domain knowledge as well as empirical heuristics to guess the stability and synthesizability of molecules and crystals. The famous Pauling rules of crystal stability are an example of such heuristics. However, after the accelerating material discovery in all the years since Pauling, these rules now fail to account for the stability of most known crystals. A new predictive set of heuristics for crystal stability/synthesizability is unlikely to be uncovered by human perception, given the magnitude and dimensionality of crystallographic data. Hence, a data-driven approach should be proposed to find a predictive model or set of heuristics which differentiate synthesizable crystal structures from the rest. The main challenge of this research problem is the lack of a negative set for classification. Here, there are two classes of data: the positive class which contains synthesizable materials and the negative class which contains materials which are not synthesizable. While the data from the positive class is simply the data of crystals which have been experimentally synthesized, we do not have access to data points which are certainly unsynthesizable. Strictly speaking, if an attempt of synthesizing a crystal fails, it does not necessarily follow that the crystal is not synthesizable. Also, there is no database available which contains the intended crystal structures of unsuccessful synthesis attempts. This project proposes a semi-supervised learning scheme to predict crystal synthesizability. The ML model is trained on experimental and theoretical crystal data. The initial featurization focuses on local environments which is inspired by the Pauling Rules. The experimental data points are downloaded through the Pymatgen API from the Materials Project database which contains relaxed structures recorded in Inorganic Crystal Structure Database – ICSD. The theoretical data is queried from select databases accessible through the Optimade project’s API. T2 - MSE Congress 2022 CY - Darmstadt, Germany DA - 27.09.2022 KW - Synthesizability KW - PU Learning KW - Cheminformatics PY - 2022 AN - OPUS4-56731 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - JOUR A1 - Wilke, Marco A1 - Röder, Bettina A1 - Paul, Martin A1 - Weller, Michael G. T1 - Sintered glass monoliths as supports for affinity columns N2 - A novel stationary phase for affinity separations is presented. This material is based on sintered borosilicate glass readily available as semi-finished filter plates with defined porosity and surface area. The material shows fast binding kinetics and excellent long-term stability under real application conditions due to lacking macropores and high mechanical rigidity. The glass surface can be easily modified with standard organosilane chemistry to immobilize selective binders or other molecules used for biointeraction. In this paper, the manufacturing of the columns and their respective column holders by 3D printing is shown in detail. The model system protein A/IgG was chosen as an example to examine the properties of such monolithic columns under realistic application conditions. Several specifications, such as (dynamic) IgG capacity, pressure stability, long-term performance, productivity, non-specific binding, and peak shape, are presented. It could be shown that due to the very high separation speed, 250 mg antibody per hour and column can be collected, which surpasses the productivity of most standard columns of the same size. The total IgG capacity of the shown columns is around 4 mg (5.5 mg/mL), which is sufficient for most tasks in research laboratories. The cycle time of an IgG separation can be less than 1 min. Due to the glass material’s excellent pressure resistance, these columns are compatible with standard HPLC systems. This is usually not the case with standard affinity columns, limited to manual use or application in low-pressure systems. The use of a standard HPLC system also improves the ability for automation, which enables the purification of hundreds of cell supernatants in one day. The sharp peak shape of the elution leads to an enrichment effect, which might increase the concentration of IgG by a factor of 3. The final concentration of IgG can be around 7.5 mg/mL without the need for an additional nano-filtration step. The purity of the IgG was > 95% in one step and nearly 99% with a second polishing run. KW - Affinity Chromatography KW - Affinity Extraction KW - Affinity Separation KW - Protein Purification KW - Down Stream Processing KW - Antibody Purification KW - Diagnostic Antibodies KW - Therapeutic Antibodies KW - Automated Purification KW - HPLC KW - FPLC KW - IgG determination KW - Concentration step KW - Monoclonal Antibodies KW - Polyclonal Antibodies KW - Human Plasma KW - Glass Support KW - Borosilicate Glass KW - Monolith KW - Sintered Material KW - Additive Manufacturing KW - Column holder KW - Construction KW - Open Science KW - Citizen Science KW - Protein A KW - Regeneration KW - High-Speed Separations KW - Robustness PY - 2021 UR - https://nbn-resolving.org/urn:nbn:de:kobv:b43-527581 DO - https://doi.org/10.3390/separations8050056 SN - 2297-8739 VL - 8 IS - 5 SP - 1 EP - 16 PB - MDPI CY - Basel AN - OPUS4-52758 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - JOUR A1 - Cakir, Cafer Tufan A1 - Piotrowiak, T. A1 - Reinholz, Uwe A1 - Ludwig, A. A1 - Emmerling, Franziska A1 - Streli, C. A1 - de Oliveira Guilherme Buzanich, Ana A1 - Radtke, Martin T1 - Exploring the Depths of Corrosion: A Novel GE-XANES Technique for Investigating Compositionally Complex Alloys N2 - In this study, we propose the use of nondestructive, depth-resolved, element-specific characterization using grazing exit X-ray absorption near-edge structure spectroscopy (GE-XANES) to investigate the corrosion process in compositionally complex alloys (CCAs). By combining grazing exit X-ray fluorescence spectroscopy (GE-XRF) geometry and a pnCCD detector, we provide a scanning-free, nondestructive, depth-resolved analysis in a sub-micrometer depth range, which is especially relevant for layered materials, such as corroded CCAs. Our setup allows for spatial and energy-resolved measurements and directly extracts the desired fluorescence line, free from scattering events and other overlapping lines. We demonstrate the potential of our approach on a compositionally complex CrCoNi alloy and a layered reference sample with known composition and specific layer thickness. Our findings indicate that this new GE-XANES approach has exciting opportunities for studying surface catalysis and corrosion processes in real-world materials. KW - Degradation mechanisms KW - Grazin exit XANES KW - Depth resolved XANES KW - Compositional complex alloys KW - Corrosion PY - 2023 DO - https://doi.org/10.1021/acs.analchem.3c00404 VL - 95 SP - 4810 EP - 4818 PB - ACS Publications AN - OPUS4-57823 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Radnik, Jörg T1 - Interlaboratory comparisons as tool in advanced materials characterisation N2 - Interlaboratory comparisons (ILCs) are an important tool for the validation of characterisation methods, and, herwith, a prerequisite for standardisation. The "Versailles Project on Advanced Materials and Standards" offers a framework for performing such ILCs: (i) TiO2 nanoparticles using ToF-SIMS, and (ii) the chemical composition of functionalized graphene using XPS. The results of both ILCs underline the importance of sample preparation for the measured results. T2 - NanoMeasure France Meeting CY - Online meeting DA - 07.06.2024 KW - Standardisation KW - Validation KW - Interlaboratory comparison KW - Graphene related 2D materials KW - Titania nanoparticles PY - 2024 AN - OPUS4-60532 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - JOUR A1 - George, Janine A1 - Petretto, G. A1 - Naik, Aakash Ashok A1 - Esters, M. A1 - Jackson, A. J. A1 - Nelson, R. A1 - Dronskowski, R. A1 - Rignanese, G.-M. A1 - Hautier, G. T1 - Cover profile for the article "Automated bonding analysis with crystal orbital Hamilton populuations" N2 - Invited for this month’s cover are researchers from Bundesanstalt für Materialforschung und -prüfung (Federal Institute for Materials Research and Testing) in Germany, Friedrich Schiller University Jena, Université catholique de Louvain, University of Oregon, Science & Technology Facilities Council, RWTH Aachen University, Hoffmann Institute of Advanced Materials, and Dartmouth College. The cover picture shows a workflow for automatic bonding analysis with Python tools (green python). The bonding analysis itself is performed with the program LOBSTER (red lobster). The starting point is a crystal structure, and the results are automatic assessments of the bonding situation based on Crystal Orbital Hamilton Populations (COHP), including automatic plots and text outputs. Coordination environments and charges are also assessed. More information can be found in the Research Article by J. George, G. Hautier, and co-workers. KW - Automation KW - Chemical bonds KW - High-throughput PY - 2022 DO - https://doi.org/10.1002/cplu.202200246 SN - 2192-6506 SP - 1 EP - 2 PB - Wiley-VCH CY - Weinheim AN - OPUS4-55557 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Naik, Aakash Ashok A1 - George, Janine T1 - New descriptors for materials properties based on bonding indicators N2 - Includes a summary of the Ph.D. project that deals with generating a database populated with materials bonding properties and how we intend to gain deeper insights into material properties through this research. T2 - SALSA 2022 CY - Berlin, Germany DA - 15.09.2022 KW - Bonding analysis KW - Automation KW - Materials Informatics KW - Computational Chemistry PY - 2022 AN - OPUS4-56142 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - GEN A1 - Naik, Aakash Ashok A1 - Ertural, Christina A1 - Dhamrait, Nidal A1 - Benner, Phillip A1 - George, Janine T1 - Quantum-Chemical Bonding Database (Unprocessed data : Part 5) N2 - This data is associated with the manuscript "A Quantum-Chemical Bonding Database for Solid-State Materials." Refer to mpids.txt to see data related to which compounds are available in the tar file. (mp-xxx refer to Materials Project ID) KW - Bonding analysis KW - Automation KW - Materials Informatics KW - Computational Chemistry KW - Database PY - 2023 DO - https://doi.org/10.5281/zenodo.7852806 PB - Zenodo CY - Geneva AN - OPUS4-57445 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - GEN A1 - Naik, Aakash Ashok A1 - Ertural, Christina A1 - Dhamrait, Nidal A1 - Benner, Phillip A1 - George, Janine T1 - Quantum-Chemical Bonding Database (Unprocessed data : Part 4) N2 - This data is associated with the manuscript "A Quantum-Chemical Bonding Database for Solid-State Materials." Refer to mpids.txt to see data related to which compounds are available in the tar file. (mp-xxx refer to Materials Project ID) KW - Bonding analysis KW - Automation KW - Materials Informatics KW - Computational Chemistry KW - Database PY - 2023 DO - https://doi.org/10.5281/zenodo.7852798 PB - Zenodo CY - Geneva AN - OPUS4-57444 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - JOUR A1 - Lutz, C. A1 - Hampel, S. A1 - Ke, X. A1 - Beuermann, S. A1 - Turek, T. A1 - Kunz, U. A1 - de Oliveira Guilherme Buzanich, Ana A1 - Radtke, Martin A1 - Fittschen, U. T1 - Evidence for redox reactions during vanadium crossover inside the nanoscopic water-body of Nafion 117 using X-ray absorption near edge structure spectroscopy N2 - A major source of capacity fade of the common vanadium redox flow battery (VRFB) is the vanadium ion transport through the separator. However, different transport models disagree significantly in the diffusion coefficient for the different V species and the influence of different transport mechanisms. The underlying hypothesis of this work is that reactions inside the membrane are partly responsible for these discrepancies. Accordingly, it was investigated if redox reactions inside the nanoscopic water body of Nafion 117 can occur. X-ray absorption near edge structure spectroscopy (XANES) was used to distinguish between the different V species inside hydrated Nafion 117 and novel PVDF-based membranes. It was validated that the speciation of vanadium can be performed using the pre-edge peak energy and intensity. The experiments were performed as follows: strips of the membrane were exposed from one site to a V3+ solution (green) and from the other site to a VO2+ solution (yellow). The ions could diffuse into the membrane from both sides. A change of color of the membrane strip was observed. The blue color in the middle of the strip indicated that VO2+ was formed where V3+ and VO2+ got in contact. Using XANES this reaction inside Nafion was proven. KW - PVDF-Based membrane KW - VRFB KW - Vanadium speciation KW - XANES KW - Nafion 117 PY - 2020 DO - https://doi.org/10.1016/j.jpowsour.2020.229176 VL - 483 SP - 229176 PB - Elsevier B.V. AN - OPUS4-51719 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Ertural, Christina A1 - Deringer, V. L. A1 - George, Janine T1 - Automation of machine learning driven interatomic potential generation for predicting vibrational properties N2 - Investigating the phononic properties is beneficial for predicting low thermal conductivity thermoelectric materials.1–3 Employing density functional theory4 takes many calculation steps and consumes a lot of computational resources.5,6 Using machine learning driven interatomic potentials (MLIP, e.g., Gaussian approximation potential,8 GAP) opens up a faster route to phonons7 but in most cases, the potentials are specifically tailored for a certain compound. In this work, we automate the generation of such MLIPs in a Python code-based workflow, based on the automation tools atomate29 and pymatgen10 which combines the automatic DFT computations with the automated fitting of GAPs. Automation enables easier testing, benchmarking and validation.11 We aim to provide the workflow-generated potentials for storage in databases. T2 - 16th International conference on materials chemistry (MC16) CY - Dublin, Ireland DA - 03.07.2023 KW - Interatomic potentials KW - Machine learning KW - Phonons KW - Thermoelectrics PY - 2023 AN - OPUS4-57932 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Yusenko, Kirill A1 - de Oliveira Guilherme Buzanich, Ana A1 - Radtke, Martin A1 - Reinholz, Uwe A1 - Riesemeier, Heinrich A1 - Emmerling, Franziska T1 - BAMline 2.0 – further technical developments for a broader multipurpose hard X-ray beamline at BESSY II N2 - We show further development of our beamline in the contexst of further itermational collaboration. T2 - PACC and AfSC CY - Accra, Ghana DA - 28.01.2019 KW - Synchrotron radiation PY - 2019 AN - OPUS4-47317 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Pauw, Brian Richard A1 - Laskina, Sofya A1 - Naik, Aakash Ashok A1 - Smales, Glen Jacob A1 - George, Janine T1 - “Ultima Ratio”: Multi-scale, high-resolution 3D-FFT scattering pattern simulations N2 - This talk highlights a proof-of-concept that demonstrates the ability to calculate high-resolution Fourier transforms. These can be combined with multi-scale modeling to simulate scattering over a wide range, from small-angle scattering to XRD and PDF. T2 - Shapespyer/MuSSIC launch workshop CY - Didcot, UK DA - 20.02.2023 KW - X-ray scattering KW - Simulation KW - Fourier Transform KW - 3D KW - High resolution KW - Multi-scale PY - 2023 AN - OPUS4-57031 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Naik, Aakash Ashok A1 - George, Janine T1 - Building quantum chemical orbital based bonding descriptor database N2 - Motivation, methodology and and results of our quantum chemical bonding descriptors database presented in form of a Poster T2 - RSC Twitter Conference 2023 CY - Online meeting DA - 28.02.2023 KW - Bonding analysis KW - Automation KW - Materials Informatics KW - Computational Chemistry KW - Database PY - 2023 UR - https://twitter.com/NaikAak/status/1630400167080869893 UR - https://twitter.com/NaikAak/status/1630540436434558977 AN - OPUS4-57101 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - George, Janine T1 - Automation in Computational Materials Science N2 - This lecture illustrated the current state of automation in the field of computational materials science based on recent examples from my research. T2 - NOA Lecture Series FSU Jena CY - Jena, Germany DA - 02.11.2021 KW - Data analysis KW - Machine learning KW - High-throughput computations PY - 2021 AN - OPUS4-54089 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - JOUR A1 - George, Janine T1 - Automation in DFT-based computational materials science N2 - Automation simplifies the use of computational materials science software and makes it accessible to a wide range of users. This enables high-throughput calcula-tionsand makesiteasier for non-specialists to enter computational materials science. However, in-creasing automation also poses threats that should be considered while interacting with automated procedures. KW - DFT KW - Automation KW - High-throughput computations PY - 2021 DO - https://doi.org/10.1016/j.trechm.2021.07.001 SN - 2589-5974 VL - 3 IS - 9 SP - 697 EP - 699 PB - Elsevier CY - Amsterdam AN - OPUS4-53127 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - de Oliveira Guilherme Buzanich, Ana A1 - Michalchuk, Adam A1 - Cakir, Cafer Tufan A1 - Yusenko, Kirill A1 - Radtke, Martin A1 - Reinholz, U. A1 - Emmerling, Franziska T1 - Time resolved in situ monitoring of mechanochemical transformations by X-ray spectroscopy (XAS) N2 - Mechanochemical reactions promise a new direction for environmentally benign preparation of materials, and has been dubbed by IUPAC as one of the 10 chemical innovations that will change our world. Despite this significant promise, very little is known about the mechanisms that drive mechanochemical transformations, posing significant barriers to realizing their full potential. To this end, there is growing need to follow mechanochemical reactions in situ and in real time. We here describe advances in the development and application of XAS methods to monitor material synthesis in real time under mechanochemical conditions. We demonstrate the generality of our approaches by describing mechanochemical syntheses of materials by both vibratory ball milling and by Resonant Acoustic Mixing (RAM), where a time resolution of 1 second is for a whole XAS spectrum was achieved. Moreover, we describe how spectroscopic methods can be coupled to diffraction-based approaches, thereby providing new dimensions in understanding mechanochemical synthesis. T2 - Denver X-ray Conference: DXC 2021 CY - Online meeting DA - 02.08.2021 KW - Dispersive XAS KW - Mechanochemistry KW - Time resolved KW - In situ PY - 2021 AN - OPUS4-56257 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - de Oliveira Guilherme Buzanich, Ana A1 - Michalchuk, Adam A1 - Cakir, Cafer Tufan A1 - Haider, M. B. A1 - Yusenko, Kirill A1 - Radtke, Martin A1 - Reinholz, U. A1 - Emmerling, Franziska T1 - Time resolved in situ monitoring of mechanochemical transformations by X-ray spectroscopy (XAS) N2 - Mechanochemical reactions promise a new direction for environmentally benign preparation of materials, and has been dubbed by IUPAC as one of the 10 chemical innovations that will change our world. Despite this significant promise, very little is known about the mechanisms that drive mechanochemical transformations, posing significant barriers to realizing their full potential. To this end, there is growing need to follow mechanochemical reactions in situ and in real time. We here describe advances in the development and application of XAS methods to monitor material synthesis in real time under mechanochemical conditions. We demonstrate the generality of our approaches by describing mechanochemical syntheses of materials by both vibratory ball milling and by Resonant Acoustic Mixing (RAM), where a time resolution of 1 second is for a whole XAS spectrum was achieved. Moreover, we describe how spectroscopic methods can be coupled to diffraction-based approaches, thereby providing new dimensions in understanding mechanochemical synthesis. T2 - AfLS3 CY - Online meeting DA - 14.11.2021 KW - Dipsersive XAS KW - Mechanochemistry KW - Time-resolved KW - In situ PY - 2021 AN - OPUS4-56256 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER -