TY - CHAP A1 - Radtke, Martin A1 - Reinholz, Uwe A1 - Guerra, M.F. A1 - Martinón-Torres, M. A1 - Lemasson, Q. A1 - Moignard, B. A1 - Pacheco, C. A1 - Pichon, L. A1 - Macdonald, L. A1 - Hess, M. A1 - Tissot, I. ED - Guerra, M. F. ED - Martinón-Torres, M. ED - Quirke, S. T1 - Analytical approaches to Egyptian goldwork N2 - The structure and composition of ancient gold objects retain information about their long history of manufacture, from the exploitation of the ore to the finishing touches, as well as evidence of their use, deposition, and degradation. By developing an efficient analytical strategy, it is possible to retrieve that information. This chapter sets the necessary foundation 131to explore fully the analytical results presented in the following chapters of this volume. The techniques employed in the analyses of the Egyptian jewellery are described and the analytical parameters provided. For more established techniques, only brief introductions are presented, while more recent developments are presented in greater detail. KW - Gold KW - Synchrotron KW - D2XRF KW - Egypt PY - 2023 UR - https://nbn-resolving.org/urn:nbn:de:kobv:b43-586039 DO - https://doi.org/10.17863/CAM.99681 SP - 131 EP - 191 AN - OPUS4-58603 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - JOUR A1 - Naik, Aakash A1 - Ertural, Christina A1 - Dhamrait, Nidal A1 - Benner, Philipp A1 - George, Janine T1 - A Quantum-Chemical Bonding Database for Solid-State Materials N2 - An in-depth insight into the chemistry and nature of the individual chemical bonds is essential for understanding materials. Bonding analysis is thus expected to provide important features for large-scale data analysis and machine learning of material properties. Such chemical bonding information can be computed using the LOBSTER software package, which post-processes modern density functional theory data by projecting the plane wave-based wave functions onto an atomic orbital basis. With the help of a fully automatic workflow, the VASP and LOBSTER software packages are used to generate the data. We then perform bonding analyses on 1520 compounds (insulators and semiconductors) and provide the results as a database. The projected densities of states and bonding indicators are benchmarked on standard density-functional theory computations and available heuristics, respectively. Lastly, we illustrate the predictive power of bonding descriptors by constructing a machine learning model for phononic properties, which shows an increase in prediction accuracies by 27% (mean absolute errors) compared to a benchmark model differing only by not relying on any quantum-chemical bonding features. KW - Bonding Analysis KW - DFT KW - High-throughput KW - Database KW - Phonons KW - Machine Learning PY - 2023 UR - https://nbn-resolving.org/urn:nbn:de:kobv:b43-582892 DO - https://doi.org/10.1038/s41597-023-02477-5 VL - 10 IS - 1 SP - 1 EP - 18 AN - OPUS4-58289 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - GEN A1 - Ghosh, Sheuly A1 - Ueltzen, Katharina A1 - George, Janine A1 - Neugebauer, Jörg A1 - Körmann, Fritz T1 - Chemical ordering and magnetism in face-centered cubic CrCoNi alloy N2 - The impact of magnetism on chemical ordering in face-centered cubic CrCoNi medium entropy alloy is studied by a combination of ab initio simulations, machine learning potentials, and Monte Carlo simulations. Large magnetic energies are revealed for some mixed L12 /L10 type ordered configurations, which are rooted in strong nearest-neighbor magnetic exchange interactions and chemical bonding among the constituent elements. There is a delicate interplay between magnetism and stability of MoPt2 and L12 /L10 type of ordering which may explain opposing experimental and theoretical findings. KW - Bonding analysis KW - Alloys KW - Magnetism KW - Material design PY - 2024 UR - https://nbn-resolving.org/urn:nbn:de:kobv:b43-600040 DO - https://doi.org/10.21203/rs.3.rs-3978660/v1 SN - 2693-5015 SP - 1 EP - 13 PB - Research Square Platform LLC CY - Durham, NC AN - OPUS4-60004 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - INPR A1 - Pauw, Brian Richard A1 - Smales, Glen Jacob A1 - Anker, A. S. A1 - Balazs, D. M. A1 - Beyer, F. L. A1 - Bienert, Ralf A1 - Bouwman, W. G. A1 - Breßler, Ingo A1 - Breternitz, J. A1 - Brok, E. S. A1 - Bryant, G. A1 - Clulow, A. J. A1 - Crater, E. R. A1 - De Geuser, F. A1 - Giudice, A. D. A1 - Deumer, J. A1 - Disch, S. A1 - Dutt, S. A1 - Frank, K. A1 - Fratini, E. A1 - Gilbert, E. P. A1 - Hahn, Marc Benjamin A1 - Hallett, J. A1 - Hohenschutz, Max A1 - Hollamby, M. J. A1 - Huband, S. A1 - Ilavsky, J. A1 - Jochum, J. K. A1 - Juelsholt, M. A1 - Mansel, B. W. A1 - Penttilä, P. A1 - Pittkowski, R. K. A1 - Portale, G. A1 - Pozzo, L. D. A1 - Ricardo de Abreu Furtado Garcia, P. A1 - Rochels, L. A1 - Rosalie, Julian M. A1 - Saloga, P. E. J. A1 - Seibt, S. A1 - Smith, A. J. A1 - Smith, G. N. A1 - Annadurai, V. A1 - Spiering, G. A. A1 - Stawski, Tomasz A1 - Taché, O. A1 - Thünemann, Andreas A1 - Toth, K. A1 - Whitten, A. E. A1 - Wuttke, J. T1 - The human factor - Results of a small-angle scattering data analysis round robin N2 - A Round Robin study has been carried out to estimate the impact of the human element in small-angle scattering data analysis. Four corrected datasets were provided to participants ready for analysis. All datasets were measured on samples containing spherical scatterers, with two datasets in dilute dispersions, and two from powders. Most of the 46 participants correctly identified the number of populations in the dilute dispersions, with half of the population mean entries within 1.5 % and half of the population width entries within 40 %, respectively. Due to the added complexity of the structure factor, much fewer people submitted answers on the powder datasets. For those that did, half of the entries for the means and widths were within 44 % and 86 % respectively. This Round Robin experiment highlights several causes for the discrepancies, for which solutions are proposed. KW - Round robin KW - Sall-angle scattering KW - Nanostructure quantification KW - Nanostructure KW - SAXS KW - MOUSE KW - X-ray scattering KW - Size distribution KW - Nanoparticles PY - 2023 UR - https://nbn-resolving.org/urn:nbn:de:kobv:b43-571342 DO - https://doi.org/10.48550/arXiv.2303.03772 SP - 1 EP - 23 PB - Cornell University CY - Ithaca, NY AN - OPUS4-57134 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - JOUR A1 - Naik, Aakash Ashok A1 - Ueltzen, Katharina A1 - Ertural, Christina A1 - Jackson, Adam J. A1 - George, Janine T1 - LobsterPy: A package to automatically analyze LOBSTERruns N2 - The LOBSTER (Deringer et al., 2011;Maintz et al., 2013 ,2016 ;Nelson et al., 2020 ) software aids in extracting quantum-chemical bonding information from materials by projecting the plane-wave based wave functions from density functional theory (DFT) onto an atomic orbital basis. LobsterEnv, a module implemented in pymatgen (Ong et al., 2013) by some of the authors of this package, facilitates the use of quantum-chemical bonding information obtained from LOBSTER calculations to identify neighbors and coordination environments. LobsterPy is a Python package that offers a set of convenient tools to further analyze and summarize the LobsterEnv outputs in the form of JSONs that are easy to interpret and process. These tools enable the estimation of (anti) bonding contributions, generation of textual descriptions, and visualization of LOBSTER computation results. Since its first release, both LobsterPy and LobsterEnv capabilities have been extended significantly. Unlike earlier versions, which could only automatically analyze Crystal Orbital Hamilton Populations (COHPs) (Dronskowski & Blöchl, 1993), both can now also analyze Crystal Orbital Overlap Populations (COOP) (Hughbanks & Hoffmann, 1983) and Crystal Orbital Bond Index (COBI) (Müller et al., 2021). Extracting the information about the most important orbitals contributing to the bonds is optional, and users can enable it as needed. Additionally, bonding-based features for machinelearning (ML) studies can be engineered via the sub-packages “featurize” and “structuregraphs”. Alongside its Python interface, it also provides an easy-to-use command line interface (CLI) that runs automatic analysis of the computations and generates a summary of results and publication-ready figures. LobsterPy has been used to produce the results in Ngo et al. (2023), Chen et al. (2024), Naik et al. (2023), and it is also part of Atomate2 (2023) bonding analysis workflow for generating bonding analysis data in a format compatible with the Materials Project (Jain et al., 2013) API. KW - Materials Science KW - Automation KW - Bonding Analysis KW - Materials Properties PY - 2024 UR - https://nbn-resolving.org/urn:nbn:de:kobv:b43-595809 DO - https://doi.org/10.21105/joss.06286 VL - 9 IS - 94 SP - 1 EP - 4 PB - The Open Journal AN - OPUS4-59580 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - JOUR A1 - Rosen, Andrew S. A1 - Gallant, Max A1 - George, Janine A1 - Riebesell, Janosh A1 - Sahasrabuddhe, Hrushikesh A1 - Shen, Jimmy-Xuan A1 - Wen, Mingjian A1 - Evans, Matthew L. A1 - Petretto, Guido A1 - Waroquiers, David A1 - Rignanese, Gian-Marco A1 - Persson, Kristin A. A1 - Jain, Anubhav A1 - Ganose, Alex M. T1 - Jobflow: Computational Workflows Made Simple N2 - We present Jobflow, a domain-agnostic Python package for writing computational workflows tailored for high-throughput computing applications. With its simple decorator-based approach, functions and class methods can be transformed into compute jobs that can be stitched together into complex workflows. Jobflow fully supports dynamic workflows where the full acyclic graph of compute jobs is not known until runtime, such as compute jobs that launch other jobs based on the results of previous steps in the workflow. The results of all Jobflow compute jobs can be easily stored in a variety of filesystem- and cloud-based databases without the data storage process being part of the underlying workflow logic itself. Jobflow has been intentionally designed to be fully independent of the choice of workflow manager used to dispatch the calculations on remote computing resources. At the time of writing, Jobflow workflows can be executed either locally or across distributed compute environments via an adapter to the FireWorks package, and Jobflow fully supports the integration of additional workflow execution adapters in the future. KW - Automation KW - Workflow KW - Computational Materials Science KW - Computations KW - Software PY - 2024 UR - https://nbn-resolving.org/urn:nbn:de:kobv:b43-593104 DO - https://doi.org/10.21105/joss.05995 VL - 9 IS - 93 SP - 1 EP - 7 PB - The Open Journal AN - OPUS4-59310 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - JOUR A1 - Smales, Glen Jacob A1 - Pauw, Brian Richard T1 - The MOUSE project - A meticulous approach for obtaining traceable, wide-range X-ray scattering information N2 - Herein, we provide a "systems architecture"-like overview and detailed discussions of the methodological and instrumental components that, together, comprise the "MOUSE" project (Methodology Optimization for UltrafineStructure Exploration). The MOUSE project provides scattering information on a wide variety of samples, with traceable dimensions for both the scattering vector (q) and the absolute scattering cross-section (I). The measurable scattering vector-range of 0.012≤ q (nm-1) ≤ 92, allows information across a hierarchy of structures with dimensions ranging from ca. 0.1 to 400 nm. In addition to details that comprise the MOUSE project, such as the organisation and traceable aspects, several representative examples are provided to demonstrate its flexibility. These include measurements on alumina membranes, the tobacco mosaic virus, and dual-source information that overcomes fluorescence limitations on ZIF-8 and iron-oxide-containing carbon catalyst materials. KW - X-ray scattering KW - MOUSE KW - Instrumentation KW - SAXS KW - Methodology KW - Traceability KW - Wide-range KW - Data curation KW - FAIR KW - Uncertainties KW - Nanomaterials KW - Nanometrology PY - 2021 UR - https://nbn-resolving.org/urn:nbn:de:kobv:b43-528669 DO - https://doi.org/10.1088/1748-0221/16/06/P06034 VL - 16 IS - 6 SP - 1 EP - 50 PB - IOP CY - Bristol, UK AN - OPUS4-52866 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - JOUR A1 - Pauw, Brian Richard A1 - Smales, Glen Jacob A1 - Anker, A. S. A1 - Annadurai, V. A1 - Balazs, D. M. A1 - Bienert, Ralf A1 - Bouwman, W. G. A1 - Breßler, Ingo A1 - Breternitz, J. A1 - Brok, E. S. A1 - Bryant, G. A1 - Clulow, A. J. A1 - Crater, E. R. A1 - De Geuser, F. A1 - Del Giudice, A. A1 - Deumer, J. A1 - Disch, S. A1 - Dutt, S. A1 - Frank, K. A1 - Fratini, E. A1 - Garcia, P. R. A. F. A1 - Gilbert, E. P. A1 - Hahn, Marc Benjamin A1 - Hallett, J. A1 - Hohenschutz, M. A1 - Hollamby, M. A1 - Huband, S. A1 - Ilavsky, J. A1 - Jochum, J. K. A1 - Juelsholt, M. A1 - Mansel, B. W. A1 - Penttilä, P. A1 - Pittkowski, R. K. A1 - Portale, G. A1 - Pozzo, L. D. A1 - Rochels, L. A1 - Rosalie, Julian M. A1 - Saloga, Patrick E. J. A1 - Seibt, S. A1 - Smith, A. J. A1 - Smith, G. N. A1 - Spiering, G. A. A1 - Stawski, Tomasz M. A1 - Taché, O. A1 - Thünemann, Andreas A1 - Toth, K. A1 - Whitten, A. E. A1 - Wuttke, J. T1 - The human factor - Results of a small-angle scattering data analysis round robin N2 - A round-robin study has been carried out to estimate the impact of the human element in small-angle scattering data analysis. Four corrected datasets were provided to participants ready for analysis. All datasets were measured on samples containing spherical scatterers, with two datasets in dilute dispersions and two from powders. Most of the 46 participants correctly identified the number of populations in the dilute dispersions, with half of the population mean entries within 1.5% and half of the population width entries within 40%. Due to the added complexity of the structure factor, far fewer people submitted answers on the powder datasets. For those that did, half of the entries for the means and widths were within 44 and 86%, respectively. This round-robin experiment highlights several causes for the discrepancies, for which solutions are proposed. KW - Round Robin KW - Data analysis KW - Small-angle scattering KW - Nanomaterials KW - Interlaboratory comparability KW - Nanostructure quantification KW - Methodology KW - MOUSE PY - 2023 UR - https://nbn-resolving.org/urn:nbn:de:kobv:b43-587091 DO - https://doi.org/10.1107/S1600576723008324 SN - 1600-5767 VL - 56 IS - 6 SP - 1618 EP - 1629 PB - Wiley-Blackwell CY - Oxford AN - OPUS4-58709 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - GEN A1 - Pauw, Brian Richard A1 - Smales, Glen Jacob T1 - Complete set of raw and processed datasets, as well as associated Jupyter notebooks for analysis, associated with manuscript entitled: "The MOUSE project: a practical approach for obtaining traceable, wide-range X-ray scattering information" N2 - This dataset is a complete set of raw, processed and analyzed data, complete with Jupiter notebooks, associated with the manuscript mentioned in the title. In the manuscript, we provide a "systems architecture"-like overview and detailed discussions of the methodological and instrumental components that, together, comprise the "MOUSE" project (Methodology Optimization for Ultrafine Structure Exploration). Through this project, we aim to provide a comprehensive methodology for obtaining the highest quality X-ray scattering information (at small and wide angles) from measurements on materials science samples. KW - X-ray scattering KW - Measurement methodology KW - Traceability derivation KW - Multi-scale measurements KW - Systems architecture KW - Nanomaterials PY - 2020 DO - https://doi.org/10.5281/zenodo.4312953 PB - Zenodo CY - Geneva AN - OPUS4-51825 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - GEN A1 - Pauw, Brian Richard A1 - Smales, Glen Jacob T1 - Small-angle scattering data analysis round robin dataset - Original for participants N2 - These are four datasets that were made available to the participants of the Small-angle Scattering data analysis round robin. The intent was to find out how comparable results from different researchers are, who analyse exactly the same processed, corrected dataset. In this repository, there are: 1) a PDF document with more details for the study, 2) the datasets for people to try and fit, 3) an Excel spreadsheet to document the results. Datasets 1 and 2 were modified from: Deumer, Jerome, & Gollwitzer, Christian. (2022). npSize_SAXS_data_PTB (Version 5) [Data set]. Zenodo. https://doi.org/10.5281/zenodo.5886834 Datasets 3 and 4 were collected in-house on the MOUSE instrument. KW - Round robin KW - SAXS KW - Small angle scattering KW - SANS KW - X-ray KW - Neutron KW - Human factor KW - Data analysis KW - Data fitting KW - Human influence PY - 2023 DO - https://doi.org/10.5281/zenodo.7506365 PB - Zenodo CY - Geneva AN - OPUS4-56799 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER -