TY - CONF A1 - Souza Filho, I. A1 - Adam, Christian T1 - Fundamentals of the hydrogen plasma reduction of iron ores N2 - Hydrogen plasma treatment of iron ores or iron oxide containing wastes can be an efficient option to produce green iron e.g. for steel production. This way iron oxide is reduced to metallic iron in the liquid form by the highly reactive species that are formed in a hydrogen plasma. Hydrogen plasma can be used at the same time to remove undesired gangue elements. The presentation shows the experimental setup, shows first results of iron ore reduction by hydrogen plasma and gives an outlook for industrial application of the technology. T2 - European Academic Symposium on EAF steelmaking (EASES 2023) CY - Oulu, Finland DA - 05.06.2023 KW - Hydrogen KW - Plasma KW - Reduction PY - 2023 AN - OPUS4-57626 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - JOUR A1 - Ghiringhelli, Luca M. A1 - Baldauf, Carsten A1 - Bereau, Tristan A1 - Brockhauser, Sandor A1 - Carbogno, Christian A1 - Chamanara, Javad A1 - Cozzini, Stefano A1 - Curtarolo, Stefano A1 - Draxl, Claudia A1 - Dwaraknath, Shyam A1 - Fekete, Ádám A1 - Kermode, James A1 - Koch, Christoph T. A1 - Kühbach, Markus A1 - Ladines, Alvin Noe A1 - Lambrix, Patrick A1 - Himmer, Maja-Olivia A1 - Levchenko, Sergey V. A1 - Oliveira, Micael A1 - Michalchuk, Adam A1 - Miller, Ronald E. A1 - Onat, Berk A1 - Pavone, Pasquale A1 - Pizzi, Giovanni A1 - Regler, Benjamin A1 - Rignanese, Gian-Marco A1 - Schaarschmidt, Jörg A1 - Scheidgen, Markus A1 - Schneidewind, Astrid A1 - Sheveleva, Tatyana A1 - Su, Chuanxun A1 - Usvyat, Denis A1 - Valsson, Omar A1 - Wöll, Christof A1 - Scheffler, Matthias T1 - Shared metadata for data-centric materials science N2 - The expansive production of data in materials science, their widespread sharing and repurposing requires educated support and stewardship. In order to ensure that this need helps rather than hinders scientific work, the implementation of the FAIR-data principles (Findable, Accessible, Interoperable, and Reusable) must not be too narrow. Besides, the wider materials-science community ought to agree on the strategies to tackle the challenges that are specific to its data, both from computations and experiments. In this paper, we present the result of the discussions held at the workshop on “Shared Metadata and Data Formats for Big-Data Driven Materials Science”. We start from an operative definition of metadata, and the features that a FAIR-compliant metadata schema should have. We will mainly focus on computational materials-science data and propose a constructive approach for the FAIRification of the (meta)data related to ground-state and excited-states calculations, potential-energy sampling, and generalized workflows. Finally, challenges with the FAIRification of experimental (meta)data and materials-science ontologies are presented together with an outlook of how to meet them. KW - Library and Information Sciences KW - Statistics, Probability and Uncertainty KW - Computer Science Applications KW - Education KW - Information Systems KW - Statistics and Probability PY - 2023 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:kobv:b43-584846 VL - 10 IS - 1 SP - 1 EP - 18 PB - Springer Science and Business Media LLC AN - OPUS4-58484 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER -