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Roadmap on data-centric materials science.

Model. Simul. Mater. Sci. Eng. 32:063301 (2024)
Verlagsversion DOI
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Creative Commons Lizenzvertrag
Open Access Green möglich sobald Postprint bei der ZB eingereicht worden ist.
Science is and always has been based on data, but the terms ‘data-centric’ and the ‘4th paradigm’ of materials research indicate a radical change in how information is retrieved, handled and research is performed. It signifies a transformative shift towards managing vast data collections, digital repositories, and innovative data analytics methods. The integration of artificial intelligence and its subset machine learning, has become pivotal in addressing all these challenges. This Roadmap on Data-Centric Materials Science explores fundamental concepts and methodologies, illustrating diverse applications in electronic-structure theory, soft matter theory, microstructure research, and experimental techniques like photoemission, atom probe tomography, and electron microscopy. While the roadmap delves into specific areas within the broad interdisciplinary field of materials science, the provided examples elucidate key concepts applicable to a wider range of topics. The discussed instances offer insights into addressing the multifaceted challenges encountered in contemporary materials research.
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Publikationstyp Artikel: Journalartikel
Dokumenttyp Review
Schlagwörter Centric ; Data ; Materials ; Molecular Simulations ; Roadmap ; Science; X-ray-scattering; Electron; Reconstruction; Nanostructure; Framework; Catalysis
ISSN (print) / ISBN 0965-0393
e-ISSN 1361-651X
Quellenangaben Band: 32, Heft: 6, Seiten: , Artikelnummer: 063301 Supplement: ,
Verlag Institute of Physics Publishing (IOP)
Verlagsort Temple Circus, Temple Way, Bristol Bs1 6be, England
Begutachtungsstatus Peer reviewed
Förderungen BiGmax, the Max Planck Society's Research Network on Big-Data-Driven Materials-Science