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Roadmap on data-centric materials science.

Model. Simul. Mater. Sci. Eng. 32:063301 (2024)
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Open Access Green as soon as Postprint is submitted to ZB.
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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Publication type Article: Journal article
Document type Review
Keywords Centric ; Data ; Materials ; Molecular Simulations ; Roadmap ; Science; X-ray-scattering; Electron; Reconstruction; Nanostructure; Framework; Catalysis
ISSN (print) / ISBN 0965-0393
e-ISSN 1361-651X
Journal Modelling and Simulation in Materials Science and Engineering
Quellenangaben Volume: 32, Issue: 6, Pages: , Article Number: 063301 Supplement: ,
Publisher Institute of Physics Publishing (IOP)
Publishing Place Temple Circus, Temple Way, Bristol Bs1 6be, England
Reviewing status Peer reviewed
Institute(s) Helmholtz Artifical Intelligence Cooperation Unit (HAICU)
Grants BiGmax, the Max Planck Society's Research Network on Big-Data-Driven Materials-Science