Abstract
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.
Original language | English |
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Article number | 063301 |
Journal | Modelling and Simulation in Materials Science and Engineering |
Volume | 32 |
Issue number | 6 |
DOIs | |
State | Published - Sep 2024 |
Externally published | Yes |
Bibliographical note
Publisher Copyright:© 2024 The Author(s). Published by IOP Publishing Ltd.
Keywords
- centric
- data
- materials
- molecular simulations
- roadmap
- science
ASJC Scopus subject areas
- Modeling and Simulation
- General Materials Science
- Condensed Matter Physics
- Mechanics of Materials
- Computer Science Applications