Published June 2020 | Version Published
Journal Article Open

Roadmap on multiscale materials modeling

  • 1. ROR icon University of Groningen
  • 2. ROR icon Sandia National Laboratories
  • 3. ROR icon Lawrence Livermore National Laboratory
  • 4. ROR icon Stanford University
  • 5. ROR icon University of Cambridge
  • 6. ROR icon Eindhoven University of Technology
  • 7. ROR icon IMDEA Materials
  • 8. ROR icon Technical University of Madrid
  • 9. ROR icon University of Cincinnati
  • 10. ROR icon ETH Zurich
  • 11. ROR icon California Institute of Technology
  • 12. ROR icon Los Alamos National Laboratory
  • 13. ROR icon University of British Columbia
  • 14. ROR icon University College London
  • 15. ROR icon Sandia National Laboratories California
  • 16. ROR icon Ruhr University Bochum
  • 17. ROR icon Purdue University West Lafayette
  • 18. ROR icon University of Minnesota

Abstract

Modeling and simulation is transforming modern materials science, becoming an important tool for the discovery of new materials and material phenomena, for gaining insight into the processes that govern materials behavior, and, increasingly, for quantitative predictions that can be used as part of a design tool in full partnership with experimental synthesis and characterization. Modeling and simulation is the essential bridge from good science to good engineering, spanning from fundamental understanding of materials behavior to deliberate design of new materials technologies leveraging new properties and processes. This Roadmap presents a broad overview of the extensive impact computational modeling has had in materials science in the past few decades, and offers focused perspectives on where the path forward lies as this rapidly expanding field evolves to meet the challenges of the next few decades. The Roadmap offers perspectives on advances within disciplines as diverse as phase field methods to model mesoscale behavior and molecular dynamics methods to deduce the fundamental atomic-scale dynamical processes governing materials response, to the challenges involved in the interdisciplinary research that tackles complex materials problems where the governing phenomena span different scales of materials behavior requiring multiscale approaches. The shift from understanding fundamental materials behavior to development of quantitative approaches to explain and predict experimental observations requires advances in the methods and practice in simulations for reproducibility and reliability, and interacting with a computational ecosystem that integrates new theory development, innovative applications, and an increasingly integrated software and computational infrastructure that takes advantage of the increasingly powerful computational methods and computing hardware.

Additional Information

© 2020 The Author(s). Published by IOP Publishing Ltd. Original content from this work may be used under the terms of the Creative Commons Attribution 4.0 licence. Any further distribution of this work must maintain attribution to the author(s) and the title of the work, journal citation and DOI. Received 28 June 2019; Accepted 29 January 2020; Published 23 March 2020. The author would like to acknowledge support from the Fundamental Research Program of Korea Institute of Materials Science (PNK6410) and from the German Research Foundation (DFG) under the priority program SPP1713 (STE 116/20-2).

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Additional details

Identifiers

Eprint ID
102043
Resolver ID
CaltechAUTHORS:20200323-095145619

Funding

Korea Institute of Materials Science
PNK6410
Deutsche Forschungsgemeinschaft (DFG)
SPP1713
Deutsche Forschungsgemeinschaft (DFG)
STE 116/20-2

Dates

Created
2020-03-23
Created from EPrint's datestamp field
Updated
2022-07-12
Created from EPrint's last_modified field