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Roadmap on multiscale materials modeling

van der Giessen, Erik and Schultz, Peter A. and Bertin, Nicolas and Bulatov, Vasily V. and Cai, Wei and Csányi, Gábor and Foiles, Stephen M. and Geers, M. G. D. and González, Carlos and Hütter, Markus and Kim, Woo Kyun and Kochmann, Dennis M. and LLorca, Javier and Mattsson, Ann E. and Rottler, Jörg and Shluger, Alexander and Sills, Ryan B. and Steinbach, Ingo and Strachan, Alejandro and Tadmor, Ellad B (2020) Roadmap on multiscale materials modeling. Modelling and Simulation in Materials Science and Engineering, 28 (4). Art. No. 043001. ISSN 0965-0393.

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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.

Item Type:Article
Related URLs:
URLURL TypeDescription
van der Giessen, Erik0000-0002-8369-2254
Schultz, Peter A.0000-0002-0179-9710
Bertin, Nicolas0000-0002-1901-8767
Foiles, Stephen M.0000-0002-1907-454X
Kim, Woo Kyun0000-0002-1591-701X
Kochmann, Dennis M.0000-0002-9112-6615
LLorca, Javier0000-0002-3122-7879
Shluger, Alexander0000-0002-2488-0896
Steinbach, Ingo0000-0002-2834-1160
Strachan, Alejandro0000-0002-4174-9750
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).
Funding AgencyGrant Number
Korea Institute of Materials SciencePNK6410
Deutsche Forschungsgemeinschaft (DFG)SPP1713
Deutsche Forschungsgemeinschaft (DFG)STE 116/20-2
Subject Keywords:modeling and simulation, materials science, multiscale materials modeling
Issue or Number:4
Record Number:CaltechAUTHORS:20200323-095145619
Persistent URL:
Official Citation:Erik van der Giessen et al 2020 Modelling Simul. Mater. Sci. Eng. 28 043001
Usage Policy:No commercial reproduction, distribution, display or performance rights in this work are provided.
ID Code:102043
Deposited By: Tony Diaz
Deposited On:23 Mar 2020 17:12
Last Modified:24 Nov 2020 00:07

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