From mechanism-based to data-driven approaches in materials science

Hiemer S, Zapperi S (2021)

Publication Type: Journal article, other

Publication year: 2021

Journal

Materials Theory SpringerOpen

Original Authors: Stefan Hiemer, Stefano Zapperi

Book Volume: 5

Article Number: 4

Issue: 1

DOI: 10.1186/s41313-021-00027-3

Abstract

A time-honored approach in theoretical materials science revolves around the search for basic mechanisms that should incorporate key feature of the phenomenon under investigation. Recent years have witnessed an explosion across areas of science of a data-driven approach fueled by recent advances in machine learning. Here we provide a brief perspective on the strengths and weaknesses of mechanism based and data-driven approaches in the context of the mechanics of materials. We discuss recent literature on dislocation dynamics, atomistic plasticity in glasses focusing on the empirical discovery of governing equations through artificial intelligence. We conclude highlighting the main open issues and suggesting possible improvements and future trajectories in the fields.

Authors with CRIS profile

Stefan Hiemer Lehrstuhl für Werkstoffsimulation

Additional Organisation(s)

Graduiertenkolleg 2423 Skalenübergreifende Bruchvorgänge: Integration von Mechanik, Materialwissenschaften, Mathematik, Chemie und Physik

Involved external institutions

Università degli studi di Milano IT Italy (IT)

How to cite

APA:

Hiemer, S., & Zapperi, S. (2021). From mechanism-based to data-driven approaches in materials science. Materials Theory, 5. https://doi.org/10.1186/s41313-021-00027-3

MLA:

Hiemer, Stefan, and Stefano Zapperi. "From mechanism-based to data-driven approaches in materials science." Materials Theory 5 (2021).

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