Exploring the role of machine learning in materials science and engineering

In: Open access government, Band 40, Heft 1, S. 294-295

Abstract

Exploring the role of machine learning in materials science and engineering
In this paper, Professor Dane Morgan and Research Scientist Ryan Jacobs, from the University of Wisconsin, Madison, discuss their adventures in the field of machine learning in the areas of materials science and engineering. This paper gives a very brief and inevitably biased overview of machine learning (ML) in Materials Science and Engineering (MS&E), with examples taken from our own work with collaborators. We hope it conveys our excitement about the extraordinary potential of this new area of research. MS&E focuses on developing materials with desired properties. It has led to materials innovations that underlie much of modern society, from the transistors in computers to the batteries in cars and smartphones. In recent decades, major advances in algorithms, computing power, and data access have made ML tools extremely powerful.