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.

Talk to us

Join us for a 30 min session where you can share your feedback and ask us any queries you have

Schedule a call

Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.