Work

Adoption of Image-Driven Machine Learning for Microstructure Characterization and Materials Design: A Perspective

Year: 2021

Type: article

Source: JOM

DOI: 10.1007/s11837-021-04805-9

Authors: Arun Baskaran, Elizabeth J. Kautz, Aritra Chowdhary, Wufei Ma, Bulent Yener, Daniel J. Lewis

Institutions: Rensselaer Polytechnic Institute, Pacific Northwest National Laboratory, GE Global Research (United States), Purdue University West Lafayette

Language: English

Topic: Machine Learning in Materials Science

Subfield: Materials Chemistry

Field: Materials Science

Domain: Physical Sciences

Open Access status: green

Funders: National Science Foundation, U.S. Department of Energy, Battelle, National Nuclear Security Administration, Division of Civil, Mechanical and Manufacturing Innovation, Pacific Northwest National Laboratory

Awards: DMREF: Adaptive Control of Microstructure from the Microscale to the Macroscale, G1756126698, G2988778103, G538270251, G5726405315, G575939937, G7468415492, G84288863

OpenAlex ID: W3162226899

FWCI: 1.212

Cites: 127

Cited by: 32

Related to: 10