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Evolving the Materials Genome: How Machine Learning Is Fueling the Next Generation of Materials Discovery
2020
Annual review of materials research (Print)
Machine learning, applied to chemical and materials data, is transforming the field of materials discovery and design, yet significant work is still required to fully take advantage of machine learning algorithms, tools, and methods. Here, we review the accomplishments to date of the community and assess the maturity of state-of-the-art, data-intensive research activities that combine perspectives from materials science and chemistry. We focus on three major themes—learning to see, learning to
doi:10.1146/annurev-matsci-082019-105100
fatcat:dyxljg2mu5grzlakeeatvyymd4