Kristin Schmidt, Hitoshi Osaki, et al.
SPIE Advanced Lithography 2016
New tools enable new ways of working, and materials science is no exception. In materials discovery, traditional manual, serial, and human-intensive work is being augmented by automated, parallel, and iterative processes driven by Artificial Intelligence (AI), simulation and experimental automation. In this perspective, we describe how these new capabilities enable the acceleration and enrichment of each stage of the discovery cycle. We show, using the example of the development of a novel chemically amplified photoresist, how these technologies’ impacts are amplified when they are used in concert with each other as powerful, heterogeneous workflows.
Kristin Schmidt, Hitoshi Osaki, et al.
SPIE Advanced Lithography 2016
José Miguel Hernández-Lobato, James Requeima, et al.
ICML 2017
Seiji Takeda, Toshiyuki Hama, et al.
KDD 2020
Clyde Fare, Peter Fenner, et al.
npj Computational Materials