Accelerating materials discovery using artificial intelligence, high performance computing and robotics

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作者
Edward O. Pyzer-Knapp
Jed W. Pitera
Peter W. J. Staar
Seiji Takeda
Teodoro Laino
Daniel P. Sanders
James Sexton
John R. Smith
Alessandro Curioni
机构
[1] IBM Research Europe - Daresbury,
[2] IBM Almaden Research Centre,undefined
[3] IBM Research Europe Zurich,undefined
[4] IBM Research Tokyo,undefined
[5] IBM Thomas J. Watson Research Centre,undefined
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摘要
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.
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