Accelerating Materials Discovery Using Synthetic Intelligence, High Overall Performance Computing, And Robotics
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Abstract
New gear permits new operating methods, and materials and technological know-how are no exception. In materials discovery, traditional manual, serial, and human-extensive work is being augmented by automated, parallel, and iterative strategies driven by artificial Intelligence (AI), simulation, and experimental automation. From this perspective, we describe how these new abilities permit the acceleration and enrichment of each stage of the invention cycle. We display the use of the example of the improvement of a singular chemically amplified photoresist and how these technology's influences are amplified. At the same time, they're utilized in live performance with each other as effective, heterogeneous workflows.
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