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dc.creator Pyzer-Knapp, Edward O.
dc.creator Pitera, Jed W.
dc.creator Staar, Peter W. J.
dc.creator Takeda, Seiji
dc.creator Laino, Teodoro
dc.creator Sanders, Daniel P.
dc.creator Sexton, James
dc.creator Smith, John R.
dc.creator Curioni, Alessandro
dc.date.accessioned 2025-04-08T21:19:31Z
dc.date.available 2025-04-08T21:19:31Z
dc.date.issued 2022
dc.identifier.uri http://hdl.handle.net/123456789/15581
dc.description.abstract 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. es
dc.format.extent 9 p. es
dc.relation.ispartof npj Comput Mater, (8)84. es
dc.title Accelerating materials discovery using artificial intelligence, high performance computing and robotics es
dc.type ArtRev es
uade.subject.keyword Ciencia de los Materiales es
uade.subject.descriptor Inteligencia Artificial es
uade.subject.descriptor Robótica es
uade.subject.descriptor Informática es
uade.subject.descriptor Computación es
academic.materia.codigo 3.3.195 es
academic.materia.nombre Tecnología de los Materiales es


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