Data-science driven autonomous process optimization.

Christensen, Melodie; Yunker, Lars P E; Adedeji, Folarin; Häse, Florian; Roch, Loïc M; Gensch, Tobias; Dos Passos Gomes, Gabriel; Zepel, Tara; Sigman, Matthew S; Aspuru-Guzik, Alán; Hein, Jason E

Christensen, Melodie; Yunker, Lars P E; Adedeji, Folarin; Häse, Florian; Roch, Loïc M; Gensch, Tobias; Dos Passos Gomes, Gabriel; Zepel, Tara; Sigman, Matthew S; Aspuru-Guzik, Alán; Hein, Jason E.

Afiliación

Christensen M; Department of Chemistry, University of British Columbia, Vancouver, BC, Canada.
Yunker LPE; Department of Process Research and Development, Merck & Co., Inc., Rahway, NJ, USA.
Adedeji F; Department of Chemistry, University of British Columbia, Vancouver, BC, Canada.
Häse F; Department of Process Research and Development, Merck & Co., Inc., Rahway, NJ, USA.
Roch LM; Department of Chemistry and Chemical Biology, Harvard University, Cambridge, MA, USA.
Gensch T; Department of Chemistry, University of Toronto, Toronto, ON, Canada.
Dos Passos Gomes G; Department of Computer Science, University of Toronto, Toronto, ON, Canada.
Zepel T; Vector Institute for Artificial Intelligence, Toronto, ON, Canada.
Sigman MS; ChemOS Sàrl, Lausanne, Vaud, Switzerland.
Aspuru-Guzik A; Department of Chemistry and Chemical Biology, Harvard University, Cambridge, MA, USA.
Hein JE; Department of Chemistry, University of Toronto, Toronto, ON, Canada.

Commun Chem ; 4(1): 112, 2021 Aug 02.

Article en En | MEDLINE | ID: mdl-36697524

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Texto completo: 1 Bases de datos: MEDLINE Idioma: En Revista: Commun Chem Año: 2021 Tipo del documento: Article País de afiliación: Canadá