Chemical reaction networks and opportunities for machine learning

Mingjian Wen; Evan Walter Clark Spotte-Smith; Samuel M Blau; Matthew J McDermott; Aditi S Krishnapriyan; Kristin A Persson

doi:10.1038/s43588-022-00369-z

Chemical reaction networks and opportunities for machine learning

Nat Comput Sci. 2023 Jan;3(1):12-24. doi: 10.1038/s43588-022-00369-z. Epub 2023 Jan 16.

Authors

Mingjian Wen^{1

2}, Evan Walter Clark Spotte-Smith^{3

4}, Samuel M Blau², Matthew J McDermott^{3

4}, Aditi S Krishnapriyan^{5

6

7}, Kristin A Persson^{8

9}

Affiliations

¹ Chemical and Biomolecular Engineering, University of Houston, Houston, TX, USA.
² Energy Technologies Area, Lawrence Berkeley National Laboratory, Berkeley, CA, USA.
³ Materials Science Division, Lawrence Berkeley National Laboratory, Berkeley, CA, USA.
⁴ Materials Science and Engineering, University of California, Berkeley, Berkeley, CA, USA.
⁵ Computational Research Division, Lawrence Berkeley National Laboratory, Berkeley, CA, USA.
⁶ Chemical and Biomolecular Engineering, University of California, Berkeley, Berkeley, CA, USA.
⁷ Electrical Engineering and Computer Science, University of California, Berkeley, Berkeley, CA, USA.
⁸ Materials Science and Engineering, University of California, Berkeley, Berkeley, CA, USA. kapersson@lbl.gov.
⁹ Molecular Foundry, Lawrence Berkeley National Laboratory, Berkeley, CA, USA. kapersson@lbl.gov.

PMID: 38177958
DOI: 10.1038/s43588-022-00369-z

Abstract

Chemical reaction networks (CRNs), defined by sets of species and possible reactions between them, are widely used to interrogate chemical systems. To capture increasingly complex phenomena, CRNs can be leveraged alongside data-driven methods and machine learning (ML). In this Perspective, we assess the diverse strategies available for CRN construction and analysis in pursuit of a wide range of scientific goals, discuss ML techniques currently being applied to CRNs and outline future CRN-ML approaches, presenting scientific and technical challenges to overcome.

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Review

Abstract

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