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Title: Data Science in Chemical Engineering: Applications to Molecular Science
Chemical engineering is being rapidly transformed by the tools of data science. On the horizon, artificial intelligence (AI) applications will impact a huge swath of our work, ranging from the discovery and design of new molecules to operations and manufacturing and many areas in between. Early adoption of data science, machine learning, and early examples of AI in chemical engineering has been rich with examples of molecular data science—the application tools for molecular discovery and property optimization at the atomic scale. We summarize key advances in this nascent subfield while introducing molecular data science for a broad chemical engineering readership. We introduce the field through the concept of a molecular data science life cycle and discuss relevant aspects of five distinct phases of this process: creation of curated data sets, molecular representations, data-driven property prediction, generation of new molecules, and feasibility and synthesizability considerations.  more » « less
Award ID(s):
1633216
PAR ID:
10279449
Author(s) / Creator(s):
; ; ;
Date Published:
Journal Name:
Annual Review of Chemical and Biomolecular Engineering
Volume:
12
Issue:
1
ISSN:
1947-5438
Page Range / eLocation ID:
15 to 37
Format(s):
Medium: X
Sponsoring Org:
National Science Foundation
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