The DOI matches its Crossref record; 547 of the 547 references it cites were found in a registry or an index.
Autonomous Discovery in the Chemical Sciences Part I: Progress
Open accessAbstract
This two‐part Review examines how automation has contributed to different aspects of discovery in the chemical sciences. In this first part, we describe a classification for discoveries of physical matter (molecules, materials, devices), processes, and models and how they are unified as search problems. We then introduce a set of questions and considerations relevant to assessing the extent of autonomy. Finally, we describe many case studies of discoveries accelerated by or resulting from computer assistance and automation from the domains of synthetic chemistry, drug discovery, inorganic chemistry, and materials science. These illustrate how rapid advancements in hardware automation and machine learning continue to transform the nature of experimentation and modeling. Part two reflects on these case studies and identifies a set of open challenges for the field.
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Combining Machine Learning and Computational Chemistry for Predictive Insights Into Chemical Systems
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A field guide to flow chemistry for synthetic organic chemists
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Metadata
- Authors
- Coley, C. W., Eyke, N. S., & Jensen, K. F.
- Venue
- Angewandte Chemie International Edition
- Publisher
- Wiley
- Published
- 2020-06-08
- Volume
- 59
- Issue
- 51
- Pages
- 22858-22893
- ISSN
- 1433-7851 (ISSN-L)
- 1521-3773
- OpenAlex
- W2975022113
- Cited by
- 317
- References
- 547
- FWCI
- 11.20
- Type
- journal article
- Language
- en
- Open access
- green
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- Coley, C. W., Eyke, N. S., & Jensen, K. F. (2020). Autonomous Discovery in the Chemical Sciences Part I: Progress. Angewandte Chemie International Edition. https://doi.org/10.1002/anie.201909987
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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
