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The DOI matches its Crossref record; 10 of the 10 references it cites were found in a registry or an index.

The Molecular Industrial Revolution: Automated Synthesis of Small Molecules

Open access
Trobe, Melanie, Burke, Martin D.·2018·Angewandte Chemie International Edition

Abstract

Today we are poised for a transition from the highly customized crafting of specific molecular targets by hand to the increasingly general and automated assembly of different types of molecules with the push of a button. Creating machines that are capable of making many different types of small molecules on demand, akin to that which has been achieved on the macroscale with 3D printers, is challenging. Yet important progress is being made toward this objective with two complementary approaches: 1) Automation of customized synthesis routes to different targets by machines that enable the use of many reactions and starting materials, and 2) automation of generalized platforms that make many different targets using common coupling chemistry and building blocks. Continued progress in these directions has the potential to shift the bottleneck in molecular innovation from synthesis to imagination, and thereby help drive a new industrial revolution on the molecular scale.

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Crossref · 10.1002/anie.201710482

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Metadata

Authors
Trobe, M., & Burke, M. D.
Venue
Angewandte Chemie International Edition
Publisher
Wiley
Published
2018-03-07
Volume
57
Issue
16
Pages
4192-4214
ISSN
  • 1433-7851 (ISSN-L)
  • 1521-3773
OpenAlex
W2791253051
Cited by
194
References
10
FWCI
9.72
Type
journal article
Language
en
Open access
green

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CoChat. (2026). Citation check: The Molecular Industrial Revolution: Automated Synthesis of Small Molecules. https://app.cochat.ai/papers/10.1002/anie.201710482
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Trobe, M., & Burke, M. D. (2018). The Molecular Industrial Revolution: Automated Synthesis of Small Molecules. Angewandte Chemie International Edition. https://doi.org/10.1002/anie.201710482

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Bibliographic data: Semantic Scholar, OpenAlex, Crossref.

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.