Work

Designing Algorithms To Aid Discovery by Chemical Robots

Year: 2018

Type: article

Abstract: Recently, automated robotic systems have become very efficient, thanks to improved coupling between sensor systems and algorithms, of which the latter have been gaining significance thanks to the increase in computing power over the past few decades. However, intelligent automated chemistry platforms for discovery orientated tasks need to be able to cope with the unknown, which is a profoundly hard problem. In this Outlook, we describe how recent advances in the design and application of algorithms, coupled with the increased amount of chemical data available, and automation and control systems may allow more productive chemical research and the development of chemical robots able to target discovery. This is shown through examples of workflow and data processing with automation and control, and through the use of both well-used and cutting-edge algorithms illustrated using recent studies in chemistry. Finally, several algorithms are presented in relation to chemical robots and chemical intelligence for knowledge discovery.

Source: ACS Central Science

DOI: 10.1021/acscentsci.8b00176

Authors: Alon B. Henson, Piotr S. Gromski, Leroy Cronin

Institution: University of Glasgow

Language: English

Topic: Machine Learning in Materials Science

Subfield: Materials Chemistry

Field: Materials Science

Domain: Physical Sciences

Open Access status: diamond

Funders: Royal Society, Wolfson Foundation, Engineering and Physical Sciences Research Council, H2020 European Research Council