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Experiment Specification, Capture and Laboratory Automation Technology (ESCALATE): a software pipeline for automated chemical experimentation and data management

Published online by Cambridge University Press:  04 June 2019

Ian M. Pendleton Open the ORCID record for Ian M. Pendleton [Opens in a new window] ,
Gary Cattabriga ,
Zhi Li ,
Mansoor Ani Najeeb ,
Sorelle A. Friedler ,
Alexander J. Norquist Open the ORCID record for Alexander J. Norquist [Opens in a new window] ,
Emory M. Chan Open the ORCID record for Emory M. Chan [Opens in a new window]  and
Joshua Schrier Open the ORCID record for Joshua Schrier [Opens in a new window]
Ian M. Pendleton
Affiliation:
Department of Chemistry, Haverford College, 370 Lancaster Avenue, Haverford, Pennsylvania 19041, USA
Gary Cattabriga
Affiliation:
Department of Chemistry, Haverford College, 370 Lancaster Avenue, Haverford, Pennsylvania 19041, USA
Zhi Li
Affiliation:
Molecular Foundry, Lawrence Berkeley National Laboratory, 1 Cyclotron Road, Berkeley, California 94720, USA
Mansoor Ani Najeeb
Affiliation:
Department of Chemistry, Haverford College, 370 Lancaster Avenue, Haverford, Pennsylvania 19041, USA
Sorelle A. Friedler
Affiliation:
Department of Computer Science, Haverford College, 370 Lancaster Avenue, Haverford, Pennsylvania 19041, USA
Alexander J. Norquist
Affiliation:
Department of Chemistry, Haverford College, 370 Lancaster Avenue, Haverford, Pennsylvania 19041, USA
Emory M. Chan
Affiliation:
Molecular Foundry, Lawrence Berkeley National Laboratory, 1 Cyclotron Road, Berkeley, California 94720, USA
Joshua Schrier*
Affiliation:
Department of Chemistry, Fordham University, 441 E. Fordham Road, The Bronx, New York, 10458, USA
*
Address all correspondence to Joshua Schrier at jschrier@fordham.edu
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Abstract

Applying artificial intelligence to materials research requires abundant curated experimental data and the ability for algorithms to request new experiments. ESCALATE (Experiment Specification, Capture and Laboratory Automation Technology)—an ontological framework and open-source software package—solves this problem by providing an abstraction layer for human- and machine-readable experiment specification, comprehensive and extensible (meta-) data capture, and structured data reporting. ESCALATE simplifies the initial data collection process, and its reporting and experiment generation mechanisms simplify machine learning integration. An initial ESCALATE implementation for metal halide perovskite crystallization was used to perform 55 rounds of algorithmically-controlled experiment plans, capturing 4336 individual experiments.

Type
Artificial Intelligence Research Letters
Information
MRS Communications , Volume 9 , Issue 3 , September 2019 , pp. 846 - 859
Copyright
Copyright © Materials Research Society 2019 

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