TY - JOUR
T1 - Genetic Algorithms and Machine Learning for Predicting Surface Composition, Structure, and Chemistry
T2 - A Historical Perspective and Assessment
AU - Roberts, Josiah
AU - Bursten, Julia R.S.
AU - Risko, Chad
N1 - Publisher Copyright:
© 2021 American Chemical Society.
PY - 2021/9/14
Y1 - 2021/9/14
N2 - Genetic algorithms (GA) and machine learning (ML) have a long history of development and use in chemistry. Recent algorithmic and computational advances, however, have brought these methods to the forefront of chemical research, and chemistry is experiencing a transformation in the way that machines and humans interact to pursue scientific advances. The field of materials chemistry, in particular, has witnessed a considerable expansion in the maturity of GA and ML approaches, as machine-based materials design ushers in a new era of materials development, discovery, and deployment. In addition to predicting new compositions and properties of bulk materials, GA and ML have also guided new insights into the structure, composition, and chemistry of materials surfaces. In this review, we focus on how GA and ML have been used in conjunction with chemical simulation techniques to advance understanding of surface chemistry, examining the history, recent work, and overall success of these applications.
AB - Genetic algorithms (GA) and machine learning (ML) have a long history of development and use in chemistry. Recent algorithmic and computational advances, however, have brought these methods to the forefront of chemical research, and chemistry is experiencing a transformation in the way that machines and humans interact to pursue scientific advances. The field of materials chemistry, in particular, has witnessed a considerable expansion in the maturity of GA and ML approaches, as machine-based materials design ushers in a new era of materials development, discovery, and deployment. In addition to predicting new compositions and properties of bulk materials, GA and ML have also guided new insights into the structure, composition, and chemistry of materials surfaces. In this review, we focus on how GA and ML have been used in conjunction with chemical simulation techniques to advance understanding of surface chemistry, examining the history, recent work, and overall success of these applications.
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U2 - 10.1021/acs.chemmater.1c00538
DO - 10.1021/acs.chemmater.1c00538
M3 - Review article
AN - SCOPUS:85114441059
SN - 0897-4756
VL - 33
SP - 6589
EP - 6615
JO - Chemistry of Materials
JF - Chemistry of Materials
IS - 17
ER -