DOI: 10.3390/catal7100306. Application of Artificial Neural Networks for Catalysis: A Review

Application of Artificial Neural Networks for Catalysis: A Review

10.3390/catal7100306

Crossref journal-article

MDPI AG

Catalysts (1968)

Abstract

Machine learning has proven to be a powerful technique during the past decades. Artificial neural network (ANN), as one of the most popular machine learning algorithms, has been widely applied to various areas. However, their applications for catalysis were not well-studied until recent decades. In this review, we aim to summarize the applications of ANNs for catalysis research reported in the literature. We show how this powerful technique helps people address the highly complicated problems and accelerate the progress of the catalysis community. From the perspectives of both experiment and theory, this review shows how ANNs can be effectively applied for catalysis prediction, the design of new catalysts, and the understanding of catalytic structures.

Bibliography

Li, H., Zhang, Z., & Liu, Z. (2017). Application of Artificial Neural Networks for Catalysis: A Review. Catalysts, 7(10), 306.

Authors 3

Hao Li (first)
Zhien Zhang (additional)
Zhijian Liu (additional)

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Dates

Type	When
Created	7 years, 10 months ago (Oct. 18, 2017, 11:10 a.m.)
Deposited	1 year, 2 months ago (June 8, 2024, 5:03 p.m.)
Indexed	1 week, 1 day ago (Aug. 12, 2025, 5:29 p.m.)
Issued	7 years, 10 months ago (Oct. 18, 2017)
Published	7 years, 10 months ago (Oct. 18, 2017)
Published Online	7 years, 10 months ago (Oct. 18, 2017)

Funders 0

None

BibTeX

@article{Li_2017, title={Application of Artificial Neural Networks for Catalysis: A Review}, volume={7}, ISSN={2073-4344}, url={http://dx.doi.org/10.3390/catal7100306}, DOI={10.3390/catal7100306}, number={10}, journal={Catalysts}, publisher={MDPI AG}, author={Li, Hao and Zhang, Zhien and Liu, Zhijian}, year={2017}, month=oct, pages={306} }

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  "abstract": "<jats:p>Machine learning has proven to be a powerful technique during the past decades. Artificial neural network (ANN), as one of the most popular machine learning algorithms, has been widely applied to various areas. However, their applications for catalysis were not well-studied until recent decades. In this review, we aim to summarize the applications of ANNs for catalysis research reported in the literature. We show how this powerful technique helps people address the highly complicated problems and accelerate the progress of the catalysis community. From the perspectives of both experiment and theory, this review shows how ANNs can be effectively applied for catalysis prediction, the design of new catalysts, and the understanding of catalytic structures.</jats:p>",
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