LAPSE:2019.0650
Published Article
LAPSE:2019.0650
Data-Mining for Processes in Chemistry, Materials, and Engineering
Hao Li, Zhien Zhang, Zhe-Ze Zhao
July 25, 2019
With the rapid development of machine learning techniques, data-mining for processes in chemistry, materials, and engineering has been widely reported in recent years. In this discussion, we summarize some typical applications for process optimization, design, and evaluation of chemistry, materials, and engineering. Although the research and application targets are various, many important common points still exist in their data-mining. We then propose a generalized strategy based on the philosophy of data-mining, which should be applicable for the design and optimization targets for processes in various fields with both scientific and industrial purposes.
Keywords
chemistry, data-mining, Energy, engineering, Machine Learning, materials, neural networks
Suggested Citation
Li H, Zhang Z, Zhao ZZ. Data-Mining for Processes in Chemistry, Materials, and Engineering. (2019). LAPSE:2019.0650
Author Affiliations
Li H: College of Chemistry, Sichuan University, Chengdu 610064, China
Zhang Z: William G. Lowrie Department of Chemical and Biomolecular Engineering, The Ohio State University, 151 West Woodruff Avenue, Columbus, OH 43210, USA [ORCID]
Zhao ZZ: School of Life Sciences and State Key Laboratory of Agrobiotechnology, The Chinese University of Hong Kong, Shatin, New Territories, Hong Kong, China
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Journal Name
Processes
Volume
7
Issue
3
Article Number
E151
Year
2019
Publication Date
2019-03-11
Published Version
ISSN
2227-9717
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Original Submission
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PII: pr7030151, Publication Type: Comment
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LAPSE:2019.0650
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doi:10.3390/pr7030151
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Jul 25, 2019
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CC BY 4.0
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Jul 25, 2019
 
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Jul 25, 2019
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Calvin Tsay
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