DOI: 10.1016/j.cattod.2016.04.013. Feature engineering of machine-learning chemisorption models for catalyst design

Feature engineering of machine-learning chemisorption models for catalyst design

10.1016/j.cattod.2016.04.013

Crossref journal-article

Elsevier BV

Catalysis Today (78)

Bibliography

Li, Z., Ma, X., & Xin, H. (2017). Feature engineering of machine-learning chemisorption models for catalyst design. Catalysis Today, 280, 232â238.

Authors 3

Zheng Li (first)
Xianfeng Ma (additional)
Hongliang Xin (additional)

References 42 Referenced 196

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Dates

Type	When
Created	9 years, 3 months ago (May 14, 2016, 4:15 a.m.)
Deposited	5 years, 9 months ago (Nov. 2, 2019, 11:56 a.m.)
Indexed	1 week, 2 days ago (Aug. 12, 2025, 6:12 p.m.)
Issued	8 years, 6 months ago (Feb. 1, 2017)
Published	8 years, 6 months ago (Feb. 1, 2017)
Published Print	8 years, 6 months ago (Feb. 1, 2017)

Funders 1

American Chemical Society Petroleum Research Fund 10.13039/100006770
Region: Americas
pri (Associations and societies (private and public))
Labels7
1. ACS Petroleum Research Fund
2. Petroleum Research Fund
3. Petroleum Research Fund, American Chemical Society
4. The Petroleum Research Fund
5. ACS-Petroleum Research Fund
6. ACS PRF
7. PRF

BibTeX

@article{Li_2017, title={Feature engineering of machine-learning chemisorption models for catalyst design}, volume={280}, ISSN={0920-5861}, url={http://dx.doi.org/10.1016/j.cattod.2016.04.013}, DOI={10.1016/j.cattod.2016.04.013}, journal={Catalysis Today}, publisher={Elsevier BV}, author={Li, Zheng and Ma, Xianfeng and Xin, Hongliang}, year={2017}, month=feb, pages={232–238} }

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