Comparison of Machine Learning Algorithms in Screening Potential Additives to Ni/Al 2 O 3 Methanation Catalysts for Improving the Anti‐Coking Performance-Reference-Cited by-同舟云学术

Comparison of Machine Learning Algorithms in Screening Potential Additives to Ni/Al 2 O 3 Methanation Catalysts for Improving the Anti‐Coking Performance

Published:2019-10-25 Issue:40 Volume:4 Page:11790-11795
ISSN:2365-6549
Container-title:ChemistrySelect
language:en
Short-container-title:ChemistrySelect

Author:

Han Xiaoxia¹,Yue Lin¹,Zhao Chaofan¹,Jiang Shaohua²,Liu Junjie³,Li Yuting⁴,Ren Jun⁴^ORCID

Affiliation:

1. Taiyuan University of TechnologyCollege of Electrical and Power Engineering No. 79 Yingze West Street Taiyuan 030024 China

2. Wuyi UniversitySchool of Biotechnology and Health Sciences No. 22 dongcheng village Jiangmen 529020 China (S. Jiang

3. National Institute of MetrologyDivision of Nanoscale Measurement and Advanced Materials No. 18, Bei San Huan Dong Lu, Chaoyang Dist Beijing 100029 China

4. Taiyuan University of TechnologyKey Laboratory of Coal Science and Technology No. 79 Yingze West Street Taiyuan 030024 China

Funder

National Natural Science Foundation of China

Publisher

Wiley

Subject

General Chemistry

Link

https://onlinelibrary.wiley.com/doi/pdf/10.1002/slct.201902627

Reference86 articles.

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5. Template-Assisted Wet-Combustion Synthesis of Fibrous Nickel-Based Catalyst for Carbon Dioxide Methanation and Methane Steam Reforming

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