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Structure-activity relationship study of anti-wear additives in rapeseed oil based on machine learning and logistic regression

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成果类型:
期刊论文
作者:
Liu, Jianfang;Yi, Chenglingzi;Zhang, Yaoyun;Yang, Sicheng;Liu, Ting;...
通讯作者:
Liu, JF
作者机构:
[Yang, Sicheng; Liu, Jianfang; Peng, Shuai; Yi, Chenglingzi; Zhang, Yaoyun; Yang, Qing; Liu, Ting; Zhang, Rongrong] Wuhan Polytech Univ, Sch Life Sci & Technol, Wuhan 430023, Peoples R China.
[Jia, Dan] Wuhan Res Inst Mat Protect, State Key Lab Special Surface Protect Mat & Appli, Wuhan 430030, Peoples R China.
通讯机构:
[Liu, JF ] W
Wuhan Polytech Univ, Sch Life Sci & Technol, Wuhan 430023, Peoples R China.
语种:
英文
期刊:
RSC Advances
ISSN:
2046-2069
年:
2024
卷:
14
期:
12
页码:
8464-8480
基金类别:
National Natural Science Foundation of China [52075405]; National Natural Science Foundation of China
机构署名:
本校为第一且通讯机构
摘要:
Anti-wear performance is a crucial quality of lubricants, and it is important to conduct research into the structure-activity relationship of anti-wear additives in bio-based lubricants. These lubricants are eco-friendly and energy-efficient. A literature review resulted in the construction of a dataset comprising 779 anti-wear properties of 79 anti-wear additives in rapeseed oil, at various loadings and additive levels. The anti-wear additives were classified into six groups, including phosphoric acid, formate esters, borate esters, thiazoles, triazine derivatives, and thiophene. Logistic reg...

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