Machine Learning Screening of Efficient Ionic Liquids for Targeted Cleavage of the ?-O-4 Bond of Lignin
文献类型：期刊论文
| 作者 | Ding, Wei-Lu1,2,4; Zhang, Tao2,3; Wang, Yanlei1,2,4; Xin, Jiayu1,2,4; Yuan, Xiaoqing2,4; Ji, Lin3; He, Hongyan1,2,4 |
| 刊名 | JOURNAL OF PHYSICAL CHEMISTRY B
 |
| 出版日期 | 2022-05-26 |
| 卷号 | 126期号:20页码:3693-3704 |
| ISSN号 | 1520-6106 |
| DOI | 10.1021/acs.jpcb.1c10684 |
| 英文摘要 | Lignin conversion into high value-added chemicals is of great significance for maximizing the use of renewable energy. Ionic liquids (ILs) have been widely used for targeted cleavage of the C-O bonds of lignin due to their high catalytic activity. Studying the cleavage activity of each IL is impossible and timeconsuming, given the huge number of cations and anions. Currently, the mainstream approach to determining the cleavage activity of one IL is to calculate the activation barrier energy (Ea) theoretically via transition state search, a process that involves the iterative determination of an appropriate "imaginary frequency". Machine learning (ML) has been widely used for catalyst design and screening, enabling accurate mapping from specified descriptors to target properties. To avoid complicated Ea calculations and to screen potential candidates, in this study, we selected nearly 103 ILs and guaiacylglycerol-beta-guaiacyl ether (GG) as the lignin model and used the ML technology to train models that can rapidly predict the cleavage activity of ILs. Taking the easily accessible bond dissociation energy (BDE) of the beta-O-4 bond in GG as the target, an ML model with r > 0.93 for predicting the catalytic activity of ILs was obtained. The change tendency of the BDE is consistent with the experimental yield of guaiacol, reflecting the reliability of the ML model. Finally, [C2MIM][Tyrosine] and [C3MIM][Tyrosine] as the optimal candidates for future applications were screened out. This is a novel strategy for predicting the catalytic activity of ILs on lignin without the need to calculate complicated reaction pathways while reducing time consumption. It is anticipated that the ML model can be utilized in future practical applications for targeted cleavage of lignin. |
| WOS关键词 | MODEL COMPOUNDS ; P-COUMARATE ; MECHANISM ; VALORIZATION ; PHOSPHORUS ; ACIDOLYSIS ; OXIDATION ; LINKAGES ; RADICALS ; STRATEGY |
| 资助项目 | Nation Key R&D Program of China[2021YFE0190800] ; National Natural Science Foundation of China[21922813] ; National Natural Science Foundation of China[22008238] ; National Natural Science Foundation of China[21736003] ; National Natural Science Foundation of China[21921005] ; Fund of State Key Laboratory of Multiphase complex systems[MPCS-2021-A-07] ; Fund of State Key Laboratory of Multiphase complex systems[MPCS-2021-A-10] ; Youth Innovation Promotion Association CAS[2021046] ; Youth Innovation Promotion Association CAS[Y2021022] |
| WOS研究方向 | Chemistry |
| 语种 | 英语 |
| WOS记录号 | WOS:000806447100008 |
| 出版者 | AMER CHEMICAL SOC |
| 资助机构 | Nation Key R&D Program of China ; National Natural Science Foundation of China ; Fund of State Key Laboratory of Multiphase complex systems ; Youth Innovation Promotion Association CAS |
| 源URL | [http://ir.ipe.ac.cn/handle/122111/53885]  |
| 专题 | 中国科学院过程工程研究所 |
| 通讯作者 | Ji, Lin; He, Hongyan |
| 作者单位 | 1.Chinese Acad Sci, Innovat Acad Green Manufacture, Beijing 100190, Peoples R China 2.Chinese Acad Sci, Beijing Key Lab Ion Liquids Clean Proc, CAS Key Lab Green Proc & Engn, State Key Lab Multiphase Complex Syst,Inst Proc E, Beijing 100190, Peoples R China 3.Capital Normal Univ, Dept Chem, Beijing 100048, Peoples R China 4.Univ Chinese Acad Sci, Beijing 100049, Peoples R China |
| 推荐引用方式 GB/T 7714 | Ding, Wei-Lu,Zhang, Tao,Wang, Yanlei,et al. Machine Learning Screening of Efficient Ionic Liquids for Targeted Cleavage of the ?-O-4 Bond of Lignin[J]. JOURNAL OF PHYSICAL CHEMISTRY B,2022,126(20):3693-3704. |
| APA | Ding, Wei-Lu.,Zhang, Tao.,Wang, Yanlei.,Xin, Jiayu.,Yuan, Xiaoqing.,...&He, Hongyan.(2022).Machine Learning Screening of Efficient Ionic Liquids for Targeted Cleavage of the ?-O-4 Bond of Lignin.JOURNAL OF PHYSICAL CHEMISTRY B,126(20),3693-3704. |
| MLA | Ding, Wei-Lu,et al."Machine Learning Screening of Efficient Ionic Liquids for Targeted Cleavage of the ?-O-4 Bond of Lignin".JOURNAL OF PHYSICAL CHEMISTRY B 126.20(2022):3693-3704. |
入库方式： OAI收割
来源：过程工程研究所
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