Auto Machine Learning Assisted Preparation of Carboxylic Acid by TEMPO-Catalyzed Primary Alcohol Oxidation  

作　　者：Jia Qiu Yougen Xu Shimin Su Yadong Gao Peiyuan Yu Zhixiong Ruan Kuangbiao Liao 

机构地区：[1]Guangdong Laboratory Animals Monitoring Institute,Guangdong Provincial Key Laboratory of Laboratory Animals,Guangzhou,Guangdong 510663,China [2]Guangzhou Municipal and Guangdong Provincial Key Laboratory of Molecular Target&Clinical Pharmacology,the NMPA and State Key Laboratory of Respiratory Disease,School of Pharmaceutical Sciences and the Fifth Affiliated Hospital,Guangzhou Medical University,Guangzhou,Guangdong 511436,China [3]Bioland Laboratory,Guangzhou,Guangdong 510005,China [4]Department of Chemistry,Southern University of Science and Technology,Shenzhen,Guangdong 518055,China [5]Guangzhou Laboratory,Guangzhou,Guangdong 510320,China

出　　处：《Chinese Journal of Chemistry》2023年第2期143-150,共8页中国化学（英文版）

基　　金：We are grateful for financial support from Guangzhou Laboratory,Bioland Laboratory,and the National Natural Science Foundation of China(No.22071249).

摘　　要：Though alcohol oxidations were considered as well-established reactions,selecting productive conditions or predicting reaction yields for unseen alcohols remained as major challenges.Herein,an auto machine learning(ML)model for TEMPO-catalyzed oxida-tion of primary alcohols to the corresponding carboxylic acids is disclosed.A dataset of 3444 data,consisting of 282 primary alco-hols and 45 conditions,were generated using high-throughput experimentation(HTE).With the HTE data and 105 descriptors,a multi-label prediction was performed with AutoGluon(an open-source auto machine learning framework)and KNIME(an open-source data analytics platform).For the independent test of 240 reactions(a full matrix of 20 unseen alcohols and 12 condi-tions),AutoGluon with multi-label prediction for yield prediction(AGMP)gave excellent performance.For external test of 1308 re-actions(consisting of 84 alcohols and 45 conditions),AGMP still afforded good results with R2 as 0.767 and MAE as 4.9%.The model also revealed that the newly generated descriptor(Y/N,classification of the reaction reactivity)was the most relevant descriptor for yield prediction,offering a new perspective to integrate HTE and ML in organic synthesis.

关 键 词：TEMPO OXIDATION Primary alcohols Carboxylic acids AutoGluon 

分 类 号：O62[理学—有机化学]