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New strategy for production of Primary alcohols from aliphatic olefins by tandem cross-metathesis/hydrogenation

Chinese Chemical Letters 2020年第6期31卷 1525-1529页

作者： Ruilong Jia Zhijun Zuo Xu Li Lei Liu Jinxiang Dong College of Chemistry and Chemical Engineering Taiyuan University of TechnologyTaiyuan 030024China Shanxi University of Traditional Chinese Medicine Jinzhong 030619China Key Laboratory of Coal Science and Technology of Ministry of Education and Shanxi Province Taiyuan University of TechnologyTaiyuan 030024China School of Chemical Engineering and Light Industry Guangdong University of Technology.Guangzhou 510006China

Primary alcohols are widely used in industry as solvents and precursors of detergents.The classic methods for hydration of terminal alkenes always produce the Markovnikov products.Herein,we reported a reliable approach to produce Primary alcohols from terminal alkenes combining with biomass-derived allyl alcohol by tandem cross-metathesis/hydrogenation.A series of primary alcohol with different chain lengths was successfully produced in high yields(ca.90%).Computational studies revealed that self-metathesis and hydrogenation of substrates are accessible but much slower than crossmetathesis.This new methodology represents a unique alternative to Primary alcohols from terminal alkenes.

关键词： Primary alcohols Aliphatic olefins Allyl alcohol Cross-metathesis/hydrogenation Anti-Markovnikov regioselectivity

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

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Chinese Journal of Chemistry 2023年第2期41卷 143-150页

作者： Jia Qiu Yougen Xu Shimin Su Yadong Gao Peiyuan Yu Zhixiong Ruan Kuangbiao Liao Guangdong Laboratory Animals Monitoring Institute Guangdong Provincial Key Laboratory of Laboratory AnimalsGuangzhouGuangdong 510663China Guangzhou Municipal and Guangdong Provincial Key Laboratory of Molecular Target&Clinical Pharmacology the NMPA and State Key Laboratory of Respiratory DiseaseSchool of Pharmaceutical Sciences and the Fifth Affiliated HospitalGuangzhou Medical UniversityGuangzhouGuangdong 511436China Bioland Laboratory GuangzhouGuangdong 510005China Department of Chemistry Southern University of Science and TechnologyShenzhenGuangdong 518055China Guangzhou Laboratory GuangzhouGuangdong 510320China

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

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