{"title":"工业均相催化系统发展中机器学习方法的现状展望","authors":"José Ferraz-Caetano","doi":"10.2174/2213337209666220728094248","DOIUrl":null,"url":null,"abstract":"\n\nThis brief perspective outlines the pivotal role of Machine Learning methods in the green, digital transition of industrial chemistry. The focus on homogenous catalysis highlights the recent methodologies in the development of industrial processes, including the design of new catalysts and the enhancement of sustainable reaction conditions to lower production costs. We report several examples of Machine Learning assisted methodologies through recent Data Science trends on innovation of industrial homogeneous organocatalytic systems. We also stress the current benefits, drawbacks, and limitations towards the mass implementation of these Data Science methodologies.\n","PeriodicalId":10945,"journal":{"name":"Current Organocatalysis","volume":" ","pages":""},"PeriodicalIF":0.9000,"publicationDate":"2022-07-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Current Outlooks on Machine Learning Methods for the Development of Industrial Homogeneous Catalytic Systems\",\"authors\":\"José Ferraz-Caetano\",\"doi\":\"10.2174/2213337209666220728094248\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"\\n\\nThis brief perspective outlines the pivotal role of Machine Learning methods in the green, digital transition of industrial chemistry. The focus on homogenous catalysis highlights the recent methodologies in the development of industrial processes, including the design of new catalysts and the enhancement of sustainable reaction conditions to lower production costs. We report several examples of Machine Learning assisted methodologies through recent Data Science trends on innovation of industrial homogeneous organocatalytic systems. We also stress the current benefits, drawbacks, and limitations towards the mass implementation of these Data Science methodologies.\\n\",\"PeriodicalId\":10945,\"journal\":{\"name\":\"Current Organocatalysis\",\"volume\":\" \",\"pages\":\"\"},\"PeriodicalIF\":0.9000,\"publicationDate\":\"2022-07-28\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Current Organocatalysis\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.2174/2213337209666220728094248\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q4\",\"JCRName\":\"CHEMISTRY, PHYSICAL\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Current Organocatalysis","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.2174/2213337209666220728094248","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"CHEMISTRY, PHYSICAL","Score":null,"Total":0}
Current Outlooks on Machine Learning Methods for the Development of Industrial Homogeneous Catalytic Systems
This brief perspective outlines the pivotal role of Machine Learning methods in the green, digital transition of industrial chemistry. The focus on homogenous catalysis highlights the recent methodologies in the development of industrial processes, including the design of new catalysts and the enhancement of sustainable reaction conditions to lower production costs. We report several examples of Machine Learning assisted methodologies through recent Data Science trends on innovation of industrial homogeneous organocatalytic systems. We also stress the current benefits, drawbacks, and limitations towards the mass implementation of these Data Science methodologies.
期刊介绍:
Current Organocatalysis is an international peer-reviewed journal that publishes significant research in all areas of organocatalysis. The journal covers organo homogeneous/heterogeneous catalysis, innovative mechanistic studies and kinetics of organocatalytic processes focusing on practical, theoretical and computational aspects. It also includes potential applications of organocatalysts in the fields of drug discovery, synthesis of novel molecules, synthetic method development, green chemistry and chemoenzymatic reactions. This journal also accepts papers on methods, reagents, and mechanism of a synthetic process and technology pertaining to chemistry. Moreover, this journal features full-length/mini review articles within organocatalysis and synthetic chemistry. It is the premier source of organocatalysis and synthetic methods related information for chemists, biologists and engineers pursuing research in industry and academia.