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DOI | 10.1126/science.aar5169 |
Predicting reaction performance in C-N cross-coupling using machine learning | |
Ahneman, Derek T.1; Estrada, Jesus G.1; Lin, Shishi2; Dreher, Spencer D.2; Doyle, Abigail G.1 | |
2018-04-13 | |
发表期刊 | SCIENCE
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ISSN | 0036-8075 |
EISSN | 1095-9203 |
出版年 | 2018 |
卷号 | 360期号:6385页码:186-190 |
文章类型 | Article |
语种 | 英语 |
国家 | USA |
英文摘要 | Machine learning methods are becoming integral to scientific inquiry in numerous disciplines. We demonstrated that machine learning can be used to predict the performance of a synthetic reaction in multidimensional chemical space using data obtained via high-throughput experimentation. We created scripts to compute and extract atomic, molecular, and vibrational descriptors for the components of a palladium-catalyzed Buchwald-Hartwig cross-coupling of aryl halides with 4-methylaniline in the presence of various potentially inhibitory additives. Using these descriptors as inputs and reaction yield as output, we showed that a random forest algorithm provides significantly improved predictive performance over linear regression analysis. The random forest model was also successfully applied to sparse training sets and out-of-sample prediction, suggesting its value in facilitating adoption of synthetic methodology. |
领域 | 地球科学 ; 气候变化 ; 资源环境 |
收录类别 | SCI-E |
WOS记录号 | WOS:000429805400042 |
WOS关键词 | CATALYSIS ; REGRESSION ; DISCOVERY ; TOOL |
WOS类目 | Multidisciplinary Sciences |
WOS研究方向 | Science & Technology - Other Topics |
URL | 查看原文 |
引用统计 | |
文献类型 | 期刊论文 |
条目标识符 | http://119.78.100.173/C666/handle/2XK7JSWQ/198404 |
专题 | 地球科学 资源环境科学 气候变化 |
作者单位 | 1.Princeton Univ, Dept Chem, Princeton, NJ 08544 USA; 2.Merck Sharp & Dohme Corp, Chem Capabil & Screening, Kenilworth, NJ 07033 USA |
推荐引用方式 GB/T 7714 | Ahneman, Derek T.,Estrada, Jesus G.,Lin, Shishi,et al. Predicting reaction performance in C-N cross-coupling using machine learning[J]. SCIENCE,2018,360(6385):186-190. |
APA | Ahneman, Derek T.,Estrada, Jesus G.,Lin, Shishi,Dreher, Spencer D.,&Doyle, Abigail G..(2018).Predicting reaction performance in C-N cross-coupling using machine learning.SCIENCE,360(6385),186-190. |
MLA | Ahneman, Derek T.,et al."Predicting reaction performance in C-N cross-coupling using machine learning".SCIENCE 360.6385(2018):186-190. |
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