Artificial Intelligence for Contemporary Chemistry Research

被引:6
作者
Zhu Boyang [1 ]
Wu Ruilong [1 ]
Yu Xi [1 ,2 ]
机构
[1] Tianjin Univ, Dept Chem, Tianjin 300072, Peoples R China
[2] Tianjin Key Lab Mol Optoelect Sci, Tianjin 300072, Peoples R China
基金
中国国家自然科学基金;
关键词
artificial intelligence; machine learning; molecular descriptor; deep learning; MOLECULAR DESCRIPTORS; INHIBITORS; PREDICTION; SEARCH;
D O I
10.6023/A20070306
中图分类号
O6 [化学];
学科分类号
0703 ;
摘要
Artificial intelligence (AI), especially the machine learning, is playing an increasingly important role in contemporary scientific research. Unlike the traditional computer program, machine learning can analyze a large number of data repeatedly and optimize its own model, a process which is called a "learning process". So that the AI can find the relationship underling the experiments from a large number of data, form a new model with better prediction and decisionmaking ability, and make an optimized strategy. The characteristics of chemical research just hit the strengths of machine learning. Chemical research often faces very complex material system and experimental process, so it is difficult to accurately analyze and making judgment through physical chemistry principles. Artificial intelligence can mine the correlation of massive experimental data generated in chemical experiments, help chemists make reasonable analysis and prediction, and therefore greatly accelerate the process of chemical research. This review presents the modern artificial intelligence method and its basic principles on solving chemical problems, by representative examples with specific machine learning algorithm. The application of artificial intelligence in chemical science is in a period of vigorous rise. Artificial intelligence has initially shown a powerful assist to chemical research. We hope this review can help more domestic chemical workers understand and use this powerful tool.
引用
收藏
页码:1366 / 1382
页数:17
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