@article{HAN2023, 
author = {Yingfeng HAN and Xinyue LU and Le ZHANG},
title = {AI & Chem: From automation to intelligence},
year = {2023},
journal = {Journal of Northwest University (Natural Science Edition)},
volume = {53},
number = {1},
pages = {1-16},
keywords = {laboratory automation, automated synthesis, artificial chemistry intelligence, machine learning, interdisciplinarity},
url = {https://www.sciopen.com/article/10.16152/j.cnki.xdxbzr.2023-01-001},
doi = {10.16152/j.cnki.xdxbzr.2023-01-001},
abstract = {At present, the gradual and in-depth development of multidisciplinary paradigm has put forward new requirements to traditional chemical synthesis. Recently, with the rapid development of artificial intelligence technology represented by machine learning, the "AI+Chem" model has gradually made automatic synthesis intelligent. By mining massive chemical experiment data, AI can not only help researchers make reasonable analysis and prediction, but also liberate researchers from tedious and complex daily experiments, which can greatly accelerate the related research and development process. This review combs the recent development of chemical research field from automatic synthesis to intelligence. We started with the description of the development of laboratory automation platform. Then, we systematically summarized recent progress on the construction paradigm of laboratory automation platform, emphasized the combination of automatic synthesis technology and artificial intelligence to achieve intelligent closed-loop strategy of chemical synthesis. Finally, we discussed the future development prospects of this field.}
}