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Journal Article 2

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2023 2

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Artificial intelligence 1

Atomic simulation 1

Catalysis 1

Deep reinforcement learning 1

Graph neural networks 1

Machine learning 1

Neural network potential 1

Retrosynthesis 1

Retrosynthesis prediction 1

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Artificial Intelligence for Retrosynthesis Prediction Review

Yinjie Jiang, Yemin Yu, Ming Kong, Yu Mei, Luotian Yuan, Zhengxing Huang, Kun Kuang, Zhihua Wang, Huaxiu Yao, James Zou, Connor W. Coley, Ying Wei

Engineering 2023, Volume 25, Issue 6,   Pages 32-50 doi: 10.1016/j.eng.2022.04.021

Abstract:

In recent years, there has been a dramatic rise in interest in retrosynthesis prediction with artificialUnlike conventional retrosynthesis prediction performed by chemists and by rule-based expert systems,datasets to predict reactions and retrosynthesis routes.This review describes the current landscape of AI-driven retrosynthesis prediction.We then review the related AI techniques and recent progress that enable retrosynthesis prediction.

Keywords： Retrosynthesis prediction     Artificial intelligence     Graph neural networks     Deep reinforcement learning    

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Machine Learning for Chemistry: Basics and Applications Review

Yun-Fei Shi, Zheng-Xin Yang, Sicong Ma, Pei-Lin Kang, Cheng Shang, P. Hu, Zhi-Pan Liu

Engineering 2023, Volume 27, Issue 8,   Pages 70-83 doi: 10.1016/j.eng.2023.04.013

Abstract: Three important fields of ML in chemistry are discussed: ① retrosynthesis, in which ML predicts the likely

Keywords： Machine learning     Atomic simulation     Catalysis     Retrosynthesis     Neural network potential    

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Title Author Date Type Operation

Artificial Intelligence for Retrosynthesis Prediction

Yinjie Jiang, Yemin Yu, Ming Kong, Yu Mei, Luotian Yuan, Zhengxing Huang, Kun Kuang, Zhihua Wang, Huaxiu Yao, James Zou, Connor W. Coley, Ying Wei

Journal Article

Machine Learning for Chemistry: Basics and Applications

Yun-Fei Shi, Zheng-Xin Yang, Sicong Ma, Pei-Lin Kang, Cheng Shang, P. Hu, Zhi-Pan Liu

Journal Article