RSscore:Reaction superiority learned from reaction mapping hypergraph  

作　　者：Chenyang Xu Lijuan Guo Kang Zhou Hai Yu Chaoliang Wei Fengqi Fan Lei Zhang 

机构地区：[1]State Key Laboratory of Fine Chemicals,Frontiers Science Center for Smart Materials Oriented Chemical Engineering,Institute of Chemical Process Systems Engineering,School of Chemical Engineering,Dalian University of Technology,Dalian 116024,China [2]PetroChina Lanzhou Lubricating Oil Research&Development Institute,Lanzhou 730060,China

出　　处：《Chinese Journal of Chemical Engineering》2024年第10期203-215,共13页中国化学工程学报（英文版）

基　　金：the financial support of the National Natural Science Foundation of China(22078041,22278053);Dalian High-level Talents Innovation Support Program(2021RQ105);the Fundamental Research Funds for China Central Universities(DUT22QN209,DUT22LAB608).

摘　　要：The selection of chemical reactions is directly related to the quality of synthesis pathways,so a reasonable reaction evaluation metric plays a crucial role in the design and planning of synthesis pathways.Since reaction conditions also need to be considered in synthesis pathway design,a reaction metric that combines reaction time,temperature,and yield is required for chemical reactions of different reaction agents.In this study,a chemical reaction graph descriptor which includes the atom-atom mapping relationship is proposed to effectively describe reactions.Then,through pre-training using graph contrastive learning and fine-tuning through supervised learning,we establish a model for generating the probability of reaction superiority(RSscore).Finally,to validate the effectiveness of the current evaluation index,RSscore is applied in two applications,namely reaction evaluation and synthesis routes analysis,which proves that the RSscore provides an important agents-considered evaluation criterion for computer-aided synthesis planning(CASP).

关 键 词：Computer-aided synthesis planning Neural networks Reaction evaluation indicator Reaction graph Graph contractive learning 

分 类 号：TQ052[化学工程]