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化工基础数据获取新范式:机制+数据驱动 被引量:1

New Paradigm for Determining Fundamental Chemical Engineering Data:A“Mechanism+Data Driven”Strategy
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摘要 基于国家自然科学基金委员会化学科学部科技活动“化工基础数据获取新范式战略研讨会”的研讨成果,聚焦于化工基础数据获取,面向人工智能赋能现代化工基础研究新范式的目标,本文凝练了化工基础理论、模型化研究与人工智能方法深度融合实现化工基础数据精确获取、助力产品设计以及过程与工艺设计的关键科学问题。同时,总结了近年来化工基础数据智能获取、化学与化工研究方法与人工智能相耦合在数据精确扩增、化工机制研究、智能设计等方面的研究进展,并对化工基础数据获取新范式提出建议,有望助力我国化工智能化发展的理论创新和技术突破。 With the support from Department of Chemical Sciences,National Natural Science Foundation of China,“Symposium on New Paradigm for Determining Fundamental Chemical Engineering Data”focuses on the determination of chemical engineering data and presents suggestions addressing key scientific issues encountered in the deep integration of basic chemical engineering fundamental theories and modeling research with artificial intelligence methods.The suggestions aim to achieve accurate determination of chemical engineering fundamental data,thereby assisting in product design,process optimization,and technology development.This article also highlights recent research progress in the intelligent determination of chemical engineering data,focusing on areas such as accurate data augmentation,chemical engineering mechanism research and intelligent design.Furthermore,this article proposes a new paradigm of determining fundamental chemical engineering data,with the expectation of fostering theoretical innovation and technological breakthroughs for the intelligent development of Chinas chemical industry.
作者 吉远辉 朱家华 穆立文 陆小华 周晨 张国俊 Yuanhui Ji;Jiahua Zhu;Liwen Mu;Xiaohua Lu;Chen Zhou;Guojun Zhang(School of Chemistry and Chemical Engineering,Southeast University,Nanjing 211189;State Key Laboratory of Materials-Oriented Chemical Engineering,College of Chemical Engineering,Nanjing Tech University,Nanjing 211816;Department of Chemical Sciences,National Natural Science Foundation of China,Beijing 100085)
出处 《中国科学基金》 CSSCI CSCD 北大核心 2024年第4期712-718,共7页 Bulletin of National Natural Science Foundation of China
关键词 化工智能化 化工基础数据 理论模型 产品与过程设计 人工智能算法 intelligent chemical engineering process fundamental chemical engineering data modeling product and process design artificial intelligence algorithms
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