The future of sustainable chemistry and process: Convergence of artificial intelligence, data and hardware

作     者：Xin Yee Tai Hao Zhang Zhiqiang Niu Steven D.R.Christie Jin Xuan 

作者机构：Department of Chemical EngineeringLoughborough UniversityLoughborough LE113TUUnited Kingdom School of EngineeringThe University of EdinburghEdinburgh EH93FBUnited Kingdom Department of ChemistryLoughborough UniversityLoughborough LE113TUUnited Kingdom 

出 版 物：《Energy and AI》 (能源与人工智能（英文）)

年 卷 期：2020年第2卷第2期

页      面：167-174页

核心收录：

学科分类：07[理学] 0701[理学-数学] 070101[理学-基础数学] 

基　　金：Department of Chemical Engineering  Loughborough University 

主　　题：Artificial intelligence In-/on-line monitoring Additive manufacturing 

摘      要：Sustainable chemistry for renewable energy generation and green synthesis is a timely research topic with the vision to provide present needs without compromising future *** the era of Industry 4.0,sustainable chemistry and process are undergoing a drastic transformation from continuous flow system toward the next level of operations,such as cooperating and coordinating machine,self-decision-making system,autonomous and automatic problem solver by integrating artificial intelligence,data and hardware in the cyber-physical *** to the lack of convergence between the physical and cyber spaces,the open-loop systems are facing challenges such as data isolation,slow cycle time,and insufficient resources *** researches have been devoted to accelerating these cycles,reducing the time between multistep processes and real-time characterization via additive manufacturing,in-/on-line monitoring,and artificial *** final goal is to concurrently propose process recipes,flow synthesis,and molecules characterization in sustainable chemical processes,with each step transmitting and receiving data *** process is known as‘closing the loop’,which will potentially create a future lab with highly integrated systems,and generate a service-orientated platform for end-to-end synchronization and self-evolving,inverse molecular design,and automatic science *** perspective provides a methodical approach for understanding cyber and physical systems individually,enabled by artificial intelligence and additive manufacturing,respectively,in combination with in-/on-line ***,the future perspective and key challenges for the development of the closed-loop system in sustainable chemistry and process are discussed.