基于人工智能的微分散基础研究  

Fundamental research on microdispersion based on artificial intelligence

作　　者：刘梦绮 王凯[1] 骆广生[1] LIU Mengqi;WANG Kai;LUO Guangsheng(Department of Chemical Engineering,State Key Laboratory of Chemical Engineering,Tsinghua University,Beijing 100084,China)

机构地区：[1]清华大学化学工程系,化学工程联合国家重点实验室,北京100084

出　　处：《化工学报》2024年第4期1096-1104,共9页CIESC Journal

基　　金：国家自然科学基金项目(L2324201,21991104);中国科学院学部前沿交叉研判项目(XK2023HXC001);清华大学-中国石油化工集团有限公司绿色化工联合研究院资助项目(20212930034)。

摘　　要：微分散是微化工技术的重要组成部分,其装备和过程的复杂性使得相关研究受到诸多限制,传统思想指导下微分散基础研究以“设计-实验-模型”为思路,进展缓慢。近年来,人工智能方法因其强大的识别和回归能力在化工领域备受关注,人工智能辅助的微分散基础研究有利于形成微化工过程认识的新范式,促进微化工技术发展。本文介绍了人工智能方法的一般思路及其针对微分散研究的适用性,综述了人工智能技术在显微图像识别、液滴和气泡分散尺寸预测以及微分散过程控制和优化中的研究进展,对未来基于人工智能的微化工研究进行了展望。Microdispersion is an important part of micro chemical engineering technology.The complexity of equipment and processes imposes many limitations on its related research.Under the guidance of traditional thinking,the basic research on microdispersion follows the approach of“design-experiment-modeling”,resulting in slow progress.In recent years,artificial intelligence(AI)methods have received increasing attention in chemical engineering due to their powerful recognition and regression capabilities.AI-assisted basic research on microdispersion is conducive to forming a new paradigm for understanding micro chemical engineering processes,promoting the development of micro chemical engineering technology.This article introduces the general idea of AI methods and their applicability to microdispersion investigation,reviews the developments of AI technology in microscopic image recognition,droplet and bubble dispersion size prediction,and microdispersion process control and optimization,and offers insights into the prospective directions of micro chemical engineering based on AI technology.

关 键 词：微流体学 分散 模型 算法 人工智能 

分 类 号：TQ021.1[化学工程]