Artificial intelligence-motivated in-situ imaging for visualization investigation of submicron particles deposition in electric-flow coupled fields  

作　　者：Shanlong Tao Xiaoyong Yang Wei Yin Yong Zhu 

机构地区：[1]School of Mechanical and Power Engineering,East China University of Science and Technology,Shanghai 200237,China [2]Research Center for Combustion and Environmental Technology,School of Mechanical Engineering,Shanghai Jiao Tong University,Shanghai 200240,China

出　　处：《Chinese Journal of Chemical Engineering》2024年第10期13-21,共9页中国化学工程学报（英文版）

基　　金：supported by the National Natural Science Foundation of China(52200130,22308100).

摘　　要：This study delves into the intricate deposition dynamics of submicron particles within electric-flow coupled fields,underscoring the unique challenges posed by their minuscule size,aggregation tendencies,and biological reactivity.Employing an operando investigation system that synergizes microfluidic technology with advanced micro-visualization techniques within a lab-on-a-chip framework enables a meticulous examination of the dynamic deposition phenomena.The incorporation of object detection and deep learning methodologies in image processing streamlines the automatic identification and swift extraction of crucial data,effectively tackling the complexities associated with capturing and mitigating these hazardous particles.Combined with the analysis of the growth behavior of particle chain under different applied voltages,it established that a linear relationship exists between the applied voltage and θ.And there is a negative correlation between the average particle chain length and electric field strength at the collection electrode surface(4.2×10^(5)to 1.6×10^(6)V·m^(-1)).The morphology of the deposited particle agglomerate at different electric field strengths is proposed:dendritic agglomerate,long chain agglomerate,and short chain agglomerate.

关 键 词：Artificial intelligence In-situ imaging Submicron particles LAB-ON-A-CHIP DEPOSITION 

分 类 号：TP18[自动化与计算机技术—控制理论与控制工程] X513[自动化与计算机技术—控制科学与工程]