文献类型：期刊文献

英文题名：An intelligent microfluidic system for automated generation of hydrogel microcapsules with impedance-based feedback

作者：Guo, Jiahao[1,2];Xia, Yucheng[1,2];Jin, Cong[1,2];Shi, Yifan[3,4];Jiang, Guojun[1,2];Ouyang, Liming[1,2];Gu, Zhen[1,2];Zhang, Lixin[1,2];Wang, Huifeng[1,2]

机构：[1]East China Univ Sci & Technol, Key Lab Smart Mfg Energy Chem Proc Minist Educ, Shanghai 200237, Peoples R China;[2]East China Univ Sci & Technol, State Key Lab Bioreactor Engn, Shanghai 200237, Peoples R China;[3]Fudan Univ, Huashan Hosp, Dept Digest Dis, Shanghai 200040, Peoples R China;[4]Fudan Univ, Huashan Hosp, Natl Clin Res Ctr Aging & Med, Shanghai 200040, Peoples R China

年份：2026

卷号：461

外文期刊名：SENSORS AND ACTUATORS B-CHEMICAL

收录：;EI(收录号：20261520494425);WOS:【SCI-EXPANDED(收录号:WOS:001745164100001)】；

基金：This research was funded by National Major Scientific Instruments and Equipments Development Project of National Natural Science Foundation of China (grant number: 32327801) ,the National Natural Science Foundation of China (grant number: 62103148, 62101190) .

语种：英文

外文关键词：Hydrogel microcapsule; Artificial intelligence; Closed-loop control; Impedance detection; 3D droplet microfluidic

摘要：Hydrogel microcapsules (HGMCs) as smart encapsulation systems have garnered significant attention in the fields of biomedical engineering, 3D cell culture and biomimetic material development. Vision-based closed-loop control of microfluidics are widely used to enhance the accuracy and stability for HGMCs generation, but requires extra optical system and high computing resources. In this study, we proposed a novel, closed-loop microfluidic system for HGMCs generation, by integrating 3D flow-focus device, impedance-based feedback and artificial-intelligence-assisted control into a complete solution. For real-time impedance monitoring, microelectrodes were fabricated directly into the microfluidic device. The impedance waveform was both used for diagnosis of the microfluidic system and extracting structure information of HGMCs using a lightweight convolutional neural network (CNN) suitable for deployment on a general-purpose computer. As a result, we prove that the impedance sensing can be used to evaluate the core-shell diameter of the HGMCs, that reaching a resolution of 2.07 & micro;m. We also demonstrated that the closed-loop generation approach can enhance the structure homogeneity of HGMCs, that enabling low coefficient of variation (CV) of the inner diameter (<= 1.87%) and the outer diameter (<= 1.30%). Owing to its advantages including low cost, label-free, adaptability and simple setup, the proposed system provides an effective solution for automatic and large-scale manufacturing of HGMCs.