ANN-Based Instantaneous Simulation of Particle Trajectories in Microfluidics

被引:6
|
作者
Zhang, Naiyin [1 ]
Liang, Kaicong [2 ]
Liu, Zhenya [2 ]
Sun, Taotao [2 ]
Wang, Junchao [2 ]
机构
[1] Hangzhou Dianzi Univ, Sch Automat, Hangzhou 310018, Peoples R China
[2] Hangzhou Dianzi Univ, Key Lab RF Circuits & Syst, Minist Educ, Hangzhou 310018, Peoples R China
基金
中国国家自然科学基金;
关键词
microfluidics; machine learning; particle trajectory; design automation; computer-aided design;
D O I
10.3390/mi13122100
中图分类号
O65 [分析化学];
学科分类号
070302 ; 081704 ;
摘要
Microfluidics has shown great potential in cell analysis, where the flowing path in the microfluidic device is important for the final study results. However, the design process is time-consuming and labor-intensive. Therefore, we proposed an ANN method with three dense layers to analyze particle trajectories at the critical intersections and then put them together with the particle trajectories in straight channels. The results showed that the ANN prediction results are highly consistent with COMSOL simulation results, indicating the applicability of the proposed ANN method. In addition, this method not only shortened the simulation time but also lowered the computational expense, providing a useful tool for researchers who want to receive instant simulation results of particle trajectories.
引用
收藏
页数:9
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