TY - JOUR
T1 - Structural Optimization of Microfluidic Chips for Enhancing Droplet Manipulation and Observation via Electrodynamics Simulation
AU - Zhao, Yanfeng
AU - Zheng, Zhiqiang
AU - Liu, Jiaxin
AU - Dong, Xinyi
AU - Yang, Haotian
AU - Wu, Anping
AU - Shi, Qing
AU - Wang, Huaping
N1 - Publisher Copyright:
Copyright © 2025 Yanfeng Zhao et al.
PY - 2025
Y1 - 2025
N2 - Digital microfluidic chips (DMCs) have shown huge potential for biochemical analysis applications due to their excellent droplet manipulation capabilities. The driving force is a critical factor for characterizing and optimizing the performance of droplet manipulation. Conducting numerical analysis of the driving force is essential for DMC design, as it helps optimize the structural parameters. Despite advances in numerical analysis, evaluating driving forces in partially filled electrodes remains challenging. Here, we propose a versatile electrodynamics simulation model designed to analyze the driving forces of partially filled electrodes to optimize the structural parameters of DMCs. This model utilizes finite element analysis to determine the voltage distribution within the DMC and calculates the driving force acting on the droplets using the principles of virtual work. Using this electrodynamics simulation model, we evaluated the effects of various structural parameters, including the dielectric constant and thickness of the dielectric layer, the dielectric constant and conductivity of the droplet, and substrate spacing, on the droplet driving force. This evaluation helps to optimize the structural parameters and enhances the droplet manipulation of DMCs. Measurements of droplet acceleration demonstrated that the droplet acceleration on the partially filled electrode aligns with the simulated driving force trend, which verified the effectiveness of the proposed electrodynamics simulation model. We anticipate that the electrodynamics simulation model is capable of evaluating the driving force in partially filled electrodes within complex DMCs, offering unprecedented possibilities for future structural designs of DMCs.
AB - Digital microfluidic chips (DMCs) have shown huge potential for biochemical analysis applications due to their excellent droplet manipulation capabilities. The driving force is a critical factor for characterizing and optimizing the performance of droplet manipulation. Conducting numerical analysis of the driving force is essential for DMC design, as it helps optimize the structural parameters. Despite advances in numerical analysis, evaluating driving forces in partially filled electrodes remains challenging. Here, we propose a versatile electrodynamics simulation model designed to analyze the driving forces of partially filled electrodes to optimize the structural parameters of DMCs. This model utilizes finite element analysis to determine the voltage distribution within the DMC and calculates the driving force acting on the droplets using the principles of virtual work. Using this electrodynamics simulation model, we evaluated the effects of various structural parameters, including the dielectric constant and thickness of the dielectric layer, the dielectric constant and conductivity of the droplet, and substrate spacing, on the droplet driving force. This evaluation helps to optimize the structural parameters and enhances the droplet manipulation of DMCs. Measurements of droplet acceleration demonstrated that the droplet acceleration on the partially filled electrode aligns with the simulated driving force trend, which verified the effectiveness of the proposed electrodynamics simulation model. We anticipate that the electrodynamics simulation model is capable of evaluating the driving force in partially filled electrodes within complex DMCs, offering unprecedented possibilities for future structural designs of DMCs.
UR - http://www.scopus.com/inward/record.url?scp=86000665862&partnerID=8YFLogxK
U2 - 10.34133/cbsystems.0217
DO - 10.34133/cbsystems.0217
M3 - Article
AN - SCOPUS:86000665862
SN - 2097-1087
VL - 6
JO - Cyborg and Bionic Systems
JF - Cyborg and Bionic Systems
M1 - 0217
ER -