Zhao Yanfeng, Zheng Zhiqiang, Liu Jiaxin, Dong Xinyi, Yang Haotian, Wu Anping, Shi Qing, Wang Huaping
Intelligent Robotics Institute, School of Mechatronical Engineering, Beijing Institute of Technology, Beijing 100081, China.
Department of Biomedical Engineering, City University of Hong Kong, Hong Kong 999077, China.
Cyborg Bionic Syst. 2025 Mar 6;6:0217. doi: 10.34133/cbsystems.0217. eCollection 2025.
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.
数字微流控芯片(DMCs)因其出色的液滴操控能力,在生化分析应用中展现出巨大潜力。驱动力是表征和优化液滴操控性能的关键因素。对驱动力进行数值分析对于DMC设计至关重要,因为它有助于优化结构参数。尽管数值分析取得了进展,但评估部分填充电极中的驱动力仍然具有挑战性。在此,我们提出了一种通用的电动力学模拟模型,旨在分析部分填充电极的驱动力,以优化DMC的结构参数。该模型利用有限元分析来确定DMC内的电压分布,并根据虚功原理计算作用在液滴上的驱动力。使用这个电动力学模拟模型,我们评估了各种结构参数的影响,包括介电层的介电常数和厚度、液滴的介电常数和电导率以及基板间距,对液滴驱动力的影响。这种评估有助于优化结构参数,并增强DMC的液滴操控能力。液滴加速度的测量表明,部分填充电极上的液滴加速度与模拟的驱动力趋势一致,这验证了所提出的电动力学模拟模型的有效性。我们预计,该电动力学模拟模型能够评估复杂DMC中部分填充电极的驱动力,为DMC未来的结构设计提供前所未有的可能性。