Qian Qing, Xu Wenchang, Tian Haoran, Cheng Wenbo, Zhou Lianqun, Wang Jishuai
School of Biomedical Engineering (Suzhou), Division of Life Sciences and Medicine, University of Science and Technology of China, Hefei 230026, China.
CAS Key Laboratory of Biomedical Diagnostics, Suzhou Institute of Biomedical Engineering and Technology, Chinese Academy of Sciences (CAS), Suzhou 215163, China.
Micromachines (Basel). 2023 Oct 18;14(10):1938. doi: 10.3390/mi14101938.
Over the past few decades, micro liquid dispensing technology has been widely used in biology, chemistry, material and environmental sciences due to its efficacy in processing multiple samples. For practical applications, precise and effective droplet generation is very important. Despite numerous droplet generation methods, the implementation of droplet-on-demand still faces challenges concerning system complexity, precision, cost, and robustness. In this work, a novel on-demand contacting droplet generation method incorporated with model-based feedback control with an image processing unit as a sensor was proposed. By studying droplet identification using image processing techniques, the model of droplet formation was simplified. Then model-based feedback control was implemented using volumes of dispensed samples as sensing signals by tuning related parameters adaptively to resist disturbances. The proposed method was integrated and applied to a homebuilt automated micro liquid dispensing system with droplets ranging from 20 nanoliter to 200 nanoliter. The experimental results demonstrated a high degree of accuracy and precision. Additionally, the proposed system's practical utility was evaluated by analyzing mutations in genes associated with sensorineural hearing loss, verifying its effectiveness.
在过去几十年里，微液体分配技术因其在处理多个样品方面的功效，已在生物学、化学、材料和环境科学中得到广泛应用。对于实际应用而言，精确且有效地产生液滴非常重要。尽管有众多液滴产生方法，但按需产生液滴在系统复杂性、精度、成本和稳健性方面仍面临挑战。在这项工作中，提出了一种新颖的按需接触式液滴产生方法，该方法结合了基于模型的反馈控制，并将图像处理单元用作传感器。通过使用图像处理技术研究液滴识别，简化了液滴形成模型。然后，通过自适应调整相关参数以抵抗干扰，将基于模型的反馈控制应用于以分配样品的体积作为传感信号的情况。所提出的方法被集成并应用于一个自制的自动化微液体分配系统，该系统产生的液滴范围为20纳升至200纳升。实验结果证明了其高度的准确性和精度。此外，通过分析与感音神经性听力损失相关的基因突变来评估所提出系统的实际效用，验证了其有效性。
