Yang Zhenyu, Jiang Zhongning, Lin Haisong, Fan Xiaoxue, Wu Changjin, Lam Edmund Y, So Hayden K H, Shum Ho Cheung
Advanced Biomedical Instrumentation Centre, Hong Kong Science Park, Shatin, New Territories, Hong Kong, China.
Department of Mechanical Engineering, The University of Hong Kong, Hong Kong, China.
Sci Adv. 2025 Aug;11(31):eadx2826. doi: 10.1126/sciadv.adx2826. Epub 2025 Jul 30.
Microfluidic fabrication technologies are increasingly used to produce functional anisotropic microstructures for broad applications. However, the limited flow manipulation methods hinder the production of intricate microstructure morphologies. In this work, we introduce CeyeHao, an artificial intelligence-driven flow programming methodology for designing microchannels to perform unprecedented flow manipulations. In CeyeHao, microchannels containing hierarchically assembled obstacles are constructed, offering more than double flow transformation modes and immense configurability compared to state-of-the-art methods. An AI model, CEyeNet, predicts the transformed flow profiles, reducing computation time by up to 2700 folds and achieving up to 97 and 90% accuracy with simulated and experiment results. CeyeHao facilitates microchannel design in both human-guided and automatic modes, enabling creation of flow morphologies with highly regulated geometries and elaborate artistic patterns, along with precise topology manipulation of multiple streams. The superior flow manipulation capability of CeyeHao can facilitate broad applications from complex microstructure fabrication to precise reaction control.
微流体制备技术越来越多地用于生产功能性各向异性微结构，以实现广泛的应用。然而，有限的流动操纵方法阻碍了复杂微结构形态的产生。在这项工作中，我们引入了CeyeHao，这是一种由人工智能驱动的流动编程方法，用于设计微通道以执行前所未有的流动操纵。在CeyeHao中，构建了包含分层组装障碍物的微通道，与现有方法相比，提供了两倍以上的流动转换模式和巨大的可配置性。一个人工智能模型CEyeNet预测转换后的流动剖面，将计算时间减少多达2700倍，并在模拟和实验结果中分别达到高达97%和90%的准确率。CeyeHao在人工引导和自动模式下都便于微通道设计，能够创建具有高度规则几何形状和精细艺术图案的流动形态，以及对多个流进行精确的拓扑操纵。CeyeHao卓越的流动操纵能力可促进从复杂微结构制造到精确反应控制等广泛的应用。
