物理
微流控
牛顿流体
机械
流量(数学)
非牛顿流体
整改
微通道
整流器(神经网络)
热力学
计算机科学
功率(物理)
随机神经网络
机器学习
循环神经网络
人工神经网络
作者
Ran Tao,Tiniao Ng,Yan Su,Zhigang Li
出处
期刊:Physics of Fluids
[American Institute of Physics]
日期:2020-05-01
卷期号:32 (5)
被引量:27
摘要
Flow rectification for Newtonian fluids remains challenging compared with that for non-Newtonian fluids because the physical properties of Newtonian fluids are independent of the structure of flow channels, and flow rectification can only be achieved through direction-dependent flow scenarios. In this work, we fabricate a microfluidic rectifier for Newtonian fluids using asymmetric converging–diverging microchannels. The highest diodicity measured for the rectifier is 1.77, which is 15%–54% higher than previous microfluidic rectifiers for Newtonian fluids. An expression for the diodicity is developed based on two scaling laws for the flow resistances in the forward and backward directions. Numerical simulations are also performed to confirm the experiments.
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