Widely accessible method for 3D microflow mapping at high spatial and temporal resolutions  

作　　者：Evan Lammertse Nikhil Koditala Martin Sauzade Hongxiao Li Qiang Li Luc Anis Jun Kong Eric Brouzes 

机构地区：[1]Department of Biomedical Engineering,Stony Brook University,Stony Brook,NY 11794,USA [2]Department of Mathematics and Statistics,Department of Computer Science,Georgia State University,Atlanta,GA 30302,USA [3]Laufer Center for Physical and Quantitative Biology,Stony Brook University,Stony Brook,NY 11794,USA [4]Cancer Center,Stony Brook School of Medicine,Stony Brook,NY 11794,USA [5]Institute for Engineering Driven Medicine,Stony Brook University,Stony Brook,NY 11794,USA

出　　处：《Microsystems & Nanoengineering》2022年第4期57-71,共15页微系统与纳米工程（英文）

基　　金：the manuscript.This work was supported by an award from the National Science Foundation(NSF)-CBET(No.1705578).

摘　　要：Advances in microfluidic technologies rely on engineered 3D flow patterns to manipulate samples at the microscale.However,current methods for mapping flows only provide limited 3D and temporal resolutions or require highly specialized optical set-ups.Here,we present a simple defocusing approach based on brightfield microscopy and open-source software to map micro-flows in 3D at high spatial and temporal resolution.Our workflow is both integrated in ImageJ and modular.We track seed particles in 2D before classifying their Z-position using a reference library.We compare the performance of a traditional cross-correlation method and a deep learning model in performing the classification step.We validate our method on three highly relevant microfluidic examples:a channel step expansion and displacement structures as single-phase flow examples,and droplet microfluidics as a twophase flow example.First,we elucidate how displacement structures efficiently shift large particles across streamlines.Second,we reveal novel recirculation structures and folding patterns in the internal flow of microfluidic droplets.Our simple and widely accessible brightfield technique generates high-resolution flow maps and it will address the increasing demand for controlling fluids at the microscale by supporting the efficient design of novel microfluidic structures.

关 键 词：FLOW RESOLUTION METHOD 

分 类 号：TP271.31[自动化与计算机技术—检测技术与自动化装置]