Literature DB >> 32599820

Design Applicable 3D Microfluidic Functional Units Using 2D Topology Optimization with Length Scale Constraints.

Yuchen Guo1,2, Hui Pan1, Eddie Wadbro3, Zhenyu Liu1.   

Abstract

Due to the limits of computational time and computer memory, topology optimization problems involving fluidic flow frequently use simplified 2D models. Extruded versions of the 2D optimized results typically comprise the 3D designs to be fabricated. In practice, the depth of the fabricated flow channels is finite; the limited flow depth together with the no-slip condition potentially make the fluidic performance of the 3D model very different from that of the simplified 2D model. This discrepancy significantly limits the usefulness of performing topology optimization involving fluidic flow in 2D-at least if special care is not taken. Inspired by the electric circuit analogy method, we limit the widths of the microchannels in the 2D optimization process. To reduce the difference of fluidic performance between the 2D model and its 3D counterpart, we propose an applicable 2D optimization model, and ensure the manufacturability of the obtained layout, combinations of several morphology-mimicking filters impose maximum or minimum length scales on the solid phase or the fluidic phase. Two typical Lab-on-chip functional units, Tesla valve and fluidic channel splitter, are used to illustrate the validity of the proposed application of length scale control.

Entities:  

Keywords:  fluidic flow; length scale control; morphology mimicking filters; topology optimization

Year:  2020        PMID: 32599820      PMCID: PMC7345215          DOI: 10.3390/mi11060613

Source DB:  PubMed          Journal:  Micromachines (Basel)        ISSN: 2072-666X            Impact factor:   2.891


  5 in total

Review 1.  Design of pressure-driven microfluidic networks using electric circuit analogy.

Authors:  Kwang W Oh; Kangsun Lee; Byungwook Ahn; Edward P Furlani
Journal:  Lab Chip       Date:  2011-12-16       Impact factor: 6.799

2.  The lab finally comes to the chip!

Authors:  George Whitesides
Journal:  Lab Chip       Date:  2014-09-07       Impact factor: 6.799

3.  Tri-fluid mixing in a microchannel for nanoparticle synthesis.

Authors:  Xiangsong Feng; Yukun Ren; Likai Hou; Ye Tao; Tianyi Jiang; Wenying Li; Hongyuan Jiang
Journal:  Lab Chip       Date:  2019-08-05       Impact factor: 6.799

4.  Topology Optimization of Passive Micromixers Based on Lagrangian Mapping Method.

Authors:  Yuchen Guo; Yifan Xu; Yongbo Deng; Zhenyu Liu
Journal:  Micromachines (Basel)       Date:  2018-03-20       Impact factor: 2.891

Review 5.  A Review on Micromixers.

Authors:  Gaozhe Cai; Li Xue; Huilin Zhang; Jianhan Lin
Journal:  Micromachines (Basel)       Date:  2017-09-11       Impact factor: 2.891

  5 in total

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