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Diaphragm-based microfluidic platforms for reconfigurable sample manipulation: from enrichment to activated sorting.

Abdullah-Bin Siddique1, Shaghayegh Mirhosseini1, Nathan S Swami1,2

  • 1Electrical & Computer Engineering, University of Virginia, Charlottesville, VA, 22904 USA. gcx2vm@virginia.edu.

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Diaphragm-actuated microfluidics offers precise sample manipulation by dynamically reconfiguring channels. This approach unifies analyte enrichment and cell sorting for advanced lab-on-a-chip systems.

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Area of Science:

  • Microfluidics and Lab-on-a-Chip Technologies
  • Biomedical Engineering
  • Analytical Chemistry

Background:

  • Microfluidic systems rely on precise sample manipulation for analytical performance.
  • Existing methods like passive separations and field-based techniques have limitations in tunability and complexity.
  • Diaphragm-based actuation offers a novel solution by dynamically reconfiguring microchannel geometry.

Purpose of the Study:

  • To consolidate diaphragm-actuated microfluidic strategies as a unified framework for active sample manipulation.
  • To review and benchmark various diaphragm actuation schemes and materials.
  • To explore emerging directions for advanced lab-on-a-chip applications.

Main Methods:

  • Review of diaphragm-based microfluidic strategies for sample enrichment and activated sorting.
  • Benchmarking of diaphragm materials, geometries, and actuation schemes (pneumatic, piezoelectric, etc.).
  • Evaluation against performance metrics including pressure-deflection transfer, latency, efficiency, selectivity, and gating accuracy.

Main Results:

  • Diaphragm actuation enables sub-second fluidic control for enrichment (trapping, focusing, nanoconfinement) and sorting (label-based, label-free, hybrid).
  • Various actuation schemes and materials are compared based on quantitative performance metrics.
  • Identified key performance indicators for evaluating diaphragm-actuated systems.

Conclusions:

  • Diaphragm-based actuation provides a versatile platform for autonomous, label-free, and high-content lab-on-a-chip systems.
  • Emerging directions include smart materials, feedback control, scalable fabrication, and AI integration.
  • This approach bridges sample enrichment and activated sorting for next-generation diagnostics and biomanufacturing.