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.
Lab on a Chip
|January 14, 2026
Summary
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.
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.


