ArticleBioImpacts : BI2026
Computational analysis on design and optimization of low-frequency dielectrophoretic microfluidic lab on a chip for
Article in BioImpacts : BI, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
Introduction: Bloodstream infections (BSIs) caused by Methods: A dual-channel microfluidic separation device was developed with independently operated pathways. The primary channel (2000×198 μm) integrated ten crown-shaped microelectrodes, while the secondary channel (1540×80 μm) incorporated eight microelectrodes. The primary channel isolated both target strains directly from whole blood; the secondary channel enabled further separation between standard Gram-positive MRSA and MSSA. Finite element modeling was performed using COMSOL Multiphysics, which integrated the Electric Currents, Creeping Flow, and Particle Tracing modules. Separation efficiency was evaluated across varying voltages, electrode geometries, and sample-to-buffer flow rate ratios at 1 Hz. Dielectric properties from published data were used to calculate the Clausius-Mossotti (CM) factor for predicting DEP behavior. Results: In the primary channel, nearly 100% separation efficiency and purity were achieved for isolating MRSA and MSSA from red blood cells (RBCs), white blood cells (WBCs), and platelets (PLTs) at 24-28 Vpp and a sample-to-buffer flow rate ratio of 1:2. The secondary channel successfully differentiated MSSA from MRSA at 42-46 Vpp and a 1:5 flow rate ratio, exploiting their distinct membrane characteristics. Crown-shaped electrodes outperformed rectangular designs by generating higher electric field gradients, thereby enhancing separation performance. Conclusion: The dual-channel LOC system enables high-efficiency, label-free separation and identification of MRSA and MSSA directly from whole blood using low-frequency negative DEP (nDEP). The optimized configuration supports rapid pathogen detection, offering substantial advantages over conventional diagnostic platforms.
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