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Electrochemical Microfluidic Platform for Bacterial Identification

Jul 2026 · ECS Meeting Abstracts · Vol MA2026-01, pp. 2500-2500 · 0 citations

TL;DR

This platform demonstrates how nanoscale plasmonic–electrochemical coupling can overcome fundamental kinetic limitations in molecular diagnostics for point-of-care bacterial identification, enabling robust detection even in complex biological matrices without sample pre-culture.

Abstract

The accelerating global burden of antimicrobial resistance is driven in part by delays in accurate bacterial identification, which frequently necessitate empiric broad-spectrum antibiotic therapy. Conventional identification methods rely on culture-based workflows or centralized laboratory infrastructure, resulting in prolonged turnaround times that limit timely clinical decision-making and compromise antimicrobial stewardship. Rapid, culture-free diagnostic approaches capable of identifying bacterial pathogens are therefore urgently needed. We present a plasmonically enhanced electrochemical microfluidic system for rapid bacterial identification that integrates nucleic acid amplification with nanoscale signal amplification. Species-specific bacterial DNA is targeted using loop-mediated isothermal amplification (LAMP), while nanostructured plasmonic metasurfaces promote hot-electron generation under optical excitation, enhancing interfacial charge transfer and reaction kinetics. During amplification, proton release drives the reduction of a redox-active reporter, producing a measurable electrochemical signal that is captured using differential pulse voltammetry. Plasmonic enhancement improves sensitivity and signal-to-noise ratios, enabling robust detection even in complex biological matrices without sample pre-culture. Using this approach, bacterial identification is achieved within approximately 15 minutes of signal acquisition, with high analytical specificity. This platform demonstrates how nanoscale plasmonic–electrochemical coupling can overcome fundamental kinetic limitations in molecular diagnostics for point-of-care bacterial identification.

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