In Situ Fabrication of Controlled Porous Manifold Coupled with Non-Planar Microelectrodes for Microfluidic Biosensors

Abstract

The demand for a versatile and portable point-of-use (POU) sensor platform has surged due to the pandemic, especially in countries with limited medical laboratory facilities. We recently unveiled a portable, non-planar, interdigitated, flow-through, porous electrode platform that automatically measures electrochemical impedance spectroscopy (EIS) signals from various biomarkers. However, the packed powder exhibited a loss of performance over time due to displacement, leaching, and poor stability. Herein, we modified the packing strategy by synthesizing the sensing material within the channel, thereby improving adhesion, structural integrity, and stability. Leveraging the exceptional thermal stability, mechanical strength, and chemical resistance of polyimide (PI), we developed a novel fabrication approach that combines liquid-phase inversion and breath-figure techniques to create a porous PI manifold with single-walled carbon nanotubes (SWCNTs) under varying humidity conditions. Scanning electron microscope (SEM) analysis revealed that lower relative humidity (RH) conditions yield larger but less uniformly distributed pores, leading to increased channel pressure. The manifold demonstrated exceptional stability under rigorous flow conditions, withstanding a high flow rate of 30 µL/min while maintaining consistent pressure-EIS responses. The device produced a measurable proof-of-concept impedance response following exposure to a femtomolar concentration of complementary target ssDNA in 1× PBS within 15 min. A formal limit of detection was not determined in the present study. We developed a mechanically stable sensor design with improved durability under repeated flow conditions by systematically optimizing synthesis conditions and manifold configuration. This innovative fabrication strategy demonstrates the importance of packing methodology in sensor design and paves the way for robust, scalable, and efficient diagnostic solutions in resource-limited settings.