Fully Automated Microfluidic Electrochemical Platform as a Versatile Biosensor

We present a fully automated microfluidic electrochemical sensing platform capable of executing complex fluidic operations and acquiring high-fidelity electrochemical impedance spectroscopy data. The system is automated using Python, enabling open-source automation. It demonstrates strong signal stability and reproducibility, validated by consistent impedance responses across multiple cycles of potassium chloride solutions at 10 and 100 mM concentrations. Integrated pressure sensing enables real-time monitoring of pressure drops across the microfluidic channel, offering diagnostic insights into potential issues, such as leakage, packing failure, or bubble formation. The sensing capability of the platform was evaluated by detecting single-stranded DNA sequences. The system exhibited a selective response, with an approximately 70% greater change in charge transfer resistance upon exposure to an entirely complementary target DNA sequence compared to a completely mismatched sequence. These results highlight the system's sensitivity and sequence specificity. This work demonstrates the development of a versatile, compact, and automated electrochemical microfluidic platform with potential applications in point-of-care diagnostics for nucleic acids, proteins, and other relevant biomarkers, including those associated with zoonotic diseases.