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 (EIS) 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 mM 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 (ssDNA) 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.

Authors

Institutions

Publication Details

Journal
IEEE Sensors Letters
Published
2025-07-14
DOI
https://doi.org/10.1109/lsens.2025.3588757
Citations
2
Primary Topic
Fuel Cells and Related Materials
Type
article
Field-Weighted Citation Impact
1.46
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Fully Automated Microfluidic Electrochemical Platform as a Versatile Biosensor

Niranjan Haridas Menon, Sagnik Basuray, Yassa Beshai
2 citations
IEEE Sensors Letters
Fuel Cells and Related Materials
1.46
article

Fully Automated Microfluidic Electrochemical Platform as a Versatile Biosensor

Niranjan Haridas Menon, Sagnik Basuray, Yassa Beshai
article en
2 citations

Abstract

We present a fully automated microfluidic electrochemical sensing platform capable of executing complex fluidic operations and acquiring high-fidelity electrochemical impedance spectroscopy (EIS) 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 mM 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 (ssDNA) 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.

IEEE Sensors LettersVol. 9(8)
New Jersey Institute of Technology (US)
Affordable and clean energy
Openalex Percentile: Top 16%
Fuel Cells and Related Materials
1.46
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.

Fully Automated Microfluidic Electrochemical Platform as a Versatile Biosensor — Niranjan Haridas Menon, Sagnik Basuray, et al. · IEEE Sensors Letters (2025) | TGRS Research Map | TGRS