I-Corps: Translation Potential of a Microfluidic Electrochemical Gas Sensor Platform for Diagnostics of Airborne Chemicals

This I-Corps project focuses on commercializing a portable, cost-effective, and highly accurate sensor for detecting specific airborne chemical indicators associated with health and agricultural issues. Many critical human health conditions and plant diseases produce unique airborne chemical signatures, known as volatile organic compounds. Current diagnostic approaches rely on complex, expensive, and time-consuming laboratory analyses, requiring samples to be sent off-site. Transportation delays slow intervention and increase costs, hindering widespread early detection. For instance, the early detection of certain human diseases, such as lung cancer, dramatically improves survival rates; however, traditional methods are not readily accessible. Similarly, a substantial portion of global food production is lost annually due to plant diseases, threatening food security and economic stability worldwide. Effective, on-site detection tools are urgently needed to mitigate these challenges. This sensor technology enables rapid and precise identification of these chemical indicators directly where they are required – whether in a clinic or on a farm. Its compact design eliminates the need for cumbersome sample collection and transport, providing immediate results.

This I-Corps project utilizes experiential learning, coupled with a firsthand investigation of the industry ecosystem, to assess the translation potential of the technology. This solution is based on the development of a portable, integrated sensor platform designed for the sensitive and selective detection of airborne volatile organic compounds. The platform incorporates a novel microfluidic electrochemical sensor that facilitates direct, in situ, gas-liquid interactions within a compact architecture. Embedded microelectrodes enable simultaneous electrochemical measurements, enhancing the signal-to-noise ratio. This sophisticated microfluidic design significantly improves the mass transport of target analytes to the sensing interface, resulting in superior sensitivity compared to conventional methods. The system integrates a fluidics module for precise gas sample delivery and a detection module capable of executing various electrochemical techniques, including electrochemical impedance spectroscopy, cyclic voltammetry, and differential pulse voltammetry. A data analysis module processes the electrochemical signatures using trained machine learning models to provide accurate qualitative and quantitative predictions of the compounds present. This integrated approach represents a significant scientific advancement over bulky and time-consuming laboratory-based techniques, offering a robust, rapid, and cost-effective alternative for on-site diagnostics. The goal is to provide immediate, actionable insights for diverse applications, enabling faster decision-making and intervention, thereby transforming current diagnostic workflows in human health and agriculture.

This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

Award Number: 2535040
Principal Investigator: Sagnik Basuray
Funds Obligated: $50,000
State: NJ