SBIR Phase I: Optimizing Ion Mobility Spectrometry for Distributed Chemical Sensing

The broader impact/commercial potential of this Small Business Innovation Research Phase I project seeks to produce a high performance, low power, electronic chemical sensor system that does not require a radioactive ionization source. Achieving a low cost, non-radioactive Internet of Things (IoT) systems for chemical sensing in a more distributed and connected network has potentially far reaching implications in many industries. Creating an IoT network of sensors to safely monitor chemical signatures on a large and distributed scale, in real-time, may provide new analytical-quality chemical sensing capabilities. Sensor applications may range from engineering (monitoring fermentations) and to health care (diagnostics), to environmental monitoring (air quality) and defense and security (hazard detection) or agriculture (waste mitigation). The chemical sampling and sensor platform has the potential to be integrated with cell phones and autonomous systems. The market for personal use devices could be substantial.This Small Business Innovation Research (SBIR) Phase I project seeks to establish an experimental and theoretical framework to optimize Differential Mobility Spectrometry (DMS) for analytical quality chemical identification. There are many types of chemical sensors that have been commercialized but no high-quality systems meet the performance, safety, and cost constraints required to be a successfully linked in an IoT system. The fundamental physics and commercial utility of DMS is well established, so it is a leading candidate for this use. The foundation of the system is a miniaturized DMS. Because the microchip operates on lithium ion polymer batteries, it has the potential for widely dispersed IoT-linked chemical sensing but the reliance on radioactive isotopes for chemical ionization is a critical barrier to adoption that limits commercial applications. This technical barrier may be overcome by combining a non-radioactive, plasma-based method of chemical ionization. The experimental results will be used to validate custom software to simulate performance of this complex system. If the performance of the combined system can be successfully modeled, it can be further miniaturized and optimized. The detection of natural gas odorants and selected food and flavor compounds have been selected as initial proof-of-concept commercial applications.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.