Photonic Nose: Toward System-On-Chip Optical Gas and Odor Sensing

Oregon State University, Corvallis OR

Investigators

Abstract

Gas and odor sensing plays pivotal roles in energy industry, healthcare, food safety, security, defense, and environmental protection, but it still remains a grand challenge given the stringent requirement of sensitivity and selectivity. So why not learning from our noses that have been perfected by millions of years of evolution. The mammalian olfactory system is well recognized for its ability to identify a large number of airborne molecules, far better than most artificial sensors. The objective of this project is to develop a bio-inspired photonic nose (P-nose) system by mimicking the mammalian olfactory system, which will enable ultra-compact optical gas and odor sensing technology with ultra-high sensitivity and specificity. This research will point out a unique way to advance the frontline research of bio-inspired systems and transcend existing bench-top optical gas sensing technology into system-on-chip level for a broad spectrum of engineering applications. The synergy of this research and education will benefit graduate and undergraduate students at the Oregon State University by enhancing the curricula of nanophotonic technology, broaden the participation of under-represented minorities through leveraging the summer research programs of the Student Chapter of the Optical Society of America at OSU, and use a multidisciplinary approach to educate and develop future high-tech entrepreneurs in technology-based ventures. The objective of this project is to investigate a bio-inspired photonic nose system by mimicking the mammalian olfactory system, which will enable system-on-chip optical gas and odor sensing technology with ultra-high sensitivity and specificity. The mammalian olfactory system is well recognized for its ability to identify a large number of airborne molecules, far better than most artificial sensors. The ultra-high sensitivity and specificity of the mammalian olfactory system come from two critical mechanisms: 1) the mucous membrane inside the nasal cavity with large surface areas (>70cm2) to capture trace level of gas and odorant molecules; and 2) a combinatorial response of about four hundred different olfactory receptor neurons to sense more than ten thousand types of odorant. The proposed biomimetic P-nose system will integrate the PIs' recent research breakthroughs in both nanomaterials and photonic devices: 1) nanoporous metal-organic framework materials as highly efficient and selective gas and odorant absorbents mimicking the mucous membrane inside the nasal cavity; and 2) narrow-band plasmonic filter array with ultra-high detection sensitivity that is analogue to olfactory receptor neurons to probe the finger-print infrared absorption spectra of various gas and odorant molecules. A fully system-on-chip optical gas and odor sensing technology will be demonstrated at the end of this project to simultaneously detect multiplex gases including CO2, CH4, and volatile organic compounds at the near-infrared wavelength range. Intellectual Significance: Ultra-compact gas and odor sensors play pivotal roles in many engineering applications. State-of-the-art technology is dominant by electronic nose that relies on arrayed electronic gas sensors made of metal-oxides and conductive polymers, which lack sensitivity and specificity. Compared with exiting E-nose techniques, the proposed biomimetic photonic nose probes the finger-print IR spectra and is expected to bring transformative impact in detection sensitivity, specificity, sensing time, power consumption, as well as the capability to work under extreme conditions such as in explosive gas atmosphere, radiation, or high electric/magnetic fields. Such bio-inspired concept of photonic nose can be ultimately implemented by integrating chip-scale nanophotonic devices with emerging nano-porous materials, and will open a new path toward system-on-chip optical gas sensing with full functionalities including gas capture, sensing, spectroscopy, and pattern recognition.