ODOR DISCRIMINATION USING STEADY-STATE AND TRANSIENT CHARACTERISTICS OF TIN-OXIDE SENSORS

The development of useful chemical microsystems must include the selection of sensors and signal processing sufficient to solve chemical-sensing problems in an accurate and robust manner. Unfortunately, many microelectronic chemical sensors suffer from drift, mismatch, and reproducibility problems that limit their performance in such microsystems. Appropriate signal processing, however, can overcome these limitations. Here, a chemical sensor array architecture and signal-processing framework are presented to discriminate between reducing chemicals in an array of tin-oxide sensors. The array consists of tin-oxide sensors operating at various temperatures, and the resulting steady-state and transient behaviors of these sensors are analyzed and thresholded into a binary output. This binary representation of an odor is constant over sensor drift and concentration changes, while remaining sufficient to discriminate between a variety of reducing chemicals (acetone, ethanol, hexane, isopropanol, methanol, and carbon monoxide) as well as mixtures containing two of these chemicals.