A miniature electronic nose (ENose) has been designed and built at the Jet Propulsion Laboratory (JPL), Pasadena, CA, and was designed to detect, identify, and quantify ten common contaminants and relative humidity changes. The sensing array includes 32 sensing films made from polymer carbon-black composites. Event identification and quantification were done using the Levenberg-Marquart nonlinear least squares method. After successful ground training, this ENose was used in a demonstration experiment aboard STS-95 (October-November, 1998), in which the ENose was operated continuously for six days and recorded the sensors' response to the air in the mid-deck. Air samples were collected daily and analyzed independently after the flight. Changes in shuttle-cabin humidity were detected and quantified by the JPL ENose; neither the ENose nor the air samples detected any of the contaminants on the target list. The device is microgravity insensitive.

An array-based sensing system based on 32 polymer/carbon composite conductometric sensors is under development at JPL. Until the present phase of development, the analyte set has focused on organic compounds (common solvents) and a few selected inorganic compounds, notably ammonia and hydrazine.

We report a quantitative structure-activity relationships ͑QSAR͒ study using genetic function approximations to describe the activities of a polymer-carbon composite chemical vapor sensor using a novel approach to selecting a molecular descriptor set. The measured sensor responses are conductivity changes in polymer-carbon composite films upon exposure to target vapors at partsper-million concentrations. The descriptor set combines the basic analyte descriptor set commonly used in QSAR studies with descriptors for sensing film-analyte interactions. The basic analyte descriptors are obtained using a combination of empirical and semiempirical quantitative structure-property relationships methods. The descriptors for the sensing film-analyte interactions are calculated using molecular modeling and simulation tools. A statistically validated QSAR model was developed for a training data set consisting of 17 analyte molecules. The applicability of this model was also tested by predicting sensor activities for three test analytes not considered in the training set.

The Third Generation ENose is an air quality monitor designed to operate in the environment of the US Lab on the International Space Station (ISS). It detects a selected group of analytes at target concentrations in the ppm regime at an environmental temperature range of 18 -30 o C, relative humidity from 25 -75% and pressure from 530 to 760 torr. This device was installed and activated on ISS on Dec. 9, 2008 and has been operating continuously since activation. Data are downlinked and analyzed weekly. Results of analysis of ENose monitoring data show the short term presence of low concentration of alcohols, octafluoropropane and formaldehyde as well as frequent short term unknown events.

An array-based sensing system based on polymercarbon composite conductometric sensors is under development at JPL for use as an environmental monitor in the International Space Station. Sulfur dioxide has been added to the analyte set for this phase of development. Using molecular modeling techniques, the interaction energy between SO 2 and polymer functional groups has been calculated, and polymers selected as potential SO 2 sensors. Experiment has validated the model and two selected polymers have been shown to be promising materials for SO 2 detection.