Analytical capabilities of chemiresistive microsensor arrays in a simulated Martian atmosphere

The capabilities of a chemiresistive microsensor array for detecting and identifying trace target analytes were examined under a simulated Martian atmosphere. The simulated environment included low oxygen content (0.15%) balanced by carbon dioxide, low pressure (7.5 hPa) and temperature (199.1 K), and trace levels of up to three target molecules presented simultaneously. The target molecules were selected from four possible analytes (methane, hydrogen, ethane and sulfur dioxide), presented to the sensor array at multiple concentrations of 200 nmol/mol or less. Signals from four elements of a 16-element microsensor array were employed in the data analyses described. Each element used a different sensing film and was operated with a dynamic temperature program tuned to the background environment. The rich data streams collected from the microsensor array as it was exposed to the complex mixtures and carbon dioxide-based background were analyzed using two approaches: Linear Discriminant Analysis (LDA) and Partial Least Squares Discriminant Analysis (PLS-DA). Analysis of the data by LDA was used for initial assessment of the data streams, and indicated that the data from the microsensor array provided sufficient information to identify, and potentially quantify, each of the target analytes. Further analysis showed that it was possible to separate the methane from the other analytes, as demonstrated after analyzing the data by PLS-DA. Furthermore, the models developed using PLS-DA on one day were able to discriminate the analytes on other days. The success rate was qualitatively dependent on the length of time between the day on which the model was trained and the day on which the validation data were acquired. The work demonstrates the potential of this microsensor array approach to be further developed as a low mass, low-power-consumption screening tool for space exploration.