Plasmonic Conducting Metal Oxide-Based Optical Fiber Sensors for Chemical and Intermediate Temperature-Sensing Applications.

The demand for real-time sensors in harsh environments at elevated temperature is significant and increasing. In this manuscript, the chemical and temperature sensing using the optical response through the practical fiber platform is demonstrated, and principle component analysis is coupled with targeted experimental film characterization to understand the fundamental sensing layer properties, which dominate measured gas sensing responses in complex gas mixtures. More specifically, tin-doped indium oxide-decorated sensors fabricated with the sol-gel method show stable and stepwise transmission responses varying over a wide range of H2 concentration (5-100%) at 250-350 °C as well as responses to CH4 and CO to a lesser extent. Measured responses are attributed to modifications to the surface plasmon resonance absorption in the near-infrared range and are dominated by the highest concentrations of the most-reducing analyte based upon systematic mixed gas stream experiments. Principal component analysis is utilized for this type of sensor to improve the quantitative and qualitative understanding of responses, clearly identifying that the dominant principle component (PC #1) accounts for ∼78% of total data variance. Correlations between PC #1 and the experimentally derived free carrier concentration confirm that this material property plays the strongest role on the ITO gas sensing mechanism, while correlations between the free carrier mobility and the second most important principle component (PC #2) suggest that this quantity may play a significant but secondary role. As such, the results presented here clarify the relationship between generalized principle components and fundamental sensing materials properties thereby suggesting the pathway toward improved multicomponent gas speciation through sensor layer engineering. The work presented represents a significant step toward the ultimate objective of optical waveguide sensors integrated with multivariate data analytics for multiparameter monitoring with a single sensor element.