Visualize the Gas Spreading Over Time as Separate Trajectories with Matrix Decomposition Based on the Linearity of LSPR Gas Sensor Response

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  • Zheng Xiaofan
    Graduate School of Information Science and Electrical Engineering, Department of Informatics, Kyushu University
  • Matsuoka Masato
    Graduate School of Information Science and Electrical Engineering, Department of Electronics, Kyushu University
  • Hayashi Kenshi
    Graduate School of Information Science and Electrical Engineering, Department of Electronics, Kyushu University
  • Tomiura Yoichi
    Graduate School of Information Science and Electrical Engineering, Department of Informatics, Kyushu University

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<p>Detecting and visualizing gas distributed in two dimensions is enabled by the localized surface plasmon resonance (LSPR) gas sensor. This study provides a method for analyzing measurement data that allows component gases to be visualized separately. The degree of decrease in the intensity of the transmitted light (corresponding to the absorbance) due to the effect of the surrounding gas on the sensor was taken as the response of the sensor, and an approximate linear proportionality between the gas concentration and the response of the sensor was assured through measuring the sample of gas sources in different dilutions. Because the responses of gas sensor to mixed gases can be regarded as the sum of the responses to each component gas with respect to its concentration, this proportionality lead the possibility to estimate the concentration distribution of component gases by applying the algorithm of matrix decomposition. We applied matrix decomposition to real measurement data and visualized the component gases spreading over time. Moreover, we discussed the impact of speculating on the number of components in our case by conducting a simulation experiment.</p>

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