Tae-In Jeong, Thanh Mien Nguyen, Eunji Choi, Alexander Gliserin, Thu M T Nguyen, San Kim, Sehyeon Kim, Hyunseo Kim, Gyeong-Ha Bak, Na-Yeong Kim, Vasanthan Devaraj, Eunjung Choi, Jin-Woo Oh, Seungchul Kim
The colorimetric sensor-based electronic nose has been demonstrated to discriminate specific gaseous molecules for various applications, including health or environmental monitoring. However, conventional colorimetric sensor systems rely on RGB sensors, which cannot capture the complete spectral response of the system. This limitation can degrade the performance of machine learning analysis, leading to inaccurate identification of chemicals with similar functional groups. Here, we propose a novel time-resolved hyperspectral (TRH) data set from colorimetric array sensors consisting of 1D spatial, 1D spectral, and 1D temporal axes, which enables hierarchical analysis of multichannel 2D spectrograms via a convolution neural network (CNN)...
March 28, 2024: ACS Sensors