Abstract-Qualitative and quantitative analysis of terahertz gas-phase spectroscopy using independent component analysis

Zhijie Li, Nick Rothbart, Xiaojiao Deng, Hua Geng, Xiaoping Zheng, Philipp Neumaier, Heinz-Wilhelm Hübers, 



https://www.sciencedirect.com/science/article/abs/pii/S0169743920300307

This study aims at the qualitative and quantitative analysis of the absorption spectra of gas mixtures measured around 245 GHz. Gas-phase spectra of several volatile organic compounds were measured at different pressures. Based on these spectral data, the independent component analysis (ICA) was applied to recover the components’ spectra and predict their relative concentrations. It is demonstrated that the ICA method is a promising tool to decompose the mixture spectra contributing to high-accuracy qualitative and quantitative analysis of terahertz gas-phase spectroscopy.

Abstract-Terahertz Spectrum Analysis Based on Empirical Mode Decomposition

https://link.springer.com/article/10.1007%2Fs10762-017-0394-x

Precise identification of terahertz absorption peaks for materials with low concentration and high attenuation still remains a challenge. Empirical mode decomposition was applied to terahertz spectrum analysis in order to improve the performance on spectral fingerprints identification. We conducted experiments on water vapor and carbon monoxide respectively with terahertz time domain spectroscopy. By comparing their absorption spectra before and after empirical mode decomposition, we demonstrated that the first-order intrinsic mode function shows absorption peaks clearly in high-frequency range. By comparing the frequency spectra of the sample signals and their intrinsic mode functions, we proved that the first-order function contains most of the original signal’s energy and frequency information so that it cannot be left out or replaced by high-order functions in spectral fingerprints detection. Empirical mode decomposition not only acts as an effective supplementary means to terahertz time-domain spectroscopy but also shows great potential in discrimination of materials and prediction of their concentrations