Separation of Ammonia Isotopologues by Benchtop Drift Tube Ion Mobility Spectrometry and Chemometric Modeling

were calculated, respectively. The presence of moisture in the carrier gas was found to significantly reduce the resolution of isotopologue separation. To address this limitation and enhance signal clarity, the application of wavelet denoising was conducted, with universal thresholding based on Symlet, Daubechies, and Coiflet wavelet families systematically evaluated. The Daubechies wavelet (db9) at level 9 was identified as the optimal denoising approach. Following this, multivariate curve resolution alternating least-squares (MCR-ALS) was employed for the decomposition of the complex overlapping signals into their pure ion mobility spectra and corresponding concentration profiles over time. The integration of wavelet-based denoising and MCR-ALS offers a practical strategy for the enhancement of DTIMS performance in complex isotopologue separation, particularly for future studies focused on quantitative analysis. Future work will involve the integration of steady-state isotopic transient kinetic analysis (SSITKA) for a comprehensive kinetic framework for kinetic models.