Comprehensive Data Analysis using Regions of Interest Multivariate Curve Resolution for Ion Mobility Mass Spectrometry: analysis of plastic additives.

Published

June 22, 2026

Author(s)

Yamil Simon, Ana Torres-Agullo, Silvia Lacorte, Roma Tauler

Abstract

Ion mobility enhances liquid chromatography-mass spectrometry identification capabilities by providing an additional dimension that improves mass coverage, sensitivity, and resolving power, and it is particularly valuable for untargeted analysis. However, the high dimensionality and large amount of information in the datasets obtained in this type of analysis are a big challenge for data processing, enabling its broader application and potential. The Regions of Interest Multivariate Curve Resolution (ROIMCR) approach is a chemometric method based on the bilinear model intrinsic data structure of the data. It represents an effective strategy for efficient feature extraction, deconvolution, and resolution of overlapping signals in complex datasets without losing relevant information and maintaining instrumental mass accuracy. In this work, the application of the ROIMCR method is shown for the first time for liquid chromatography ion mobility mass (IM) spectrometry in data-dependent acquisition (DDA) mode, including MS1 and MS2 datasets for the analysis of plastic additives. An improvement in the discrimination of isomeric species and minimization of interferences was shown, leading to more reliable profiles. IM-MS data from 5 microsphere standards and three plastic samples leaching experiments, all composed of PE, containing complex mixtures of unknown additives, were analysed, resolved, and collision cross-section (CCS) values were calculated for each component. The methodology allowed the direct link between the IM signals and the identification of 14 different plastic additives, including phthalates, siloxanes, or phosphates, present in the original polymers. Our findings demonstrate that ROIMCR provides an effective and scalable solution for extracting meaningful information from complex IM datasets.

Citation

Analytical and Bioanalytical Chemistry

Pub Type

Journals

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Keywords

Ion Mobility, Liquid Chromatography, Mass Spectrometry, Multivariate Curve Resolution

Citation

Simon, Y. , Torres-Agullo, A. , Lacorte, S. and Tauler, R. (2026), Comprehensive Data Analysis using Regions of Interest Multivariate Curve Resolution for Ion Mobility Mass Spectrometry: analysis of plastic additives., Analytical and Bioanalytical Chemistry, [online], https://tsapps.nist.gov/publication/get_pdf.cfm?pub_id=960808 (Accessed September 26, 2026)

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