Methods for Detection and Identification of Chemical Compounds Using GC-IMS

Gas Chromatography-Ion Mobility Spectrometry (GC-IMS) is a powerful analytical technique for separating and identifying chemical compounds. The resulting data is represented as a matrix image, where peak locations correspond to specific compounds that must be accurately detected, isolated, and correlated with the concentrations present in the sample. This work presents a tailored approach for peak detection in GC-IMS data, with a focus on tracking concentration variations. The methodology is designed for relative short columns and applied across diverse solution matrices. Short-column GC-IMS is particularly valuable for rapid detection applications, such as the identification of chemical warfare agents (CWAs). However, its reduced separation efficiency leads to broader peaks and increased signal overlap, making peak differentiation more challenging, especially in complex matrices. To address these limitations, we employ signal processing techniques to preprocess data, define regions of interest (ROIs), and apply localized peak detection, enhancing both sensitivity and accuracy. As a practical application, we detect tributylphosphate (TBP), a toxic industrial chemical (TIC) commonly used as a simulant for nerve agents, across various matrices, including diesel, oil, solvent, sand, and mixtures containing other hazardous chemicals. A short GC column is used to reduce acquisition time and minimize exposure to hazardous substances, albeit at the cost of resolution. The results demonstrate the effectiveness of the proposed method, successfully detecting, distinguishing, and quantifying peaks in the acquired data.