Inverse Infrared Spectral Deconvolution for Quantitative Analysis of Polymer Mixtures in Scattering Media

Infrared (IR) spectroscopy is a powerful tool for analyzing complex substances. It allows to identify materials based on their functional groups. Nevertheless, spectral interpretation of composite materials with IR spectroscopy remains a significant challenge for analytical and forensic laboratories, especially if the samples are small, producing significant scattering that complicates the interpretation of IR spectra. Effectively tackling this challenge, we present an innovative IR-based method for non-destructively identifying the individual components within a mixture. Our study focuses on two- and multi-component strongly scattering homogeneous mixed-composition microspheres filled with organic polymers. The results reveal that our algorithm can: 1) reconstruct the pure absorption of functional groups in composite systems by eliminating scattering effects, 2) identify the number of components in a mixture, 3) determine the volume fractions of the constituents, and 4) generate pure permittivity spectra for each component in the mixture. What sets this method apart is its noninvasive nature -- it does not rely on expensive separation techniques such as chromatography or time-consuming calibration processes. Additionally, it may be fully automated, making it accessible for users of various levels of expertise in spectroscopy. The method addresses critical challenges in analytical and forensic chemistry, enabling previously unattainable insights -- such as rapid quantification of trace chemicals in drug formulations for forensic analysis or identification of synthetic polymer blends in environmental microplastics.