Towards Universal Calibration for Infrared Spectroscopy with Probabilistic Interference Removal
Year: 2026
Type: preprint
Abstract: Structured interferences from substrates, matrices, and instrumental artifacts in mid-infrared (IR) spectra often overlap with analyte features and introduce errors in quantitative analysis. Existing correction methods rely on heuristic parameter selection and frequently perform suboptimally when applied across a diverse set of samples. We present a probabilistic framework, Variational-Inference-based Background Elimination in Spectroscopy (VIBES), for automated estimation of regularization hyperparameters from the data that enables removal of such interferences. Background contributions are modeled using covariance structures learned from analytical blank measurements, analyte signals as residual components from background removal under appropriate probabilistic assumptions that promote robustness and hyperparameters calibrated by maximizing a variational approximation to the model evidence. VIBES is demonstrated on two types of transmission-mode measurements with different types of background variations and analyte features, and shows capability to isolate the analyte absorption spectrum with high correlation (r > 0.95) between absorbance and mass loading across sharp and broad peak spectra. Interference-corrected spectra are furthermore shown to be consistent with absorption coefficients derived from complex refractive indices acquired from other measurement modalities. The possibility for quantitative extraction of analyte spectra in the presence of various interferences suggests a path toward development of universal calibrations for mid-IR spectroscopy.
Source: ChemRxiv
Language: English
Subfield: Analytical Chemistry
Field: Chemistry
Domain: Physical Sciences
Open Access status: green
OpenAlex ID: W7213895188