Improved Algorithm for Quantitative Analyses of Infrared Spectra of Multicomponent Gas Mixtures with Unknown Compositions

Abstract

We present a major improvement of an algorithm based on a spectral library search for the quantitative analysis of multicomponent gas samples with unknown compositions. A quantitative spectral database of infrared spectra is used as a training set to compute regression coefficients. Concentrations are computed in the principal component space via principal component regression (PCR). In addition to previous algorithms, we introduce a rating for each candidate substance depending on the concentration found with PCR and a filter that removes candidates that are predicted with negative concentrations if their rating is below a certain threshold. Negative concentrations arise when the measured spectrum contains components that are not contained in the database. The PCR is recomputed until all candidates have a rating above the threshold. Then an adaptive filter "subtracts" the substance with the highest rating from both the measured spectrum and the library and appends it to a hit list. The iteration of this procedure directly produces a list of substances in order of descending importance (i.e., contribution to the measured absorbance) with their corresponding concentrations. The algorithm is tested on spectra of multicomponent surgical smoke samples. The four main components (water, methane, ethane, and ethene) are identified correctly (within the top 5 of the hit list) for an appropriate choice of the rating threshold. The algorithm describes the composition of the smoke sample correctly despite the presence of features in the spectrum that cannot be explained by the spectrum of any single substance present in the database.

Infrared Spectroscopy on Smoke Produced by Cauterization of Animal Tissue

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Chemical analysis of surgical smoke by infrared laser spectroscopy

“…The spectra measured with the MIR DFG spectrometer were qualitatively similar for most of the 27 measured smoke samples. The spectra were analyzed with a specially developed algorithm [52] and a database of FTIR spectra [53]. A typical absorption spectrum measured at room temperature and ambient pressure is shown in Fig.…”

Quantitative Chemical Analysis of Surgical Smoke Generated During Laparoscopic Surgery With a Vessel-Sealing Device

“…59 By using all the known absorption lines in the available spectral range, the resulting concentration values are very robust against noise and interference from, for example, overlapping absorption lines belonging to other substances. The algorithm provides the constituents of the sample and their concentrations.…”