Compensation of temperature effects on spectra through evolutionary rank analysis.

Abstract

Spectra measured in various ranges of temperature are usually slightly different from each other in shape and position of the bands. Although the displayed inconsistencies are rather small, yet may lead to incorrect analysis and interpretation of the collected spectrothermal data. Thus the unspecific spectral effects induced by temperature, in particular the thermal shifts and broadening of the bands, have to be compensated. In the paper, a simple two-step method of thermospectral dataset uniformisation is presented. Thermally induced 'movement' of the bands is approximated as a linear function of the difference of temperatures, so the co-shifting of the spectra is done linearly. Thermal broadening is mimicked by convoluting the low-temperature signal (spectrum) with a Gaussian or Lorentzian spreading filter. Proper widths (values of FWHM) of these filters, used to uniform the whole dataset, are assumed to depend on the difference of temperatures, in a form of one-parameter functions. This assumption, which has been empirically confirmed, is a fundamental premise of the method of Partial Compensation for Thermal Broadening (PCTB). Optimal values of the parameters of all the functions, used to compensate both thermal shifting and broadening, are found by the Evolutionary Rank Analysis (ERA) applied on an evolving data matrix. Efficiency of the proposed approach was verified on the UV-Vis thermospectral dataset of one-component model systems. In addition, since the method is aimed at making uniformed the thermospectral datasets of multi-component systems with similar spectral properties of individual components, the two-component conformer system of t-APE (trans-1-(2'-anthryl)-2-phenylethene) has also been analyzed.