Toward Accurate PAH IR Spectra Prediction: Handling Charge Effects with Classical and Deep Learning Models.

Polycyclic aromatic hydrocarbons (PAHs) play a crucial role in astrochemistry, environmental studies, and combustion chemistry, yet interpreting their infrared (IR) spectra remains challenging due to the similarity of spectral features of many molecules. The presumable presence of both neutral and charged PAHs in mixtures complicates spectra interpretation, too. While first-principle calculations provide accurate spectral predictions, their high computational cost limits scalability.

Recovering fluorescence spectra hidden by scattering signal: In search of the best smoother.

Interpolation of the scattering areas in fluorescence excitation-emission matrices is a useful preprocessing method in fluorescence spectroscopy and data modelling. Commonly used row-by-row interpolation using piecewise cubic Hermite interpolating polynomials smoother (PCHIP), however, frequently leads to artifacts because it does not make any use of the information in the other dimension. We have suggested the way of constructing the penalty matrices for Whittaker smoothing that removed one of the main sources of difference between the axis of multiparametric signal - the grid step size - thus making it possible to reduce the number of parameters to optimize.

Towards Automated Classification of Zooplankton Using Combination of Laser Spectral Techniques and Advanced Chemometrics.

Zooplankton identification has been the subject of many studies. They are mainly based on the analysis of photographs (computer vision). However, spectroscopic techniques can be a good alternative due to the valuable additional information that they provide.

A novel approach for discovering correlations between elemental and molecular composition using laser-based spectroscopic techniques.

Modern analytical techniques, including laser-induced breakdown spectroscopy (LIBS) and Raman spectroscopy, yield multidimensional data, which are most efficiently used in conjunction with chemometric techniques, including multi-block algorithms. In this study, we use several algorithms for the processing of laser-induced breakdown and Raman spectra of zooplankton organisms, which are found to accumulate lithium for an unknown reason. Correlations between elemental and molecular composition of zooplankton have been found.

Carbon determination in carbon-manganese steels under atmospheric conditions by Laser-Induced Breakdown Spectroscopy.

The most sensitive lines of carbon, used nowadays for its determination in steels by laser-induced-breakdown spectroscopy (LIBS), are at vacuum UV and, thereby, LIBS potential is significantly reduced. We suggested the use of the C I 833.51 nm line for carbon determination in low-alloy steels (c(C)~0.

Automatic identification of emission lines in laser-induced plasma by correlation of model and experimental spectra.

We have applied an algorithm to automatically identify emission lines in laser-induced breakdown spectrometry (LIBS). A Q-switched Nd:YAG laser at 355 nm was used to ablate a high-alloy stainless steel sample. The algorithm was implemented by three parts: simulation of the set of spectra corresponding to different temperature (T) and electron density (N(e)), searching the best correlated pair of a model spectrum and an experimental one, and attributing the peaks with certain lines.

Reduction of the matrix influence on analytical signal in laser-enhanced ionization spectrometry with laser sampling.

The novel approach using a slope of correlation line (laser-enhanced ionization of lithium versus laser-induced plasma emission of aluminum) as analytical signal was proposed for reduction of matrix interferences in laser-enhanced ionization spectrometric determination of Li with laser sampling.