:Vibrational spectroscopy is a valuable quantitative tool for the determination of structure at surfaces. Various techniques may be applicable and useful, depending on what is available, the transparency of the substrates, the need for in situ probes, and the degree of interfacial specificity required. We examine and compare signals in infrared absorption, Raman scattering, and vibrational sum-frequency generation spectroscopy to the underlying molecular response. In all of these experiments, varying the beam polarizations enables the orientation of specific chemical functional groups to be determined. However, the sensitivity of each technique is directly connected to the manner in which the molecular response manifests itself in the measured signal. Starting with simple distributions of a single vibrational mode, leading up to multiple vibrational bands in more complex orientation distributions, we compare these three techniques in terms of their sensitivity to features of the molecular orientation distribution. This review is aimed at guiding planned experiments when multiple techniques are available for surface structural analysis.
We present a framework for using linear programming to solve a challenging problem in surface science, the elucidation of the structure and composition of adsorbed molecules from a mixture, using simulated data from polarized Raman experiments. In the past, methods applied in order to interpret such spectroscopic information were combinatorial approaches that are limited in scalability or accuracy. Quantum mechanical electronic structure calculations yield the optical response of a single molecule, from which spectra of a mixture can be determined by appropriate weighting. Furthermore, spectral obtained in different beam polarizations provide projections of the signal in the laboratory frame. We demonstrate that linear programming is an ideal tool for utilizing all of this information in order to provide the sought structural picture.
DOI : 10.1016/j.chemolab.2019.103898 Anahtar Kelimeler :
Linear programming, Molecular structure, Vibrational spectroscopy
ISSN: 0169-7439 Cilt: 196 Sayfa: 103898
We provide a complete and consistent framework in which vibrational spectra may be modeled from molecular properties and molecular properties may be gleaned from vibrational spectra. This includes practical advice on how to define and use the rotation operators when moving between laboratory and molecular coordinate systems. At the same time, we provide some tips for the facile comparison of analytical orientation distributions and the construction of spectra from molecular dynamics simulations. We illustrate these approaches for infrared absorption, Raman scattering, and vibrational sum-frequency generation spectroscopy.
2D correlation analysis provides a powerful means of extracting structural and dynamical data from spectroscopic experiments. This has been successfully developed for techniques such as IR absorption spectroscopy, where the correlation has additionally been shown to increase the spectral resolution by observing the differing behavior of overlapping absorption bands in response to an external perturbation. Visible-infrared sum-frequency generation (SFG) spectroscopy combines many of the benefits of IR absorption and Raman scattering spectroscopy, and adds a unique structural perspective due to its surface specificity. Bringing the flexibility of 2D correlation analysis to SFG experiments would therefore further enhance the power and utility of this nonlinear vibrational spectroscopy. However, straightforward application of the correlation algorithms to homodyne SFG intensity data is not ideal as the SFG line shape often masks underlying spectral features, resulting in misleading correlation maps. We show that application of correlation analysis to heterodyne SFG experiments restores the qualitative utility of such analyses. An example is provided for the case of leucine adsorption onto surfaces of varying hydrophobicity.