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Vibrational Spectroscopy in Studies of Atmospheric Corrosion.

ABSTRACT: Vibrational spectroscopy has been successfully used for decades in studies of the atmospheric corrosion processes, mainly to identify the nature of corrosion products but also to quantify their amounts. In this review article, a summary of the main achievements is presented with focus on how the techniques infrared spectroscopy, Raman spectroscopy, and vibrational sum frequency spectroscopy can be used in the field. Several different studies have been discussed where these instruments have been used to assess both the nature of corrosion products as well as the properties of corrosion inhibitors. Some of these techniques offer the valuable possibility to perform in-situ measurements in real time on ongoing corrosion processes, which allows the kinetics of formation of corrosion products to be studied, and also minimizes the risk of changing the surface properties which may occur during ex-situ experiments. Since corrosion processes often occur heterogeneously over a surface, it is of great importance to obtain a deeper knowledge about atmospheric corrosion phenomena on the nano scale, and this review also discusses novel vibrational microscopy techniques allowing spectra to be acquired with a spatial resolution of 20 nm.

SUBMITTER: Hosseinpour S

PROVIDER: S-EPMC5507006 | biostudies-other | 2017 Apr

REPOSITORIES: biostudies-other

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Project description:Vibrational spectroscopy is an essential tool in chemical analyses, biological assays, and studies of functional materials. Over the past decade, various coherent nonlinear vibrational spectroscopic techniques have been developed and enabled researchers to study time-correlations of the fluctuating frequencies that are directly related to solute-solvent dynamics, dynamical changes in molecular conformations and local electrostatic environments, chemical and biochemical reactions, protein structural dynamics and functions, characteristic processes of functional materials, and so on. In order to gain incisive and quantitative information on the local electrostatic environment, molecular conformation, protein structure and interprotein contacts, ligand binding kinetics, and electric and optical properties of functional materials, a variety of vibrational probes have been developed and site-specifically incorporated into molecular, biological, and material systems for time-resolved vibrational spectroscopic investigation. However, still, an all-encompassing theory that describes the vibrational solvatochromism, electrochromism, and dynamic fluctuation of vibrational frequencies has not been completely established mainly due to the intrinsic complexity of intermolecular interactions in condensed phases. In particular, the amount of data obtained from the linear and nonlinear vibrational spectroscopic experiments has been rapidly increasing, but the lack of a quantitative method to interpret these measurements has been one major obstacle in broadening the applications of these methods. Among various theoretical models, one of the most successful approaches is a semiempirical model generally referred to as the vibrational spectroscopic map that is based on a rigorous theory of intermolecular interactions. Recently, genetic algorithm, neural network, and machine learning approaches have been applied to the development of vibrational solvatochromism theory. In this review, we provide comprehensive descriptions of the theoretical foundation and various examples showing its extraordinary successes in the interpretations of experimental observations. In addition, a brief introduction to a newly created repository Web site (http://frequencymap.org) for vibrational spectroscopic maps is presented. We anticipate that a combination of the vibrational frequency map approach and state-of-the-art multidimensional vibrational spectroscopy will be one of the most fruitful ways to study the structure and dynamics of chemical, biological, and functional molecular systems in the future.

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Vibrational Spectroscopy in Studies of Atmospheric Corrosion.

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