Abstract
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.
Original language | English |
---|---|
Pages (from-to) | 7152-7218 |
Number of pages | 67 |
Journal | Chemical Reviews |
Volume | 120 |
Issue number | 15 |
DOIs | |
State | Published - Aug 12 2020 |
Funding
This work was supported by IBS-R023-D1 (MC). BB wishes to thank the European Union’s Horizon 2020 under the Marie Skłodowska-Curie Grant Agreement No. 665778, as well as the National Science Centre, Poland (grant no. 2016/23/P/ST4/01720). CRB acknowledges generous support from the National Science Foundation (CHE-1847199, BIO-1815354), the National Institutes of Health (R35GM133359), and the Welch Foundation (F-1891). MWDH-H and JDH thank the University of Nottingham, Green Chemicals Beacon for funding toward this research. MCT acknowledges support from Department of Energy (DE-SC0018983), National Science Foundation (1552996), and National Institutes of Health (GM114500). AGD would like to thank Prof. Andrei Tokmakoff for discussing amide modes when he was a Ph.D. student. LW acknowledges the support from the National Institutes of Health through Award R01GM130697. SAC acknowledges support from National Science Foundation (CHE-1565471).
Funders | Funder number |
---|---|
Green Chemicals Beacon | |
National Science Foundation | BIO-1815354, CHE-1847199 |
National Institutes of Health | |
U.S. Department of Energy | 1552996, CHE-1565471, R01GM130697, GM114500, DE-SC0018983 |
National Institute of General Medical Sciences | R35GM133359 |
Welch Foundation | F-1891 |
H2020 Marie Skłodowska-Curie Actions | 665778 |
University of Nottingham | |
Narodowe Centrum Nauki | 2016/23/P/ST4/01720 |
Horizon 2020 |