Geometry determination of complexes in a molecular liquid mixture using electron–vibration–vibration two-dimensional infrared spectroscopy with a vibrational transition density cube method
Literature Information
Rui Guo, Shaul Mukamel, David R. Klug
We demonstrate the use of a new vibrational transition density cube (VTDC) method for determining the geometry of complexes in a molecular liquid mixture from electron–vibration–vibration two-dimensional infrared (EVV 2DIR) spectra. The VTDC method was used to calculate the electrically-mediated intermolecular vibrational coupling and thereby the EVV 2DIR spectra. Using the 1 : 1 benzonitrile–phenylacetylene (BN–PA) liquid mixture as a test case, the new method leads to a distance of 3.60 Å between the interacting BN–PA pair, a much more accurate value than the distance previously obtained using a dipolar approximation for the electrical coupling. We also show that molecular dynamics simulations of the liquid mixture predict a modal geometry of complexation which agrees well with the geometry determined from the 2DIR data via VTDC analysis. We therefore conclude the combination of VTDC and EVV 2DIR data is a useful approach for the determination of the geometry of molecular complexes in the condensed phase.
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Physical Chemistry Chemical Physics (PCCP) is an international journal co-owned by 19 physical chemistry and physics societies from around the world. This journal publishes original, cutting-edge research in physical chemistry, chemical physics and biophysical chemistry. To be suitable for publication in PCCP, articles must include significant innovation and/or insight into physical chemistry; this is the most important criterion that reviewers and Editors will judge against when evaluating submissions. The journal has a broad scope and welcomes contributions spanning experiment, theory, computation and data science. Topical coverage includes spectroscopy, dynamics, kinetics, statistical mechanics, thermodynamics, electrochemistry, catalysis, surface science, quantum mechanics, quantum computing and machine learning. Interdisciplinary research areas such as polymers and soft matter, materials, nanoscience, energy, surfaces/interfaces, and biophysical chemistry are welcomed if they demonstrate significant innovation and/or insight into physical chemistry. Joined experimental/theoretical studies are particularly appreciated when complementary and based on up-to-date approaches.




