Robust normal modes in vibrational circular dichroismspectra

Literature Information

Publication Date 2009-05-27
DOI 10.1039/B823558A
Impact Factor 3.676
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Abstract

The use of calculations of the rotational strengths of normal modes in order to determine the absolute configuration (AC) of a molecule, by comparing a calculated vibrational circular dichroism (VCD) spectrum to an experimental one, can be made much more reliable when the vibrational modes are classified as either robust or non-robust. The robust modes are the ones with a robust sign of the rotational strength in the sense that it will not change by small perturbations in either experiment or calculation. The signs of non-robust modes may change. Clearly only robust modes should be used to establish the AC. We recommend that programs which calculate VCD spectra should provide, per normal mode, information that indicates the robustness of a mode, and therefore its usefulness for the AC determination. Such information consists of the angle ΞΎ between the electric and magnetic dipole transition moments, and the magnitudes of these dipole transition moments.

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Physical Chemistry Chemical Physics

Physical Chemistry Chemical Physics
CiteScore: 5.5
Self-citation Rate: 10.3%
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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.

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