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Least-Squares Mass-Dependence Molecular Structures.

Watson1, Roytburg, Ulrich

  • 1Steacie Institute for Molecular Sciences, National Research Council of Canada, Ottawa, Ontario, K1A 0R6, Canada

Journal of Molecular Spectroscopy
|November 30, 1999
PubMed
Summary

Determining molecular structures from zero-point moments of inertia is possible using mathematical models. A two-parameter model provides accurate, near-equilibrium structures, even with limited isotopomer data.

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Area of Science:

  • Molecular Spectroscopy
  • Quantum Chemistry
  • Computational Chemistry

Background:

  • The difference between zero-point and equilibrium moments of inertia is crucial for understanding molecular structure.
  • Atomic masses significantly influence this difference, behaving as a homogeneous function of degree 12.
  • Accurate molecular structures are essential for various chemical and physical studies.

Purpose of the Study:

  • To investigate the use of explicit mathematical models for determining near-equilibrium molecular structures.
  • To assess the feasibility of using zero-point moments of inertia from isotopomers for structural determination.
  • To identify the most effective model parameters for precise structural analysis.

Main Methods:

  • Development and application of explicit mathematical models based on molecular moments of inertia.

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  • Analysis of data from a range of molecular isotopomers.
  • Evaluation of model performance based on parameter count and fit quality (standard deviation).

    • Main Results:

    • Models with over two parameters per axis lead to correlated fits with typical isotopomer numbers.
    • A two-parameter model offers well-conditioned fits with high precision (parts-per-million standard deviation).
    • The determined structures are often close to the true equilibrium molecular structures.

    Conclusions:

    • Explicit mathematical models are effective for deriving near-equilibrium molecular structures from zero-point moments of inertia.
    • A two-parameter model is recommended for its robustness and accuracy, especially when dealing with limited isotopomer data.
    • The methodology allows for the inclusion of advanced corrections, such as Laurie-type corrections for hydrogen atoms.