Developments in electronic structure theory have led to the widespread implementation and availability of approximate quantum chemical methods approaching accuracies within 1 kcal/mol of expensive ab initio calculations. These approaches are increasingly used to understand, validate and predict the outcomes of laboratory experiments. However, a direct comparison against experiment requires additional approximations to be made about the system under study such as the rigid-rotor harmonic oscillator (RRHO) description, whose accuracy can seriously undermine even the most elaborate computation. The effects of vibrational anharmonicity, multiple accessible conformations, molecular symmetry and the breakdown of the RRHO description collectively influence predictions of thermochemistry and kinetics.<br/><br/>We have developed an easy-to-use Python package that allows chemists to confidently process computational data obtained from DFT calculations. Corrections to thermodynamic values that otherwise would be unaccounted for are automated. These are universal considerations unrestricted to a particular software package. From the information provided by the Hessian matrix of second energy derivatives, thermodynamic values can be quickly obtained implementing a variety of scaling corrections to address limitations in the descriptions of low-frequency vibrations, at any temperature/pressure required. GoodVibes also has useful features such as creating output files of molecular Cartesian coordinates, graphing a reaction profile from relative energy values, or linking single point energy calculations to frequency calculations. This reliable and fast automated correction method is available on GitHub as an open source Python package and is readily installed and accessible to use by computational non-experts.

Applying commonly overlooked corrections to DFT frequency calculations with GoodVibes

2019 Fall National Meeting

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