Quantifying and Understanding Errors in Molecular Geometries.

Area of Science:

• Computational chemistry
• Quantum chemistry
• Theoretical chemistry

Background:

• Electronic structure calculations are essential in chemistry but contain inherent errors in energies and geometries.
• Accurately quantifying geometric errors across multiple parameters (bond angles, lengths) is complex.
• Existing methods lack a unified approach to assess geometric deviations.

Purpose of the Study:

• Introduce a single, natural measure for geometric errors in computational chemistry.
• Develop a tool to rank different computational methods based on geometric accuracy.
• Provide quantitative insights into specific geometric parameter errors and method trends.

Main Methods:

• Introduction of the geometry energy offset (GEO) as a novel metric.
• Application of GEO to assess errors in various electronic structure calculation methods.
• Analysis of GEO's correlation with specific geometric parameters (bond angles, lengths).

Main Results:

• GEO provides a unified measure linking disparate geometric errors.
• A new ranking of computational methods based on geometric accuracy is established.
• GEO offers quantitative insights into errors in bond angles and lengths for different methods.
• Demonstrated GEO's utility in reducing the cost of high-level geometry optimizations.
• Identified instances where geometric errors significantly distort overall method accuracy.

Conclusions:

• The geometry energy offset (GEO) offers a powerful and versatile tool for evaluating geometric accuracy in computational chemistry.
• GEO facilitates more reliable method selection and understanding of error propagation.
• This metric aids in optimizing computational resources and improving the predictive power of theoretical chemistry.