Reliability of computed molecular structures.

Area of Science:

• Computational Chemistry
• Quantum Chemistry
• Molecular Modeling

Background:

• Accurate molecular structure prediction is vital for understanding chemical properties and reactions.
• Assessing the reliability of various computational methods is essential for guiding research choices.

Purpose of the Study:

• To evaluate the performance of 30 density-functional theory (DFT) methods and 7 basis sets for molecular structure optimization.
• To identify the most reliable and accurate computational approaches for predicting molecular geometries.

Main Methods:

• Optimization of 1342 molecules using 30 distinct computational methods.
• Systematic comparison of problematic and failed molecular structures across different methods and basis sets.
• Calculation of mean absolute deviations (MAD) for bond angles and lengths.

Main Results:

• 21.54% of molecules showed problematic structures, and 8.35% failed optimization.
• BHandH and LC-wPBE were identified as the most reliable methods for problematic molecules.
• Specific methods (e.g., DSDPBEP86, MP2) combined with large basis sets (e.g., aug-cc-pVQZ) yielded the most accurate bond lengths and angles.

Conclusions:

• Many DFT methods exhibit encouraging performance for molecular structure prediction.
• Larger basis sets, often exceeding cc-pVTZ, are generally required for high accuracy.
• The optimal combination of method and basis set may represent the current limit of computational chemistry for structural predictions.