Papers
Topics
Authors
Recent
Assistant
AI Research Assistant
Well-researched responses based on relevant abstracts and paper content.
Custom Instructions Pro
Preferences or requirements that you'd like Emergent Mind to consider when generating responses.
Gemini 2.5 Flash
Gemini 2.5 Flash 77 tok/s
Gemini 2.5 Pro 56 tok/s Pro
GPT-5 Medium 33 tok/s Pro
GPT-5 High 21 tok/s Pro
GPT-4o 107 tok/s Pro
Kimi K2 196 tok/s Pro
GPT OSS 120B 436 tok/s Pro
Claude Sonnet 4.5 34 tok/s Pro
2000 character limit reached

Uncertainty Quantification in First-Principles Predictions of Harmonic Vibrational Frequencies of Molecules and Molecular Complexes (1812.01145v1)

Published 4 Dec 2018 in physics.chem-ph and cond-mat.mtrl-sci

Abstract: Accurate prediction of molecular vibrational frequencies is important to identify spectroscopic signatures and reaction thermodynamics. In this work, we develop a method to quantify uncertainty associated with density functional theory predicted harmonic vibration frequencies utilizing the built-in error estimation capabilities of the BEEF-vdW exchange-correlation functional. The method is computationally efficiency by estimating the uncertainty at nearly the same computational cost as a single vibrational frequency calculation. We demonstrate the utility and robustness of the method by showing that the uncertainty estimates bounds the self-consistent calculations of six exchange correlation functionals for small molecules, rare gas dimers, and molecular complexes from the S22 dataset. Ten rare-gas dimers and the S22 dataset of molecular complexes provide a rigorous test as they are systems with complicated vibrational motion and non-covalent interactions. Using coefficient of variation as a uncertainty metric, we find that modes involving bending or torsional motion and those dominated by non-covalent interactions are found to have higher uncertainty in their predicted frequencies than covalent stretching modes. Given the simplicity of the method, we believe that this method can be easily adopted and should form a routine part of DFT-predicted harmonic frequency analysis.

Summary

We haven't generated a summary for this paper yet.

Lightbulb Streamline Icon: https://streamlinehq.com

Continue Learning

We haven't generated follow-up questions for this paper yet.

List To Do Tasks Checklist Streamline Icon: https://streamlinehq.com

Collections

Sign up for free to add this paper to one or more collections.