Performance of Minnesota Functionals on Vibrational Frequency

ABSTRACT Molecular geometry and harmonic frequency calculations are essential in thermochemical computations, with density functional theory (DFT) being widely employed for vibrational frequency predictions due to its efficiency and accuracy. In this study, we assessed the precision of 28 Minnesota based functionals with three different basis sets using the VIBFREQ1295 dataset. Scaling factors are necessary for predicting fundamental frequencies, global scaling factors were fitted by using F38/10 and VIBFREQ1295 datasets. The superior performing functionals were then fitted based on vibrational frequency ranges to obtain frequency‐range‐specific scaling factors. We observed consistent outlier across various model chemistries in vibrational frequency predictions, with alternative scaling factors showing minimal impact on reducing outlier occurrences. Besides, large basis sets are not indispensably required for fundamental frequency predictions. M06‐L, revM06‐L, SOGGA11‐X, PW6B95‐D3(BJ), CF22D, and M06‐2X consistently exhibit excellent performance across the three basis sets. When using frequency‐range‐specific scaling factors, the root mean squard errors (RMSEs) and median absolute errors (MedAEs) of almost all the selected functionals were reduced. PW6B95‐D3(BJ), CF22D, and MN12‐SX exhibited the lowest RMSEs. Comparisons were also done for different data classifications; the dataset was classified by the elements of the molecules, vibrational frequency intervals, and vibrational modes.

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Publication Details

Journal
International Journal of Quantum Chemistry
Published
2024-11-08
DOI
https://doi.org/10.1002/qua.27516
Citations
7
Primary Topic
Mathematical functions and polynomials
Type
article
Field-Weighted Citation Impact
6.83

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article

Performance of Minnesota Functionals on Vibrational Frequency

Gaihua Zhang, Ying Wang, Zhonghua Liu, Cheng Zhang et al.
7 citations
International Journal of Quantum Chemistry
Mathematical functions and polynomials
6.83
article

Performance of Minnesota Functionals on Vibrational Frequency

Gaihua Zhang, Ying Wang, Zhonghua Liu, Cheng Zhang, Yaqi Li, Yuanyuan Shu, Jiaxu Wang, Yini Zhou, Songping Liang
article en
7 citations

Abstract

ABSTRACT Molecular geometry and harmonic frequency calculations are essential in thermochemical computations, with density functional theory (DFT) being widely employed for vibrational frequency predictions due to its efficiency and accuracy. In this study, we assessed the precision of 28 Minnesota based functionals with three different basis sets using the VIBFREQ1295 dataset. Scaling factors are necessary for predicting fundamental frequencies, global scaling factors were fitted by using F38/10 and VIBFREQ1295 datasets. The superior performing functionals were then fitted based on vibrational frequency ranges to obtain frequency‐range‐specific scaling factors. We observed consistent outlier across various model chemistries in vibrational frequency predictions, with alternative scaling factors showing minimal impact on reducing outlier occurrences. Besides, large basis sets are not indispensably required for fundamental frequency predictions. M06‐L, revM06‐L, SOGGA11‐X, PW6B95‐D3(BJ), CF22D, and M06‐2X consistently exhibit excellent performance across the three basis sets. When using frequency‐range‐specific scaling factors, the root mean squard errors (RMSEs) and median absolute errors (MedAEs) of almost all the selected functionals were reduced. PW6B95‐D3(BJ), CF22D, and MN12‐SX exhibited the lowest RMSEs. Comparisons were also done for different data classifications; the dataset was classified by the elements of the molecules, vibrational frequency intervals, and vibrational modes.

International Journal of Quantum ChemistryVol. 124(22)
Hunan Normal University (CN), Changsha Normal University (CN)
Education Department of Hunan Province, National Natural Science Foundation of China, Science and Technology Program of Hunan Province
Openalex Percentile: Top 2%
Mathematical functions and polynomials
6.83
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