Performance of Minnesota Functionals on Vibrational Frequency

IF 2.3 3区 化学 Q3 CHEMISTRY, PHYSICAL International Journal of Quantum Chemistry Pub Date : 2024-11-08 DOI:10.1002/qua.27516
Jiaxu Wang, Cheng Zhang, Yaqi Li, Yini Zhou, Yuanyuan Shu, Songping Liang, Gaihua Zhang, Zhonghua Liu, Ying Wang
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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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明尼苏达函数在振动频率上的表现
分子几何和谐波频率计算在热化学计算中至关重要,而密度泛函理论(DFT)因其高效性和准确性被广泛用于振动频率预测。在本研究中,我们使用 VIBFREQ1295 数据集评估了 28 种基于明尼苏达函数的三种不同基集的精度。缩放因子是预测基频的必要条件,我们使用 F38/10 和 VIBFREQ1295 数据集拟合了全局缩放因子。然后根据振动频率范围对性能优越的函数进行拟合,以获得特定频率范围的缩放因子。我们观察到各种化学模型在振动频率预测方面都存在离群现象,而其他缩放因子对减少离群现象的影响微乎其微。此外,基频预测并非一定需要大型基集。M06-L、revM06-L、SOGGA11-X、PW6B95-D3(BJ)、CF22D 和 M06-2X 在三个基集中始终表现出优异的性能。在使用特定频率范围的缩放因子时,几乎所有选定函数的均方根误差(RMSE)和中值绝对误差(MedAE)都有所降低。其中 PW6B95-D3(BJ)、CF22D 和 MN12-SX 的均方根误差最小。还对不同的数据分类进行了比较;数据集按分子元素、振动频率间隔和振动模式进行了分类。
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来源期刊
International Journal of Quantum Chemistry
International Journal of Quantum Chemistry 化学-数学跨学科应用
CiteScore
4.70
自引率
4.50%
发文量
185
审稿时长
2 months
期刊介绍: Since its first formulation quantum chemistry has provided the conceptual and terminological framework necessary to understand atoms, molecules and the condensed matter. Over the past decades synergistic advances in the methodological developments, software and hardware have transformed quantum chemistry in a truly interdisciplinary science that has expanded beyond its traditional core of molecular sciences to fields as diverse as chemistry and catalysis, biophysics, nanotechnology and material science.
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