Meta-analysis of uniform scaling factors for harmonic frequency calculations

IF 16.8 2区 化学 Q1 CHEMISTRY, MULTIDISCIPLINARY Wiley Interdisciplinary Reviews: Computational Molecular Science Pub Date : 2021-10-23 DOI:10.1002/wcms.1584
Juan C. Zapata Trujillo, Laura K. McKemmish
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引用次数: 7

Abstract

Vibrational frequency calculations performed under the harmonic approximation are widespread across chemistry. However, it is well-known that the calculated harmonic frequencies tend to systematically overestimate experimental fundamental frequencies; a limitation commonly overcome with multiplicative scaling factors. In practice, multiplicative scaling factors are derived for each individual model chemistry choice (i.e., a level of theory and basis set pair), where performance is judged by, for example, the root-mean square error (RMSE) between the predicted scaled and experimental frequencies. However, despite the overwhelming number of scaling factors reported in the literature and model chemistry approximations available, there is little guidance for users on appropriate model chemistry choices for harmonic frequency calculations. Here, we compile and analyze the data for 1495 scaling factors calculated using 141 levels of theory and 109 basis sets. Our meta-analysis of this data shows that scaling factors and RMSE approach convergence with only hybrid functionals and double-zeta basis sets, with anharmonicity error already dominating model chemistry errors. Noting inconsistent data and the lack of independent testing, we can nevertheless conclude that a minimum error of 25 cm−1—arising from insufficiently accurate treatment of anharmonicity—is persistent regardless of the model chemistry choice. Based on the data we compiled and cautioning the need for a future systematic benchmarking study, we recommend ωB97X-D/def2-TZVP for most applications and B2PLYP/def2-TZVPD for superior intensity predictions. With a smaller benchmark set, direct comparison prefers ωB97X-D/6-31G* to B3LYP/6-31G*.

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谐波频率计算均匀标度因子的元分析
在谐波近似下进行的振动频率计算在化学中广泛存在。然而,众所周知,计算出的谐波频率往往会系统性地高估实验基频;一个通常用乘法比例因子克服的限制。在实践中,为每个单独的模型化学选择(即,理论和基础集对的水平)导出乘法缩放因子,其中性能是通过预测缩放频率和实验频率之间的均方根误差(RMSE)来判断的。然而,尽管在文献和可用的模型化学近似中报告了大量的比例因子,但对于谐波频率计算的适当模型化学选择,用户几乎没有指导。在这里,我们编译和分析了1495个比例因子的数据,使用141个理论水平和109个基集计算。我们对这些数据的荟萃分析表明,比例因子和RMSE仅在混合泛函和双zeta基集下趋于收敛,而非调和误差已经主导了模型化学误差。注意到不一致的数据和缺乏独立测试,我们可以得出这样的结论:无论选择哪种模型化学,最小误差为25 cm−1——这是由于对不和谐性的处理不够精确造成的。根据我们汇编的数据,并提醒需要未来的系统基准研究,我们推荐ωB97X-D/def2-TZVP用于大多数应用,B2PLYP/def2-TZVPD用于优越的强度预测。对于较小的基准集,直接比较更倾向于ωB97X-D/6-31G*而不是B3LYP/6-31G*。本文分类如下:
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来源期刊
Wiley Interdisciplinary Reviews: Computational Molecular Science
Wiley Interdisciplinary Reviews: Computational Molecular Science CHEMISTRY, MULTIDISCIPLINARY-MATHEMATICAL & COMPUTATIONAL BIOLOGY
CiteScore
28.90
自引率
1.80%
发文量
52
审稿时长
6-12 weeks
期刊介绍: Computational molecular sciences harness the power of rigorous chemical and physical theories, employing computer-based modeling, specialized hardware, software development, algorithm design, and database management to explore and illuminate every facet of molecular sciences. These interdisciplinary approaches form a bridge between chemistry, biology, and materials sciences, establishing connections with adjacent application-driven fields in both chemistry and biology. WIREs Computational Molecular Science stands as a platform to comprehensively review and spotlight research from these dynamic and interconnected fields.
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