Zapata Trujillo Juan C, McKemmish Laura K
School of Chemistry, University of New South Wales, 2052 Sydney, Australia.
J Phys Chem A. 2022 Jun 30;126(25):4100-4122. doi: 10.1021/acs.jpca.2c01438. Epub 2022 Jun 20.
High-throughput approaches for producing approximate vibrational spectral data for molecules of astrochemistry interest rely on harmonic frequency calculations using computational quantum chemistry. However, model chemistry recommendations (i.e., a level of theory and basis set pair) for these calculations are not yet available and, thus, thorough benchmarking against comprehensive benchmark databases is needed. Here, we present a new database for vibrational frequency calculations (VIBFREQ1295) storing 1295 experimental fundamental frequencies and CCSD(T)(F12*)/cc-pVDZ-F12 harmonic frequencies from 141 molecules. VIBFREQ1295's experimental data was complied through a comprehensive review of contemporary experimental data, while the data was computed here. The chemical space spanned by the molecules chosen is considered in-depth and is shown to have good representation of common organic functional groups and vibrational modes. Scaling factors are routinely used to approximate the effect of anharmonicity and convert computed harmonic frequencies to predicted fundamental frequencies. With our experimental and high-level data, we find that a single global uniform scaling factor of 0.9617(3) results in median differences of 15.9(5) cm. A far superior performance with a median difference of 7.5(5) cm can be obtained, however, by using separate scaling factors (SFs) for three regions: frequencies less than 1000 cm (SF = 0.987(1)), between 1000 and 2000 cm (SF = 0.9727(6)), and above 2000 cm (SF = 0.9564(4)). This sets a lower bound for the performance that could be reliably obtained using scaling of harmonic frequency calculations to predict experimental fundamental frequencies. VIBFREQ1295's most important purpose is to provide a robust database for benchmarking the performance of any vibrational frequency calculations. VIBFREQ1295 data could also be used to train machine-learning models for the prediction of vibrational spectra and as a reference and data starting point for more detailed spectroscopic modeling of particular molecules. The database can be found as part of the Supporting Information for this paper or in the Harvard DataVerse at https://doi.org/10.7910/DVN/VLVNU7.
用于生成具有天体化学研究价值的分子的近似振动光谱数据的高通量方法依赖于使用计算量子化学进行的谐波频率计算。然而，这些计算的模型化学建议（即理论水平和基组对）尚不可用，因此，需要针对综合基准数据库进行全面的基准测试。在这里，我们展示了一个用于振动频率计算的新数据库（VIBFREQ1295），它存储了141个分子的1295个实验基频以及CCSD(T)(F12*)/cc-pVDZ-F12谐波频率。VIBFREQ1295的实验数据是通过对当代实验数据的全面审查汇编而成的，而计算数据是在此处计算得出的。深入考虑了所选分子所涵盖的化学空间，结果表明其能很好地代表常见有机官能团和振动模式。缩放因子通常用于近似非谐性效应，并将计算出的谐波频率转换为预测的基频。利用我们的实验数据和高水平数据，我们发现单个全局统一缩放因子0.9617(3)会导致中位数差异为15.9(5) cm。然而，通过对三个区域使用单独的缩放因子（SFs）：频率小于1000 cm（SF = 0.987(1)）、在1000至2000 cm之间（SF = 0.9727(6)）以及高于2000 cm（SF = 0.9564(4)），可以获得中位数差异为7.5(5) cm的更优性能。这为使用谐波频率计算缩放来预测实验基频所能可靠获得的性能设定了下限。VIBFREQ1295的最重要目的是提供一个强大的数据库，用于对任何振动频率计算的性能进行基准测试。VIBFREQ1295数据还可用于训练用于预测振动光谱的机器学习模型，并作为对特定分子进行更详细光谱建模的参考和数据起点。该数据库可作为本文支持信息的一部分找到，或在哈佛数据文库中获取，网址为https://doi.org/10.7910/DVN/VLVNU7。
