Extensive TDDFT Benchmark Study of the Resonance Raman Spectra of Lumiflavin

IF 4.8 3区 化学 Q2 CHEMISTRY, MULTIDISCIPLINARY
Prokopis C. Andrikopoulos, Heba Halimeh
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Abstract

An extensive computational TDDFT resonance Raman study of lumiflavin is presented including 42 DFT functionals, benchmarked against the experimental Evolution Associated Spectra (EAS) of the equilibrated S1 and T1 states of FMN published earlier. Initially, off-resonance spectra were computed, yielding adequate agreement, and fine-tuning was achieved with the inclusion of specific frequency scaling factors. Since the experimental EAS were obtained under resonance for the singlet and near-resonance for the triplet state, the subsequent inclusion of resonance effects in the calculations improved the correlation for most functionals. Their evaluation according to specific criteria narrowed down the choice to HCTH, OLYP, and TPSSh. Among the included criteria were the percent error of the 0–0 transitions, the quantification of the increase/decrease in correlation due to the addition of resonance enhancements, and the reproduction of the singlet-triplet peak shifts. Owing to the extensive data set, valuable insights were gained to assist similar studies.

Abstract Image

荧光黄素共振拉曼光谱的广泛TDDFT基准研究
本文提出了一项广泛的计算TDDFT共振拉曼研究,包括42个DFT泛函,以FMN平衡S1和T1状态的实验进化相关光谱(EAS)为基准。最初,计算了非共振谱,产生了足够的一致性,并通过包含特定频率缩放因子实现了微调。由于实验EAS是在单重态的共振和三重态的近共振下获得的,因此随后在计算中包含共振效应改善了大多数泛函的相关性。他们根据特定标准进行评估,将选择范围缩小到HCTH、OLYP和TPSSh。包括的标准包括0-0跃迁的误差百分比,由于增加共振增强而导致的相关性增加/减少的量化,以及单线态-三重态峰移的再现。由于数据集广泛,获得了宝贵的见解,以协助类似的研究。
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来源期刊
CiteScore
6.60
自引率
3.30%
发文量
247
审稿时长
1.7 months
期刊介绍: This distinguished journal publishes articles concerned with all aspects of computational chemistry: analytical, biological, inorganic, organic, physical, and materials. The Journal of Computational Chemistry presents original research, contemporary developments in theory and methodology, and state-of-the-art applications. Computational areas that are featured in the journal include ab initio and semiempirical quantum mechanics, density functional theory, molecular mechanics, molecular dynamics, statistical mechanics, cheminformatics, biomolecular structure prediction, molecular design, and bioinformatics.
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