Optimizing Computational Parameters for Nuclear Electronic Orbital Density Functional Theory: A Benchmark Study on Proton Affinities

IF 4.8 3区 化学 Q2 CHEMISTRY, MULTIDISCIPLINARY Journal of Computational Chemistry Pub Date : 2025-03-18 DOI:10.1002/jcc.70082
Raza Ullah Khan, Ralf Tonner-Zech
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Abstract

This study benchmarks the nuclear electronic orbital density functional theory (NEO-DFT) method for a set of molecules that is larger than in previous studies. The focus is on proton affinity predictions to assess the influences of computational parameters. NEO-DFT incorporates nuclear quantum effects for protons involved in protonation processes. Using a test set of 72 molecules with experimental proton affinities as reference, we evaluated various exchange-correlation functionals, finding that B3LYP-based functionals deliver the most accurate results. Among the tested functionals, CAM-B3LYP performs the best with an MAD value of 6.2 kJ/mol with respect to experimental data. In NEO-DFT, electron-proton correlation (epc) functionals were assessed, with LDA-type epc17-2 yielding comparable results to the GGA-type epc19 functional. Compared to traditional DFT (MAD value of 31.6 kJ/mol), which treats nuclei classically, NEO-DFT provides enhanced accuracy for proton affinities when electron-proton correlation is included. Regarding basis sets, the def2-QZVP electronic basis set achieved the highest accuracy with an MAD value of 5.0 kJ/mol, though at a higher computational cost compared to def2-TZVP and def2-SVP, while nuclear basis sets showed minimal impact on proton affinity accuracy and no consistent trend. Overall, this study demonstrates NEO-DFT's efficacy in addressing nuclear quantum effects for proton affinity predictions, providing guidance on optimal parameter selection for future NEO-DFT applications.

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核电子轨道密度泛函理论的优化计算参数:质子亲和的基准研究
本研究将核电子轨道密度泛函理论(NEO-DFT)方法应用于一组比以往研究更大的分子。重点是质子亲和预测,以评估计算参数的影响。NEO-DFT包含质子化过程中质子的核量子效应。以72个具有实验质子亲和的分子作为参考,我们评估了各种交换相关功能,发现基于b3lyp的功能提供了最准确的结果。其中CAM-B3LYP表现最好,MAD值为6.2 kJ/mol。在NEO-DFT中,评估了电子-质子相关(epc)功能,lda型epc17-2的结果与gga型epc19功能相当。与传统的DFT (MAD值为31.6 kJ/mol)相比,当考虑电子-质子相关时,NEO-DFT提供了更高的质子亲和精度。在基集方面,def2-QZVP电子基集的精度最高,MAD值为5.0 kJ/mol,但计算成本高于def2-TZVP和def2-SVP,而核基集对质子亲和精度的影响最小,且没有一致的趋势。总的来说,这项研究证明了NEO-DFT在质子亲和预测中解决核量子效应的有效性,为未来NEO-DFT应用的最佳参数选择提供了指导。
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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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