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密度泛函理论在预测大气预成核团簇的结构和反应自由能方面的评估

Assessment of Density Functional Theory in Predicting Structures and Free Energies of Reaction of Atmospheric Prenucleation Clusters.

作者信息

Elm Jonas, Bilde Merete, Mikkelsen Kurt V

机构信息

Department of Chemistry, H. C. Ørsted Institute, University of Copenhagen, Universitetsparken 5, DK-2100 Copenhagen, Denmark.

出版信息

J Chem Theory Comput. 2012 Jun 12;8(6):2071-7. doi: 10.1021/ct300192p. Epub 2012 May 2.

Abstract

This work assesses different computational strategies for predicting structures and Gibb's free energies of reaction of atmospheric prenucleation clusters. The performance of 22 Density Functional Theory functionals in predicting equilibrium structures of molecules and water prenucleation clusters of atmospheric relevance is evaluated against experimental data using a test set of eight molecules and prenucleation clusters: SO2, H2SO4, CO2·H2O, CS2·H2O, OCS·H2O, SO2·H2O, SO3·H2O, and H2SO4·H2O. Furthermore, the functionals are tested and compared for their ability to predict the free energy of reaction for the formation of five benchmark atmospheric prenucleation clusters: H2SO4·H2O, H2SO4·(H2O)2, H2SO4·NH3, HSO4(-)·H2O, and HSO4(-)·(H2O)2. The performance is evaluated against experimental data, coupled cluster, and complete basis set extrapolation procedure methods. Our investigation shows that the utilization of the M06-2X functional with the 6-311++G(3df,3pd) basis set represents an improved approach compared to the conventionally used PW91 functional, yielding mean absolute errors of 0.48 kcal/mol and maximum errors of 0.67 kcal/mol compared to experimental results.

摘要

这项工作评估了用于预测大气预成核团簇的结构和反应吉布斯自由能的不同计算策略。使用包含八个分子和预成核团簇的测试集:SO₂、H₂SO₄、CO₂·H₂O、CS₂·H₂O、OCS·H₂O、SO₂·H₂O、SO₃·H₂O 和 H₂SO₄·H₂O,针对实验数据评估了22种密度泛函理论泛函在预测与大气相关的分子和水预成核团簇平衡结构方面的性能。此外,还测试并比较了这些泛函预测五个基准大气预成核团簇形成反应自由能的能力:H₂SO₄·H₂O、H₂SO₄·(H₂O)₂、H₂SO₄·NH₃、HSO₄⁻·H₂O 和 HSO₄⁻·(H₂O)₂。根据实验数据、耦合簇方法和完全基组外推程序方法对性能进行了评估。我们的研究表明,与传统使用的PW91泛函相比,使用6 - 311++G(3df,3pd)基组的M06 - 2X泛函是一种改进的方法,与实验结果相比,平均绝对误差为0.48千卡/摩尔,最大误差为0.67千卡/摩尔。

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