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• W4306410366 abstract "Many renewable energy technologies, such as hydrogen gas synthesis and carbon dioxide reduction, rely on chemical reactions involving hydride anions (H-). When selecting molecules to be used in such applications, an important quantity to consider is the thermodynamic hydricity, which is the free energy required for a species to donate a hydride anion. Theoretical calculations of thermodynamic hydricity depend on several parameters, mainly the density functional, basis set, and solvent model. In order to assess the effects of the above three parameters, we carry out hydricity calculations with different combinations of density functionals, basis sets, and solvent models for a set of organic molecules with known experimental hydricity values. The data are analyzed by comparing the R2 and root-mean-squared error (RMSE) of linear fits with a fixed slope of 1 and using the Akaike Information Criterion to determine statistical significance of the RMSE rank ordering. Based on these results, we quantified the accuracy of theoretical predictions of hydricity and found that the best compromise between accuracy and computational cost was obtained by using the B3LYP-D3 density functional for the geometry optimization and free-energy corrections, either ωB97X-D3 or M06-2X-D3 for single-point energy corrections, combined with a basis set no larger than def-TZVP and the C-PCM ISWIG solvation model. At this level of theory, the RMSEs of hydricity calculations for organic molecules in acetonitrile and dimethyl sulfoxide were found to be <4 and <10 kcal/mol, respectively, for an experimental data set with a dynamic range of 20-150 kcal/mol." @default.
• W4306410366 created "2022-10-17" @default.
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• W4306410366 date "2022-10-17" @default.
• W4306410366 modified "2023-09-29" @default.
• W4306410366 title "Benchmarking Density Functionals, Basis Sets, and Solvent Models in Predicting Thermodynamic Hydricities of Organic Hydrides" @default.
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• W4306410366 doi "https://doi.org/10.1021/acs.jpca.2c03072" @default.
• W4306410366 hasPubMedId "https://pubmed.ncbi.nlm.nih.gov/36251007" @default.
• W4306410366 hasPublicationYear "2022" @default.
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