Tackling an accurate description of molecular reactivity with double-hybrid density functionals

Improving the Reliability of, and Confidence in, DFT Functional Benchmarking through Active Learning

Validating the performance of exchange-correlation functionals is vital to ensure the reliability of density functional theory (DFT) calculations. Typically, these validations involve benchmarking data sets. Currently, such data sets are usually assembled in an unprincipled manner, suffering from uncontrolled chemical bias, and limiting the transferability of benchmarking results to a broader chemical space. In this work, a data-efficient solution based on active learning is explored to address this issue. Focusing─as a proof of principle─on pericyclic reactions, we start from the BH9 benchmarking data set and design a chemical reaction space around this initial data set by combinatorially combining reaction templates and substituents. Next, a surrogate model is trained to predict the standard deviation of the activation energies computed across a selection of 20 distinct DFT functionals. With this model, the designed chemical reaction space is explored, enabling the identification of challenging regions, i.e., regions with large DFT functional divergence, for which representative reactions are subsequently acquired as additional training points. Remarkably, it turns out that the function mapping the molecular structure to functional divergence is readily learnable; convergence is reached upon the acquisition of fewer than 100 reactions. With our final updated model, a more challenging─and arguably more representative─pericyclic benchmarking data set is curated, and we demonstrate that the functional performance has changed significantly compared to the original BH9 subset.

Study of Sterically Crowded Alkanes: Assessment of Non-Empirical Density Functionals Including Double-Hybrid (Cost-Effective) Methods

We theoretically study here the homolytic dissociation reactions of sterically crowded alkanes of increasing size, carrying three different (bulky) substituents such as tert-butyl, adamantyl, and [1.1.1]propellanyl, employing a family of parameter-free functionals ranging from semi-local, to hybrid and double-hybrid models. The study is complemented with the interaction between a pair of HC(CH3)3 molecules at repulsive and attractive regions, as an example of a system composed by a pair of weakly bound sterically crowded alkanes. We also assessed the effect of incorporating reliable dispersion corrections (i. e., D4 or NL) for all the functionals assessed, as well as the use of a tailored basis set (DH-SVPD) for non-covalent interactions, which provides the best trade-off between accuracy and computational cost for a seemingly extended applications to branched or crowded systems. Overall, the PBE-QIDH/DH-SVPD and r2SCAN-QIDH/DH-SVPD methods represent an excellent compromise providing relatively low, and thus very competitive, errors at a fraction of the cost of other quantum-chemical methods in use.

Computed versus experimental energy barriers in solution: Influence of the type of the density functional approximation

Mechanistic investigations at the density functional theory level of organic and organometallic reactions in solution are now broadly accessible and routinely implemented to complement experimental investigations. The selection of an appropriate functional among the plethora of developed ones is the first challenge on the way to reliable energy barrier calculations. To provide guidelines for the choice of an initial and reliable computational level, the performances of commonly used non-empirical (PBE, PBE0, PBE0-DH) and empirical density functionals (BLYP, B3LYP, B2PLYP) were evaluated relative to experimental activation enthalpies. Most reactivity databases to assess density functional performances are primarily based on high level calculations, here a set of experimental activation enthalpies of organic and organometallic reactions performed in solution were selected from the literature. As a general trend, the non-empirical functionals outperform the empirical ones. The most accurate energy barriers are obtained with hybrid PBE0 and double-hybrid PBE0-DH density functionals, both providing similar performance. Regardless of the functional under consideration, the addition of the GD3-BJ empirical dispersion correction does not enhance the accuracy of computed energy barriers.

Benefits of Range-Separated Hybrid and Double-Hybrid Functionals for a Large and Diverse Data Set of Reaction Energies and Barrier Heights

To better understand the thermochemical kinetics and mechanism of a specific chemical reaction, an accurate estimation of barrier heights (forward and reverse) and reaction energies is vital. Because of the large size of reactants and transition state structures involved in real-life mechanistic studies (e.g., enzymatically catalyzed reactions), density functional theory remains the workhorse for such calculations. In this paper, we have assessed the performance of 91 density functionals for modeling the reaction energies and barrier heights on a large and chemically diverse data set (BH9) composed of 449 organic chemistry reactions. We have shown that range-separated hybrid functionals perform better than the global hybrids for BH9 barrier heights and reaction energies. Except for the PBE-based range-separated nonempirical double hybrids, range separation of the exchange term helps improve the performance for barrier heights and reaction energies. The 16-parameter Berkeley double hybrid, ωB97M(2), performs remarkably well for both properties. However, our minimally empirical range-separated double hybrid functionals offer marginally better accuracy than ωB97M(2) for BH9 barrier heights and reaction energies.

Electronic structure analysis of electrochemical CO2 reduction by iron-porphyrins reveals basic requirements to design catalysts bearing non-innocent ligands

Electrocatalytic CO2 reduction is a possible solution to the increasing CO2 concentration in the earth atmosphere, because it enables storage of energy while using the harmful CO2 feedstock as starting...