Basis Set Combinations Research Articles

Benchmarking Quantum Mechanical Levels of Theory for Valence Parametrization in Force Fields.

A wide range of density functional methods and basis sets are available to derive the electronic structure and properties of molecules. Quantum mechanical calculations are too computationally intensive for routine simulation of molecules in the condensed phase, prompting the development of computationally efficient force fields based on quantum mechanical data. Parametrizing general force fields, which cover a vast chemical space, necessitates the generation of sizable quantum mechanical data sets with optimized geometries and torsion scans. To achieve this efficiently, choosing a quantum mechanical method that balances computational cost and accuracy is crucial. In this study, we seek to assess the accuracy of quantum mechanical theory for specific properties such as conformer energies and torsion energetics. To comprehensively evaluate various methods, we focus on a representative set of 59 diverse small molecules, comparing approximately 25 combinations of functional and basis sets against the reference level coupled cluster calculations at the complete basis set limit.

Efficient Exploitation of Numerical Quadrature with Distance-Dependent Integral Screening in Explicitly Correlated F12 Theory: Linear Scaling Evaluation of the Most Expensive RI-MP2-F12 Term.

We present a linear scaling atomic orbital based algorithm for the computation of the most expensive exchange-type RI-MP2-F12 term by employing numerical quadrature in combination with CABS-RI to avoid six-center-three-electron integrals. Furthermore, a robust distance-dependent integral screening scheme, based on integral partition bounds [Thompson, T. H.; Ochsenfeld, C. J. Chem. Phys. 2019, 150, 044101], is used to drastically reduce the number of the required three-center-one-electron integrals substantially. The accuracy of our numerical quadrature/CABS-RI approach and the corresponding integral screening is thoroughly assessed for interaction and isomerization energies across a variety of numerical integration grids. Our method outperforms the standard density fitting/CABS-RI approach with errors below 1 μEh even for small grid sizes and moderate screening thresholds. The choice of the grid size and screening threshold allows us to tailor our ansatz to a desired accuracy and computational efficiency. We showcase the approach's effectiveness for the chemically relevant system valinomycin, employing a triple-ζ F12 basis set combination (C54H90N6O18, 5757 AO basis functions, 10,266 CABS basis functions, 735,783 grid points). In this context, our ansatz achieves higher accuracy combined with a 135× speedup compared to the classical density fitting based variant, requiring notably less computation time than the corresponding RI-MP2 calculation. Additionally, we demonstrate near-linear scaling through calculations on linear alkanes. We achieved an 817-fold acceleration for C80H162 and an extrapolated 28,765-fold acceleration for C200H402, resulting in a substantially reduced computational time for the latter─from 229 days to just 11.5 min. Our ansatz may also be adapted to the remaining MP2-F12 terms, which will be the subject of future work.

An Update in Computational Methods for Environmental Monitoring: Theoretical Evaluation of the Molecular and Electronic Structures of Natural Pigment-Metal Complexes.

Metals are beneficial to life, but the presence of these elements in excessive amounts can harm both organisms and the environment; therefore, detecting the presence of metals is essential. Currently, metal detection methods employ powerful instrumental techniques that require a lot of time and money. Hence, the development of efficient and effective metal indicators is essential. Several synthetic metal detectors have been made, but due to their risk of harm, the use of natural pigments is considered a potential alternative. Experiments are needed for their development, but they are expensive and time-consuming. This review explores various computational methods and approaches that can be used to investigate metal-pigment interactions because choosing the right methods and approaches will affect the reliability of the results. The results show that quantum mechanical methods (ab initio, density functional theory, and semiempirical approaches) and molecular dynamics simulations have been used. Among the available methods, the density functional theory approach with the B3LYP functional and the LANL2DZ ECP and basis set is the most promising combination due to its good accuracy and cost-effectiveness. Various experimental studies were also in good agreement with the results of computational methods. However, deeper analysis still needs to be carried out to find the best combination of functions and basis sets.

Distributed Implementation of Full Configuration Interaction for One Trillion Determinants.

Full configuration interaction (FCI) can provide an exact molecular ground-state energy within a given basis set and serve as a benchmark for approximate methods in quantum chemical calculations, including the emerging variational quantum eigensolver. However, its exponential computational and memory requirements easily exceed the capability of a single server and limit its applicability to large molecules. In this paper, we present a distributed FCI implementation employing a hybrid parallelization scheme with multithreading and multiprocessing to expand FCI's applicability. We optimize this scheme to minimize the bottlenecks arising from interprocess communications and interthread data management. Our implementation achieves higher scalability than the naive combination of prior works and successfully calculates the exact energy of C3H8/STO-3G with 1.31 trillion determinants, which is the largest FCI calculation to the best of our knowledge. Furthermore, we provide a comprehensive list of FCI results with 136 combinations of molecules and basis sets for future evaluation and development of approximate methods.

Theoretical insights on the relationship between detection limit and complex stability of oxine ligand

The concept of detection limit was combined with quantum chemical calculations for trace analysis of cadmium and lead in aqueous solution using deprotonated 8-hydroxyquinoline (oxine) as ligand. The DFT study was performed using 6-31G(d), cc-pVTZ and SDD basis sets in combination with different theoretical methods such as; B3LYP, MP2 and M06L implemented in Gaussian 09 program package. The obtained results of the study in the gas and aqueous phases show that the chemical stability of the complex was found in the order Pb-oxine > Cd-oxine. Based on the calculations done, the stability order was relative to the detection limit (LOD) for the two metals Cd and Pb. Thus, a reverse relationship between LOD and binding energy has been found.

New-generation electron-propagator methods for vertical electron detachment energies of molecular anions: benchmarks and applications to model green-fluorescent-protein chromophores.

Ab initio electron-propagator calculations continue to be useful companions to experimental investigations of electronic structure in molecular anions. A new generation of electron-propagator methods recently has surpassed its antecedents' predictive accuracy and computational efficiency. Interpretive clarity has been conserved, for no adjustable parameters have been introduced in the preparation of molecular orbitals or in the formulation of approximate self-energies. These methods have employed the diagonal self-energy approximation wherein each Dyson orbital equals a canonical Hartree-Fock orbital times the square root of a probability factor. Numerical tests indicate that explicitly renormalized, diagonal self-energies are needed when Dyson orbitals have large valence nitrogen, oxygen or fluorine components. They also demonstrate that even greater accuracy can be realized with generalizations that do not employ the diagonal self-energy approximation in the canonical Hartree-Fock basis. Whereas the diagonal methods have fifth-power arithmetic scaling factors, the non-diagonal generalizations introduce only non-iterative sixth-power contractions. Composite models conserve the accuracy of the most demanding combinations of self-energy approximations and flexible basis sets with drastically reduced computational effort. Composite-model results on anions that resemble the chromophore of the green fluorescent protein illustrate the interpretive capabilities of explicitly renormalized self-energies. Accurate predictions on the lowest vertical electron detachment energy of each anion confirm experimental data and the utility of the diagonal self-energy approximation.

Use of Gaussian-Type Functions for Describing Fast Ion-Matter Irradiation with Time-Dependent Density Functional Theory.

The electronic stopping power is an observable property that quantifies the ability of swift ions to penetrate matter to transfer energy to the electron cloud. The recent literature has proven the value of Real-Time Time-Dependent Density Functional Theory to accurately evaluate this property from first-principles, but questions remain regarding the capability of computer codes relying on atom-centered basis functions to capture the physics at play. In this Perspective, we draw attention to the fact that irradiation by swift ions triggers electron emission into the continuum, especially at the Bragg peak. We investigate the ability of Gaussian atomic orbitals (AOC), which were fitted to mimic continuum wave functions, to improve electronic stopping power predictions. AOC are added to standard correlation-consistent basis sets or STO minimal basis sets. Our benchmarks for water irradiation by fast protons clearly advocate for the use of AOC, especially near the Bragg peak. We show that AOC only need to be placed on the molecules struck by the ion. The number of AOC that are added to the usual basis set is relatively small compared to the total number of atomic orbitals, making the use of such a basis set an excellent choice from a computational cost point of view. The optimum basis set combination is applied for the calculation of the stopping power of a proton in water with encouraging agreement with experimental data.

A theoretical investigation on hirshfeld surface, IR., UV–Vis, 1H and 13C NMR spectra, nonlinear optical properties, and in silico molecular docking of an organometallic compound: Dibromobis(l-proline)zinc(II)

This study presents quantum chemical computations and in silico molecular docking for a Zn(II) complex from the proline derivative family, with the chemical formula C10H18Br2N2O4Zn, while the synthesis involved a mixture of ZnBr2 and l-proline, which was heated at 40–45 °C for 5 h. The mixture was filtered, dried, and recrystallised to increase purity using methanol. The calculations utilised density functional theory (DFT) with the B3LYP functional and a combined basis set of 6–311++G(d,p) and LanL2DZ. The molecular structure was optimised, and based on this optimised structure, IR, UV–Vis, and NMR spectra were calculated. The frontier molecular orbitals (FMOs) analysis was conducted to obtain various chemical activity parameters associated with the energy gap.Additionally, properties such as dipole moment and first and second hyperpolarizability were investigated and analysed using the B3LYP level of theory within the DFT framework. Furthermore, the title compound was subjected to molecular docking with SARS-CoV-2 protein receptors to explore ligand–protein interactions. The docking results revealed a binding energy of −6.2 kcal/mol, suggesting that the title compound has potential as a candidate against the main protease of SARS-CoV-2.

Enhancing the Search Performance of Bayesian Optimization by Creating Different Descriptor Datasets Using Density Functional Theory.

Descriptors calculated from molecular structure information can be used as explanatory variables in Bayesian optimization (BO). Even though structural and descriptor information can be obtained from various databases for general compounds, information on highly confidential compounds such as pharmaceutical intermediates and active pharmaceutical ingredients cannot be retrieved from these databases. In particular, determining the stable structure and electronic state of a compound via quantum chemical calculations from descriptor information requires considerable computational time. Although descriptor information can be obtained using density functional theory (DFT), which has a relatively light computational load, only conventional combinations of basis sets and functionals can be selected before experiments instead of the best ones. Few studies have discussed these effects on the search performance of BO, and good search performance is highly dependent on the application. Therefore, we developed a method to improve the search performance of BO by using descriptors computed from several combinations of basis sets and functionals. The dataset obtained from averaging multiple descriptor sets exhibited better BO search performance than that of a single descriptor dataset. In addition, the more descriptor sets used for averaging, the better the search performance. This method has a relatively small computational load and can be easily used by those who are unfamiliar with quantum chemical calculations.

Computation of CCSD(T)-Quality NMR Chemical Shifts via Δ-Machine Learning from DFT.

NMR spectroscopy undoubtedly plays a central role in determining molecular structures across different chemical disciplines, and the accurate computational prediction of NMR parameters is highly desirable. In this work, a new Δ-machine learning approach is presented to correct DFT-computed NMR chemical shifts using input features from the calculation and in addition highly accurate reference data at the CCSD(T)/pcSseg-2 level of theory with a basis set extrapolation scheme. The model is trained on a data set containing 1000 optimized and geometrically distorted structures of small organic molecules comprising most elements of the first three periods and containing data for 7090 1H and 4230 13C NMR chemical shifts. Applied to the PBE0/pcSseg-2 method, the mean absolute deviation (MAD) on the internal NMR shift test set is reduced by 81% for 1H and 92% for 13C at virtually no additional computational cost. For 12 different DFT functional and basis set combinations, the MAD of the ML-corrected NMR shifts ranges from 0.021 to 0.039 ppm (1H) and from 0.38 to 1.07 ppm (13C). Importantly, the new method consistently outperforms the simple and widely used linear regression correction technique. This behavior is reproduced on three different external benchmark sets, confirming the generality and robustness of the correction scheme, which can easily be applied in DFT-based spectral simulations.

Modeling of transition metals coordination polymers of benzene tricarboxylate and pyridyl oxime-based ligands for application as antibacterial agents

Theoretical simulation involving density functional theory (DFT) computation and molecular docking has been utilized to investigate in detailed the reactivity, stability, bond interactions, and the antibacterial potential of coordination polymers constructed with pyridyl oxime and benzene tricarboxylate linkers is based on the earlier experimental studies reported by Ioannis et al., Molecules, 26 (2), 491, 2021. Five (5) complexes: [Zn(BTC)2(PyOx)2] [Cu(BTC)2(PyOx)2], [Ni(BTC)2(PyOx)2], [Co(BTC)2(PyOx)2], [Fe(BTC)2(PyOx)2] were investigated and the DFT calculations was accomplished using a combined basis sets of 6-311++G (2d,2p) and LanL2DZ for the ligands and central metal ions respectively at the B3LYP functional. Structurally, all five complexes showed tetrahedral geometry after optimization due to the bulkiness of the linkers with excellent linearity in bond lengths. Based on quantum chemical simulations, [Ni(BTC)2(PyOx)2] was observed to be the most reactive complex with lower energy gap of 1.45 eV whereas Co(BTC)2(PyOx)2] was said to be the most stable complex with high energy gap of 7.19eV which is in tandem with results from the natural bond orbital analysis (NBO). The potency of all complexes in combating multidrug resistance pathogens were studied by molecular docking analysis, [Ni(BTC)2(PyOx)2] have the most favorable docking score of -9.2 kcal/mol and excellent hydrogen bond interaction. This result is also in good agreement with the quantum descriptors. Thus, [Ni(BTC)2(PyOx)2] exhibits potentials to combat multidrug resistance pathogens.

The Microwave Rotational Electric Resonance (RER) Spectrum of Benzothiazole.

The microwave spectra of benzothiazole were measured in the frequency range 2-26.5 GHz using a pulsed molecular jet Fourier transform microwave spectrometer. Hyperfine splittings arising from the quadrupole coupling of the 14N nucleus were fully resolved and analyzed simultaneously with the rotational frequencies. In total, 194 and 92 hyperfine components of the main species and the 34S isotopologue, respectively, were measured and fitted to measurement accuracy using a semi-rigid rotor model supplemented by a Hamiltonian accounting for the 14N nuclear quadrupole coupling effect. Highly accurate rotational constants, centrifugal distortion constants, and 14N nuclear quadrupole coupling constants were deduced. A large number of method and basis set combinations were used to optimize the molecular geometry of benzothiazole, and the calculated rotational constants were compared with the experimentally determined constants in the course of a benchmarking effort. The similar value of the χcc quadrupole coupling constant when compared to other thiazole derivatives indicates only very small changes of the electronic environment at the nitrogen nucleus in these compounds. The small negative inertial defect of -0.056 uÅ2 hints that low-frequency out-of-plane vibrations are present in benzothiazole, similar to the observation for some other planar aromatic molecules.

A comparative study of DFT functionals and basis sets for describing the luminescent spectra of hexacoordinated silicon complexes

This article presents a comparative study of DFT functionals - B3LYP, BHandHLYP and CAM-B3LYP in combination with basis sets – 6-311++g(d,p), cc-pVDZ and cc-pVTZ to describe the luminescence spectra of optimized structures of neutral hexacoordinated silicon complexes. The calculation accuracy of an obtained theoretical data of an electronic absorption spectra of the structures was compared with the known experimental data. To perform comparative calculations with the experimental values, a neutral optimized structure of hexacoordinated Si(bzimpy)2 complex containing 2,6-bis(benzimidazol-2'-yl)pyridine ligand was considered. A comparison of the absorption spectra of the Si(bzimpy)2 structure showed that the use of the 6-311++g(d,p) basis set in combination with the B3LYP functional gives the best agreement with the experimental data. Based on the obtained results of the study, a comparison was made of the absorption spectra of other silicon compounds - Si(bzimpyMeO)2, Si(bzimpyMe2)2 and Si(bzimpyMeOMe2)2. Comparative graphs of the structures showed the proximity of the location of intense peaks for all four structures. Thus, we can say that the B3LYP functional gives the best agreement with the experimental data for neutral hexacoordinated silicon complexes. Also this shows that in a more detailed study of the absorption spectra, it can be noted that the use of the 6-311++g(d,p) basis set in combination with the B3LYP functional gives the most accurate values.

Investigation on Molecular Structure and Electronic Properties of Zinc (II) Complex with 2-acetylpyridinenicotinichydrazone Ligand

In the present study, the structural parameter, the electronic and nonlinear optical properties of three Zn (II) halido complexes of the type [Zn (Hal)2HL] (Hal = Cl, 1; Br, 2; I, 3; HL = 2-acetylpyridine nicotinic hydrazone) have been theoretically investigated in detail. Two of the studied complexes [ZnCl2(HL), [ZnBr2(HL)] have been synthesized before, and some molecular properties have been determined, however, the new complex [ZnI2(HL)] is theoretically modeled for the first time. The polarizability (α), dipole moment (µ) and the first-order hyperpolarizability (β) of the compounds have been investigated using the Density Functional Theory (DFT) based on the B3LYP density functional with basis set combinations. In calculations, LANL2DZ and a mixed basis set of LANL2DZ (for Zn and I) and 6-311G (for other atoms) are used in the gas-phase geometry optimization. In addition, the highest occupied molecular orbital energy (HOMO) and the lowest unoccupied molecular orbital (LUMO) of the compounds in the ground state were calculated by using the same method and the energy band gap (Eg = ELUMO-EHOMO) was obtained from frontier molecular orbitals. The equilibrium state (ground state) dipole moment value of the studied complex was calculated as 12.61 and 12.74 Debye by B3LYP/GENECP/LANL2DZ-6-311G and B3LYP/LANL2DZ method, respectively. The energy gap values of complexes 1-3 are calculated as 1.73/1.38/1.15 eV at the B3LYP/LANL2DZ and are calculated as 3.61/2.28/2.18 eV at the B3LYP/MIX respectively. The energy gap values of complexes 1-3 decrease in the order complex 1>complex 2>complex 3. The approximate geometry of the molecules in three dimensions was drawn in the Gauss View 5.0 molecular imaging program, and all theoretical calculations were used with the Gaussian 09W package program.

Computational Characterization of Zr-Oxide MOFs for Adsorption Applications.

Zr-oxide secondary building units construct metal-organic framework (MOF) materials with excellent gas adsorption properties and high mechanical, thermal, and chemical stability. These attributes have led Zr-oxide MOFs to be well-recognized for a wide range of applications, including gas storage and separation, catalysis, as well as healthcare domain. Here, we report structure search methods within the Cambridge Structural Database (CSD) to create a curated subset of 102 Zr-oxide MOFs synthesized to date, bringing a unique record for all researchers working in this area. For the identified structures, we manually corrected the proton topology of hydroxyl and water molecules on the Zr-oxide nodes and characterized their textural properties, Brunauer-Emmett-Teller (BET) area, and topology. Importantly, we performed systematic periodic density functional theory (DFT) calculations comparing 25 different combinations of basis sets and functionals to calculate framework partial atomic charges for use in gas adsorption simulations. Through experimental verification of CO2 adsorption in selected Zr-oxide MOFs, we demonstrate the sensitivity of CO2 adsorption predictions at the Henry's regime to the choice of the DFT method for partial charge calculations. We characterized Zr-MOFs for their CO2 adsorption performance via high-throughput grand canonical Monte Carlo (GCMC) simulations and revealed how the chemistry of the Zr-oxide node could have a significant impact on CO2 uptake predictions. We found that the maximum CO2 uptake is obtained for structures with the heat of adsorption values >25 kJ/mol and the largest cavity diameters of ca. 6-7 Å. Finally, we introduced augmented reality (AR) visualizations as a means to bring adsorption phenomena alive in porous adsorbents and to dynamically explore gas adsorption sites in MOFs.

Interexcited State Photophysics I: Benchmarking Density Functionals for Computing Nonadiabatic Couplings and Internal Conversion Rate Constants.

We present the first benchmarking study of nonadiabatic matrix coupling elements (NACMEs) calculated using different density functionals. Using the S1 → S0 transition in perylene solvated in toluene as a case study, we calculate the photophysical properties and corresponding rate constants for a variety of density functionals from each rung of Jacob's ladder. The singlet photoluminescence quantum yield (sPLQY) is taken as a measure of accuracy, measured experimentally here as 0.955. Important quantum chemical parameters such as geometries, absorption, emission, and adiabatic energies, NACMEs, Hessians, and transition dipole moments were calculated for each density functional basis set combination (data set) using density functional theory based multireference configuration interaction (DFT/MRCI) and compared to experiment where possible. We were able to derive simple relations between the TDDFT and DFT/MRCI photophysical properties; with semiempirical damping factors of ∼0.843 ± 0.017 and ∼0.954 ± 0.064 for TDDFT transition dipole moments and energies to DFT/MRCI level approximations, respectively. NACMEs were dominated by out-of-plane derivative components belonging to the center-most ring atoms with weaker contributions from perturbations along the transverse and longitudinal axes. Calculated theoretical spectra compared well to both experiment and literature, with fluorescence lifetimes between 7.1 and 12.5 ns, agreeing within a factor of 2 with experiment. Internal conversion (IC) rates were then calculated and were found to vary wildly between 106-1016 s-1 compared with an experimental rate of the order 107 s-1. Following further testing by mixing data sets, we found a strong dependence on the method used to obtain the Hessian. The 5 characterized data sets ranked in order of most promising are PBE0/def2-TZVP, ωB97XD/def2-TZVP, HCTH407/TZVP, PBE/TZVP, and PBE/def2-TZVP.

Revisiting fundamental properties of TiO2 nanoclusters as condensation seeds in astrophysical environments

Context. The formation of inorganic cloud particles takes place in several atmospheric environments, including those of warm, hot, rocky, and gaseous exoplanets, brown dwarfs, and asymptotic giant branch stars. The cloud particle formation needs to be triggered by the in situ formation of condensation seeds since it cannot be reasonably assumed that such condensation seeds preexist in these chemically complex gas-phase environments. Aims. We aim to develop a method for calculating the thermochemical properties of clusters as key inputs for modelling the formation of condensation nuclei in gases of changing chemical composition. TiO2 is used as benchmark species for cluster sizes N = 1–15. Methods. We created a total of 90000 candidate (TiO2)N geometries for cluster sizes N = 3−15. We employed a hierarchical optimisation approach, consisting of a force-field description, density-functional based tight-binding, and all-electron density-functional theory (DFT) to obtain accurate zero-point energies and thermochemical properties for the clusters. Results. In 129 combinations of functionals and basis sets, we find that B3LYP/cc-pVTZ, including Grimme’s empirical dispersion, performs most accurately with respect to experimentally derived thermochemical properties of the TiO2 molecule. We present a hitherto unreported global minimum candidate for size N = 13. The DFT-derived thermochemical cluster data are used to evaluate the nucleation rates for a given temperature-pressure profile of a model hot-Jupiter atmosphere. We find that with the updated and refined cluster data, nucleation becomes unfeasible at slightly lower temperatures, raising the lower boundary for seed formation in the atmosphere. Conclusions. The approach presented in this paper allows finding stable isomers for small (TiO2)N clusters. The choice of the functional and basis set for the all-electron DFT calculations has a measurable impact on the resulting surface tension and nucleation rate, and the updated thermochemical data are recommended for future considerations.

Reactivity of 9-anilinoacridine Derivatives as Potent Anticancer Agents: A DFT Approach

Background: Anticancer activity of 9-anilinoacridine derivatives has been well reported. Although, the DNA-drug sequence-specific binding of these compounds may be affected by the substituent(s) on the aniline ring, it is still unclear which substituent (NH2 or CH2–OH) on the anilino ring of the compound is the critical element. A good understanding of chemical properties such as steric, lipophilic and electronic properties at the molecular level may provide important background for mutagenic and carcinogenic properties. Objectives: The present study is an attempt to understand the reactive nature of some selected 9-anilinoacridine derivatives in both gas and solvent phases and to predict their anticancer activity by QSAR analysis. Methods: Full geometry optimizations of all derivatives were carried out at gradient corrected DFT using DMol3 program. We used DNP basis set in combination with BLYP to study all the derivatives. The molecular mechanics parameters used for QSAR analysis were calculated using Hyperchem software. Results: We found Compound (31) (R=COOC6H5) as the most stable compound and compound (6) (R1= NO2) as the most reactive one in both gas and solvent phases. Fukui function (f+) values of all the atoms showed that N10 is the most reactive atom in each of the molecule which indicates that N10 is the preferred site for nucleophilic attack. The final QSAR model with four parameters (electrophilicity, hardness, surface area, and molar refractivity) is capable of predicting anticancer activity of the compounds against leukemic HL-60 cell lines with r2 = 0.91 and 0.88 in both gas and solvent phases, respectively. Conclusion: The global and local reactivity descriptors, such as hardness, chemical potential, electrophilicity index, Fukui function, and local philicity were calculated to understand the reactive nature and reactive sites of the compounds. The comparative QSAR study with the help of DFT and MM + techniques provides the importance of the selected descriptors in predicting the activity of the selected derivatives.

Benchmarking Density Functionals, Basis Sets, and Solvent Models in Predicting Thermodynamic Hydricities of Organic Hydrides.

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.

Benchmark Density Functional Theory Approach for the Calculation of Bond Dissociation Energies of the M-O2 Bond: A Key Step in Water Splitting Reactions.

A very fascinating aspect in quantum chemical research is to determine the accurate and cost-effective methods for the calculation of electronic and structural properties through a benchmark study. The current study focuses on the performance evaluation of density functional theory methods for the accurate measurement of bond dissociation energies (BDEs) of chemically important M–O2 bonds in water splitting reactions. The BDE measurement has got noteworthy attention due to its importance in all areas of chemistry. For BDE measurements of M–O2 bonds in five metal complexes with oxygen molecules, 14 density functionals (DFs) are chosen from seven classes of DFs with two series of mixed basis sets. A combination of pseudopotential and Pople basis sets [LANL2DZ & 6-31G(d) and SDD & 6-31+G(d)] are used as a series of mixed basis sets. The B3LYP-GD3BJ functional with LANL2DZ & 6-31G(d) gives outstanding results due to low deviations, error, and the best Pearson’s correlation (R) between the experimental and theoretical data. Our study suggested an efficient, low-cost, precise, and accurate B3LYP-GD3BJ/LANL2DZ & 6-31G(d) level of theory for BDE of the M–O2 bond, which may be useful for chemists working in the field of energy generation and utilization.