Abstract

Prediction of catalytic reaction efficiency is one of the most intriguing and challenging applications of machine learning (ML) algorithms in chemistry. In this study, we demonstrated a strategy for utilizing ML protocols applied to Quantum Theory of Atoms In Molecules (QTAIM) parameters to predict the ability of the A17 L47K catalytic antibody to covalently capture organophosphate pesticides. We found that the novel “composite” DFT functional B97-3c could be effectively employed for fast and accurate initial geometry optimization, aligning well with the input dataset creation. QTAIM descriptors proved to be well-established in describing the examined dataset using density-based and hierarchical clustering algorithms. The obtained clusters exhibited correlations with the chemical classes of the input compounds. The precise physical interpretation of the QTAIM properties simplifies the explanation of feature impact for both supervised and unsupervised ML protocols. It also enables acceleration in the search for entries with desired properties within large databases. Furthermore, our findings indicated that Ridge Regression with Laplacian kernel and CatBoost Regressor algorithms demonstrated suitable performance in handling small datasets with non-trivial dependencies. They were able to predict the actual reaction barrier values with a high level of accuracy. Additionally, the CatBoost Classifier proved reliable in discriminating between “active” and “inactive” compounds.

Abstract

The angular overlap model (AOM) is an established parameterization scheme within ligand field theory (LFT). In principle, its application is fairly straightforward, but can be tedious and involve a trial-and-error approach to identify and judge the best set of parameters. With the availability of quantum chemical methods to predict d-d transitions in transition metal complexes, a rich source of computational spectroscopic data with unambiguous assignments to electronic states is available. Herein, we present AOMadillo, a software package that is designed to interface the output of ab initio LFT calculations from the ORCA suite of programs and performs a least-squares fit for a chosen AOM parameterization. Many steps of the AOM parameterization are automated, so that scans of geometric parameters and evaluations of sets of similar complexes are convenient. The fitting routine is highly configurable, allowing the efficient evaluation of different parameter sets.

Abstract

The DFT-level computational investigations into Gibbs free energies (ΔG) demonstrate that as the dielectric constant of the solvent increases, the stabilities of [M(NH₃) _n ]^2+/3+ (n = 4, 6; M = selected 3d transition metals) complexes decrease. However, there is no observed correlation between the stability of the complex and the solvent donor number. Analysis of the charge transfer and Wiberg bond indices indicates a dative-bond character in all the complexes. The solvent effect assessed through solvation energy is determined by the change in the solvent accessible surface area (SASA) and the change in the charge distribution that occurs during complex formation. It has been observed that the SASA and charge transfer are different in the different coordination numbers, resulting in a variation in the solvent effect on complex stability in different solvents. This ultimately leads to a change between the relative stability of complexes with different coordination numbers while increasing the solvent polarity for a few complexes. Moreover, the findings indicate a direct relationship between ΔΔG (∆G _solvent-∆G _gas) and ΔE _solv, which enables the computation of ΔG for the compounds in a particular solvent using only ΔG _gas and ΔE _solv. This approach is less computationally expensive.

Molecular docking is a prevalent tool in drug discovery. DOCK 6's extensible design enables implementing and testing new methods in molecular docking. Development in DOCK 3 enabled screening of large databases of billions of small molecules. To allow access to this unprecedented chemical space, we have implemented features from DOCK 3.7 into DOCK 6, including traversal of precomputed ligand conformations stored in a hierarchical database. We test these new features retrospectively.

Abstract

To allow DOCK 6 access to unprecedented chemical space for screening billions of small molecules, we have implemented features from DOCK 3.7 into DOCK 6, including a search routine that traverses precomputed ligand conformations stored in a hierarchical database. We tested them on the DUDE-Z and SB2012 test sets. The hierarchical database search routine is 16 times faster than anchor-and-grow. However, the ability of hierarchical database search to reproduce the experimental pose is 16% worse than that of anchor-and-grow. The enrichment performance is on average similar, but DOCK 3.7 has better enrichment than DOCK 6, and DOCK 6 is on average 1.7 times slower. However, with post-docking torsion minimization, DOCK 6 surpasses DOCK 3.7. A large-scale virtual screen is performed with DOCK 6 on 23 million fragment molecules. We use current features in DOCK 6 to complement hierarchical database calculations, including torsion minimization, which is not available in DOCK 3.7.

The thermodynamic stability of various alkoxy/aryloxy/peroxy radicals, as well as TEMPO and triplet dioxygen has been explored at a variety of theoretical levels. The effects of hydrogen bonding interactions on the stability of oxygen-centered radicals have been probed by addition of a single solvating water molecule.

Abstract

The stability of various alkoxy/aryloxy/peroxy radicals, as well as TEMPO and triplet dioxygen (³O₂) has been explored at a variety of theoretical levels. Good correlations between RSE_theor and RSE_exp are found for hybrid DFT methods, for compound schemes such as G3B3-D3, and also for DLPNO-CCSD(T) calculations. The effects of hydrogen bonding interactions on the stability of oxygen-centered radicals have been probed by addition of a single solvating water molecule. While this water molecule always acts as a H-bond donor to the oxygen-centered radical itself, it can act as a H-bond donor or acceptor to the respective closed-shell parent.

Methane catalytic oxidation has been extensively studied for its huge potential for energy and industrial synthesis. Oxygen atoms adsorbed on transition metal surfaces often change the catalytic activity to activate methane. The dynamic processes of methane oxidation are vital for the understanding of the effects of pre-adsorbed oxygen atoms on transition metal surfaces. This article reports the CH₄ dissociation pathways on Au, Cu, Ni, Pt, and Pd surfaces using reactive force field molecular dynamic simulations.

Abstract

The chemisorbed oxygen usually promotes the CH bond activation over less active metals like IB group metals but has no effect or even an inhibition effect over more active metals like Pd based on the static electronic structure study. However, the understanding in terms of dynamics knowledge is far from complete. In the present work, methane dissociation on the oxygen-preadsorbed transition metals including Au, Cu, Ni, Pt, and Pd is systemically studied by reactive force field (ReaxFF). The ReaxFF simulation results indicate that CH₄ molecules mainly undergo the direct dissociation on Ni, Pt, and Pd surfaces, while undergo the oxygen-assisted dissociation on Au and Cu surfaces. Additionally, the ab initio molecular dynamics (AIMD) simulations with the umbrella sampling are employed to study the free-energy changes of CH₄ dissociation, and the results further support the CH₄ dissociation pathway during the ReaxFF simulations. The present results based on ReaxFF and AIMD will provide a deeper dynamic understanding of the effects of pre-adsorbed oxygen species on the CH bond activation compared to that of static DFT.

This work centers around the evaluation of various computational DFT-based methods in their ability to correctly predict equilibrium lattice constants while at the same time producing reliable interaction energies for h-BN as a prime example of both a covalent as well as weakly bound system. The state-of-the-art fixed-node diffusion quantum Monte Carlo method provided a reference estimate of the bulk h-BN exfoliation energy.

Abstract

Materials that exhibit both strong covalent and weak van der Waals interactions pose a considerable challenge to many computational methods, such as DFT. This makes assessing the accuracy of calculated properties, such as exfoliation energies in layered materials like hexagonal boron nitride (h-BN) problematic, when experimental data are not available. In this paper, we investigate the accuracy of equilibrium lattice constants and exfoliation energy calculation for various DFT-based computational approaches in bulk h-BN. We contrast these results with available experiments and reference fixed-node diffusion quantum Monte Carlo (QMC) results. From our reference QMC calculation, we obtained an exfoliation energy of −33±$$ -33\pm $$2 meV/atom (-0.38±$$ \pm $$0.02 J/m2$$ {}^2 $$).

When an electron is added to the Li-molecule pair, it may go to the lithium-ion and neutralize it. Instead, we suggest placing this additional electron on the molecule using constrained density functional theory (CDFT).

Abstract

Li-molecule pair is a widely used model for the simulation of reduction in Li-ion batteries. We demonstrate that this model provides incorrect results for some solvents. When an electron is added to the Li-molecule pair, it may go to the lithium-ion and neutralize it. Instead, we suggest placing this additional electron on the molecule using constrained density functional theory (CDFT). This approach resembles electron behaviour in the condensed phase and reproduces the physics of the reduction. We demonstrate that suggested in this work approach provides improved agreement with experimental data. Suggested CDFT-based method is fast, reliable and may be used in computational screening of solvents. We demonstrate the practical application of the method by benchmarking it on a set of 30 molecules from the electrolyte solvent database.

Core ionization energies (IE) are accurately estimated using ΔSCF and Slater's transition state (STS). The small remaining errors come mainly from self-interaction error and can be corrected with the “shifted STS (1)” and “shifted STS (2)” methods, thus providing a convenient means for predicting core IE.

Abstract

The core ionization energies of second- and third-period elements of the molecules C₂H₅NO₂, SiF₄, Si(CH₃)₄, PF₃, POF₃, PSF₃, CS₂, OCS, SO₂, SO₂F₂, CH₃Cl, CFCl₃, SF₅Cl, and Cl₃PS are calculated by using Hartree-Fock (HF), and Kohn-Sham (KS) with BH&HLYP, B3LYP, and LC-BOP functionals. We used ΔSCF, Slater's transition state (STS), and two previously proposed shifted STS (1) and shifted STS (2) methods, which have been developed. The errors of ΔSCF and STS come mainly from the self-interaction errors (SIE) and can be corrected with a shifting scheme. In this study, we used the shifting parameters determined for each atom. The shifted STS (1) reproduces ΔSCF almost perfectly with mean absolute deviations (MAD) of 0.02 eV. While ΔSCF and STS vary significantly depending on the functional used, the variation of shifted STS (2) is small, and all shifted STS (2) values are close to the observed ones. The deviations of the shifted STS (2) from the experiment are 0.24 eV (BH&HLYP), 0.19 eV (B3LYP), and 0.23 eV (LC-BOP). These results further support the use of shifted STS methods for predicting the core ionization energies.

The electronic layout and Real Time-TD-DFT electron dynamics are investigated to unveil the charge migration time evolution in two asymmetrically substituted indenotetracene compounds for potential singlet fission-based applications in photoactive materials.

Abstract

Photo-induced charge transfer (CT) states are pivotal in many technological and biological processes. A deeper knowledge of such states is mandatory for modeling the charge migration dynamics. Real-time time-dependent density functional theory (RT-TD-DFT) electronic dynamics simulations are employed to explicitly observe the electronic density time-evolution upon photo-excitation. Asymmetrically substituted indenotetracene molecules, given their potential application as n-type semiconductors in organic photovoltaic materials, are here investigated. Effects of substituents with different electron-donating characters are analyzed in terms of the overall electronic energy spacing and resulting ultrafast CT dynamics through linear response (LR-)TD-DFT and RT-TD-DFT based approaches. The combination of the computational techniques here employed provided direct access to the electronic density reorganization in time and to its spatial and rational representation in terms of molecular orbital occupation time evolution. Such results can be exploited to design peculiar directional charge dynamics, crucial when photoactive materials are used for light-harvesting applications.