We present a computational methodology based on atom-centered potentials (ACPs) for the efficient and accurate structural modeling of large molecular systems. ACPs are atom-centered one-electron potentials that have the same functional form as effective-core potentials. In recent works, we showed that ACPs can be used to produce a correction to the ground-state wave function and electronic energy to alleviate shortcomings in the underlying model chemistry. In this work, we present ACPs for H, C, N, and O atoms that are specifically designed to predict accurate non-covalent binding energies and inter- and intramolecular geometries when combined with dispersion-corrected Hartree-Fock (HF-D3) and a minimal basis-set (scaled MINI or MINIs). For example, the combined HF-D3/MINIs-ACP method demonstrates excellent performance, with mean absolute errors of 0.36 and 0.28 kcal/mol for the S22x5 and S66x8 benchmark sets, respectively, relative to highly correlated complete-basis-set data. The application of ACPs results in a significant decrease in error compared to uncorrected HF-D3/MINIs for all benchmark sets examined. In addition, HF-D3/MINIs-ACP, has a cost only slightly higher than a minimal-basis-set HF calculation and can be used with any electronic structure program for molecular quantum chemistry that uses Gaussian basis sets and effective-core potentials.

The calculation of accurate reaction energies and barrier heights is essential in computational studies of reaction mechanisms and thermochemistry. To assess methods regarding their ability to predict these two properties, high-quality benchmark sets are required that comprise a reasonably large and diverse set of organic reactions. Due to the time-consuming nature of both locating transition states and computing accurate reference energies for reactions involving large molecules, previous benchmark sets have been limited in scope, the number of reactions considered, and the size of the reactant and product molecules. Recent advances in coupled-cluster theory, in particular local correlation methods like DLPNO-CCSD(T), now allow the calculation of reaction energies and barrier heights for relatively large systems. In this work, we present a comprehensive and diverse benchmark set of barrier heights and reaction energies based on DLPNO-CCSD(T)/CBS called BH9. BH9 comprises 449 chemical reactions belonging to nine types common in organic chemistry and biochemistry. We examine the accuracy of DLPNO-CCSD(T) vis-a-vis canonical CCSD(T) for a subset of BH9 and conclude that, although there is a penalty in using the DLPNO approximation, the reference data are accurate enough to serve as a benchmark for density functional theory (DFT) methods. We then present two applications of the BH9 set. First, we examine the performance of several density functional approximations commonly used in thermochemical and mechanistic studies. Second, we assess our basis set incompleteness potentials regarding their ability to mitigate basis set incompleteness errors. The number of data points, the diversity of the reactions considered, and the relatively large size of the reactant molecules make BH9 the most comprehensive thermochemical benchmark set to date and a useful tool for the development and assessment of computational methods.

Triphenylamine (TPA), a propeller-shaped optoelectronic molecule, has been used to generate stimuli-responsive smart fluorescent organic materials and correlate the effect of subtle structural changes on the molecular packing and mechanochromic fluorescence (MCF). The substituent (OCH3) position in the TPA phenyl ring and acceptors (malononitrile, cyanoacetamide, cyanoacetic acid, ethyl cyanoacetate, and diethylmalonate) strongly influenced the solid state and mechanochromic fluorescence as well as the molecular packing. The structure–property studies revealed that (i) TPA derivatives without the OCH3 substituent exhibit strong fluorescence (Φf = 85% (TCAAD-1, 55% (TDEM)), (ii) higher dihedral angle (τ) between donor (aminophenyl) and acceptor lead to weak/non fluorescent material, (iii) substituent at the ortho position to acceptor increased the dihedral angle (τ = 26.49 (TCAAD-2), τ = 27.14 (TDMM)), and (iv) the increase of alkyl groups produced self-reversible high contrast off-on fluorescence switching materials (TDEM). Powder X-ray diffraction studies indicate that stimuli induced reversible phase transformation from crystalline to amorphous and vice versa was responsible for fluorescence switching. The computational studies also supported that OCH3 substitution at ortho to acceptor increased the dihedral angle and optical band gap. Thus, the present studies provide a structural insight for designing TPA based organic molecules for developing new smart organic materials.

A kinetic study of the hydrogen atom transfer (HAT) reactions from a series of organic compounds to the quinolinimide-N-oxyl radical (QINO) was performed in CH 3 CN. The HAT rate constants are significantly higher than those observed with the phthalimide-N-oxyl radical (PINO) as a result of enthalpic and polar effects due to the presence of the Nheteroaromatic ring in QINO. The relevance of polar effects is supported by theoretical calculations conducted for the reactions of the two N-oxyl radicals with toluene, which indicate that the HAT process is characterized by a significant degree of charge transfer permitted by the π-stacking that occurs between the toluene and the N-oxyl aromatic rings in the transition state structures. An increase in the HAT reactivity of QINO was observed in the presence of 0.15 M HClO 4 and 0.15 M Mg(ClO 4 ) 2 due to the protonation or complexation with the Lewis acid of the pyridine nitrogen that leads to a further decrease in the electron density in the N-oxyl radical. These results fully support the use of N-hydroxyquinolinimide as a convenient substitute for N-hydroxyphthalimide in the catalytic aerobic oxidations of aliphatic hydrocarbons characterized by relatively high C−H bond dissociation energies.

We present an extensive and diverse database of peptide conformational energies. Our database contains five different classes of model geometries: dipeptides, tripeptides, and disulfide-bridged, bioactive, and cyclic peptides. In total, the database consists of 3775 conformational energy data points and 4530 conformer geometries. All the reference energies have been calculated at the LC-ωPBE-XDM/aug-cc-pVTZ level of theory, which is shown to yield conformational energies with an accuracy in the order of tenths of a kcal/mol when compared to complete-basis-set coupled-cluster reference data. The peptide conformational data set (PEPCONF) is presented as a high-quality reference set for the development and benchmarking of molecular-mechanics and semi-empirical electronic structure methods, which are the most commonly used techniques in the modeling of medium to large proteins.

There has been significant interest in developing fast and accurate quantum mechanical methods for modeling large molecular systems. In this work, by utilizing a machine learning regression technique, we have developed new low-cost quantum mechanical approaches to model large molecular systems. The developed approaches rely on using one-electron Gaussian-type functions called atom-centered potentials (ACPs) to correct for the basis set incompleteness and the lack of correlation effects in the underlying minimal or small basis set Hartree−Fock (HF) methods. In particular, ACPs are proposed for ten elements common in organic and bioorganic chemistry (H, B, C, N, O, F, Si, P, S, and Cl) and four different base methods: two minimal basis sets (MINIs and MINIX) plus a double-ζ basis set (6-31G*) in combination with dispersion-corrected HF (HF-D3/MINIs, HF-D3/MINIX, HF-D3/6-31G*) and the HF-3c method. The new ACPs are trained on a very large set (73 832 data points) of noncovalent properties (interaction and conformational energies) and validated additionally on a set of 32 048 data points. All reference data are of complete basis set coupled-cluster quality, mostly CCSD(T)/CBS. The proposed ACP-corrected methods are shown to give errors in the tenths of a kcal/mol range for noncovalent interaction energies and up to 2 kcal/mol for molecular conformational energies. More importantly, the average errors are similar in the training and validation sets, confirming the robustness and applicability of these methods outside the boundaries of the training set. In addition, the performance of the new ACP-corrected methods is similar to complete basis set density functional theory (DFT) but at a cost that is orders of magnitude lower, and the proposed ACPs can be used in any computational chemistry program that supports effective-core potentials without modification. It is also shown that ACPs improve the description of covalent and noncovalent bond geometries of the underlying methods and that the improvement brought about by the application of the ACPs is directly related to the number of atoms to which they are applied, allowing the treatment of systems containing some atoms for which ACPs are not available. Overall, the ACP-corrected methods proposed in this work constitute an alternative accurate, economical, and reliable quantum mechanical approach to describe the geometries, interaction energies, and conformational energies of systems with hundreds to thousands of atoms.

We present an extensive and diverse dataset of bond separation energies associated with the homolytic cleavage of covalently bonded molecules (A-B) into their corresponding radical fragments (A. and B.). Our dataset contains two different classifications of model structures referred to as “Existing” (molecules with associated experimental data) and “Hypothetical” (molecules with no associated experimental data). In total, the dataset consists of 4502 datapoints (1969 datapoints from the Existing and 2533 datapoints from the Hypothetical classes). The dataset covers 49 unique X-Y type single bonds (except H-H, H-F, and H-Cl), where X and Y are H, B, C, N, O, F, Si, P, S, and Cl atoms. All the reference data was calculated at the (RO)CBS-QB3 level of theory. The reference bond separation energies are non-relativistic ground-state energy differences and contain no zero-point energy corrections. This new dataset of bond separation energies (BSE49) is presented as a high-quality reference dataset for assessing and developing computational chemistry methods.

Non-covalent interactions (NCIs) play an essential role in (bio)chemistry. Wavefunction-based methods combined with large basis sets are able to accurately describe inter-and intra-molecular NCIs but are not practical for large molecular systems. Semi-empirical corrections have been developed recently that, when combined with Hartree-Fock (HF) and a small basis set, show promise in the ability to predict non-covalent binding and conformational energies over a wide range of systems. Compared to large-basis-set correlated wavefunction methods, small-basis-set HF methods significantly lower computational cost and are useful for modeling large molecular systems with sizes between many hundreds and a few thousand atoms. Using a large collection of non-covalent binding energies, conformational energies, and molecular deformation energies containing 105 880 entries, we provide a comprehensive evaluation of the performance of the minimal basis set (MINIX) HF method with three correction schemes: D3, 3c, and atom-centered potentials (ACPs). We also evaluate the performance of HF/6-31G * in combination with the D3 and ACP schemes. By comparing the three corrections, we analyze the strengths and weaknesses associated with each strategy in predicting NCIs. Our results show that D3 corrections alone do not offer significant improvements in the performance of HF/MINIX or HF/6-31G * and, in some cases, overestimate binding energies resulting in large errors when compared to the reference data. The correction strategies that offer the best reduction in the underlying errors of HF/MINIX and HF/6-31G * are shown to be 3c and ACP for HF/MINIX and ACP for HF/6-31G * .