This article summarizes technical advances contained in the fifth major release of the Q-Chem quantum chemistry program package, covering developments since 2015. A comprehensive library of exchange–correlation functionals, along with a suite of correlated many-body methods, continues to be a hallmark of the Q-Chem software. The many-body methods include novel variants of both coupled-cluster and configuration-interaction approaches along with methods based on the algebraic diagrammatic construction and variational reduced density-matrix methods. Methods highlighted in Q-Chem 5 include a suite of tools for modeling core-level spectroscopy, methods for describing metastable resonances, methods for computing vibronic spectra, the nuclear–electronic orbital method, and several different energy decomposition analysis techniques. High-performance capabilities including multithreaded parallelism and support for calculations on graphics processing units are described. Q-Chem boasts a community of well over 100 active academic developers, and the continuing evolution of the software is supported by an “open teamware” model and an increasingly modular design.

An energy decomposition analysis (EDA) separates a calculated interaction energy into as many interpretable contributions as possible; for instance, permanent and induced electrostatics, Pauli repulsions, dispersion and charge transfer. The challenge is to construct satisfactory definitions of all terms in the chemically relevant regime where fragment densities overlap, rendering unique definitions impossible. Towards this goal, we present an improved EDA for Kohn–Sham density functional theory (DFT) with properties that have previously not been simultaneously attained. Building on the absolutely localized molecular orbital (ALMO)-EDA, this second generation ALMO-EDA is variational and employs valid antisymmetric electronic wavefunctions to produce all five contributions listed above. These contributions moreover all have non-trivial complete basis set limits. We apply the EDA to the water dimer, the T-shaped and parallel-displaced benzene dimer, the p-biphthalate dimer “anti-electrostatic” hydrogen bonding complex, the biologically relevant binding of adenine and thymine in stacked and hydrogen-bonded configurations, the triply hydrogen-bonded guanine–cytosine complex, the interaction of Cl⁻ with s-triazine and with the 1,3-dimethyl imidazolium cation, which is relevant to the study of ionic liquids, and the water–formaldehyde–vinyl alcohol ter-molecular radical cationic complex formed in the dissociative photoionization of glycerol.

Machine learning potentials are an important tool for molecular simulation, but their development is held back by a shortage of high quality datasets to train them on. We describe the SPICE dataset, a new quantum chemistry dataset for training potentials relevant to simulating drug-like small molecules interacting with proteins. It contains over 1.1 million conformations for a diverse set of small molecules, dimers, dipeptides, and solvated amino acids. It includes 15 elements, charged and uncharged molecules, and a wide range of covalent and non-covalent interactions. It provides both forces and energies calculated at the ωB97M-D3(BJ)/def2-TZVPPD level of theory, along with other useful quantities such as multipole moments and bond orders. We train a set of machine learning potentials on it and demonstrate that they can achieve chemical accuracy across a broad region of chemical space. It can serve as a valuable resource for the creation of transferable, ready to use potential functions for use in molecular simulations.

In energy decomposition analysis of Kohn-Sham density functional theory calculations, the so-called frozen (or pre-polarization) interaction energy contains contributions from permanent electrostatics, dispersion, and Pauli repulsion. The standard classical approach to separate them suffers from several well-known limitations. We introduce an alternative scheme that employs valid antisymmetric electronic wavefunctions throughout and is based on the identification of individual fragment contributions to the initial supersystem wavefunction as determined by an energetic optimality criterion. The density deformations identified with individual fragments upon formation of the initial supersystem wavefunction are analyzed along with the distance dependence of the new and classical terms for test cases that include the neon dimer, ammonia borane, water-Na⁺, water-Cl⁻, and the naphthalene dimer.

It is common to introduce electron-donating or electron-withdrawing substituent groups into functional conjugated molecules (such as dyes) to tune their electronic structure properties (such as frontier orbital energy levels) and photophysical properties (such as absorption and emission wavelengths). However, there lacks a generally applicable tool that can unravel the underlying interactions between orbitals from a substrate molecule and those from its substituents in modern electronic structure calculations, despite the long history of qualitative molecular orbital theory. In this work, the absolutely localized molecular orbitals (ALMO) based analysis is extended to analyze the effects of substituent groups on the highest occupied molecular orbital (HOMO) and lowest unoccupied molecular orbital (LUMO) of a given system. This provides a bottom-up avenue towards quantification of effects from distinct physical origins (e.g. permanent electrostatics/Pauli repulsion, mutual polarization, inter-fragment orbital mixing). For the example case of prodan (a typical dye molecule), it is found that inter-fragment orbital mixing plays a key role in narrowing the HOMO–LUMO gap of the naphthalene core. Specifically, an out-of-phase mixing of high-lying occupied orbitals on the naphthalene core and the dimethylamino group leads to an elevated HOMO, whereas an in-phase combination of LUMOs on the naphthalene core and the propionyl group lowers the LUMO energy of the entire molecule. We expect this ALMO-based analysis to bridge the gap between concepts from qualitative orbital interaction analysis and quantitative electronic structure calculations.