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.

Effective core potential (ECP) integrals are among the most difficult one-electron integrals to calculate due to the projection operators. The radial part of these operators may include r, r, and r terms. For the r terms, we exploit a simple analytic expression for the fundamental projected integral to derive new recurrence relations and upper bounds for ECP integrals. For the r and r terms, we present a reconstruction method that replaces these terms by a sum of r terms and show that the resulting errors are chemically insignificant for a range of molecular properties. The new algorithm is available in Q-Chem 5.0 and is significantly faster than the ECP implementations in Q-Chem 4.4, GAMESS (US) and Dalton 2016.

We present a quadrature-based algorithm for computing the opposite-spin component of the MP2 correlation energy which scales quadratically with basis set size and is well-suited to large-scale parallelization. The key ideas, which are rooted in the earlier work of Hirata and co-workers, are to abandon all two-electron integrals, recast the energy as a seven-dimensional integral, approximate that integral by quadrature, and employ a cutoff strategy to minimize the number of intermediate quantities. We discuss our implementation in detail and show that it parallelizes almost perfectly on 840 cores for cyclosporine (a molecule with roughly 200 atoms), exhibits scaling for a sequence of polyglycines, and is principally limited by the accuracy of its quadrature.

The behavior of water confined at the nanoscale between graphene sheets has attracted much theoretical and experimental attention recently. However, the interactions, structure, and energy of water at the molecular scale underpinning the behavior of confined water have not been characterized by first-principles calculations. In this work we consider small water clusters up to the hexamer adsorbed between graphene sheets using density functional theory calculations with van der Waals corrections. We investigate the effects on structure, energy, and intermolecular interactions due to confinement between graphene sheets. For interlayer distances of about one nanometer or more, the cluster adsorption energy increases approximately linearly with the cluster size by 0.1 eV per molecule in the cluster. As the interlayer distance decreases, the cluster adsorption energy reaches a maximum at 6 to 7 Å with approximately 0.16 eV stabilization energy relative to large interlayer distances. This suggests the possibility of controlling the amount of adsorption in graphene nanomaterials by varying the interlayer distance. We also quantify the intermolecular hydrogen bonding in the clusters by calculating the dissociation energy required to remove one molecule from each cluster. For each cluster size, this is constant for interlayer distances larger than approximately 6 to 8 Å. For smaller distances the intermolecular interaction decreases rapidly thus leading to weaker cohesion between molecules in a squeezed cluster. We expect a mechanism of concerted motion for hydrogen-bonded water molecules confined between graphene sheets, as has been observed for water confined within the carbon nanotubes. Thus, the decrease in the dissociation energy we observed here is consistent with experimental results for water transport through graphene and related membranes that are of interest in nanofiltration. We also calculate the corrugation in the interaction potential between graphene sheets which suggests a switch from very small corrugation to stick-slip behavior at interlayer distances smaller than 6 Å. Our results for gas phase clusters agree reasonably with methods using more demanding quantum chemical methods to treat the van der Waals interactions, thus providing support for the relatively fast density functional theory methods used here for studying water-graphene interactions in nanoscale systems.