Advances in theory and algorithms for electronic structure calculations must be incorporated into program packages to enable them to become routinely used by the broader chemical community. This work reviews advances made over the past five years or so that constitute the major improvements contained in a new release of the Q-Chem quantum chemistry package, together with illustrative timings and applications. Specific developments discussed include fast methods for density functional theory calculations, linear scaling evaluation of energies, NMR chemical shifts and electric properties, fast auxiliary basis function methods for correlated energies and gradients, equation-of-motion coupled cluster methods for ground and excited states, geminal wavefunctions, embedding methods and techniques for exploring potential energy surfaces.

We present a new approach for calculating reaction coordinates in complex systems. The new method is based on transition path sampling and likelihood maximization. It requires fewer trajectories than a single iteration of existing procedures, and it applies to both low and high friction dynamics. The new method screens a set of candidate collective variables for a good reaction coordinate that depends on a few relevant variables. The Bayesian information criterion determines whether additional variables significantly improve the reaction coordinate. Additionally, we present an advantageous transition path sampling algorithm and an algorithm to generate the most likely transition path in the space of collective variables. The method is demonstrated on two systems: a bistable model potential energy surface and nucleation in the Ising model. For the Ising model of nucleation, we quantify for the first time the role of nuclei surface area in the nucleation reaction coordinate. Surprisingly, increased surface area increases the stability of nuclei in two dimensions but decreases nuclei stability in three dimensions.

The current scale of plastics production and the accompanying waste disposal problems represent a largely untapped opportunity for chemical upcycling. Tandem catalytic conversion by platinum supported on γ-alumina converts various polyethylene grades in high yields (up to 80 weight percent) to low-molecular-weight liquid/wax products, in the absence of added solvent or molecular hydrogen, with little production of light gases. The major components are valuable long-chain alkylaromatics and alkylnaphthenes (average ~C30, dispersity Ð = 1.1). Coupling exothermic hydrogenolysis with endothermic aromatization renders the overall transformation thermodynamically accessible despite the moderate reaction temperature of 280°C. This approach demonstrates how waste polyolefins can be a viable feedstock for the generation of molecular hydrocarbon products.

Overconsumption of single-use plastics is creating a global waste catastrophe, with widespread environmental, economic, and health-related consequences. Inspired by the benefits of processive enzyme-catalyzed conversions of biomacromolecules and guided by spectroscopic interrogations of conformation and dynamics of polymer-surface interactions, we have developed the selective hydrogenolysis of high density polyethylene into a narrow distribution of diesel and lubricant-range alkanes catalyzed by an ordered, mesoporous shell/active site/core catalyst architecture. Solid-state nuclear magnetic resonance investigations of polymer chains adsorbed onto solid materials reveal that an appropriately ordered, porous support orients polymer chains into an all-anti conformation, while measurements of polymer dynamics reveal that long hydrocarbon macromolecules readily move within the pores, with a subsequent escape being inhibited by polymer-surface interactions. These interactions and dynamic behavior resemble the binding and translocation of macromolecules in the catalytic cleft of processive enzymes. Thus, transfer of these features to a mesoporous silica material incorporating catalytic platinum sites for carbon-carbon bond hydrogenolysis of polyethylene provides a reliable stream of alkane products through a processive process.

Interpolation methods such as the nudged elastic band and string methods are widely used for calculating minimum energy pathways and transition states for chemical reactions. Both methods require an initial guess for the reaction pathway. A poorly chosen initial guess can cause slow convergence, convergence to an incorrect pathway, or even failed electronic structure force calculations along the guessed pathway. This paper presents a growing string method that can find minimum energy pathways and transition states without the requirement of an initial guess for the pathway. The growing string begins as two string fragments, one associated with the reactants and the other with the products. Each string fragment is grown separately until the fragments converge. Once the two fragments join, the full string moves toward the minimum energy pathway according to the algorithm for the string method. This paper compares the growing string method to the string method and to the nudged elastic band method using the alanine dipeptide rearrangement as an example. In this example, for which the linearly interpolated guess is far from the minimum energy pathway, the growing string method finds the saddle point with significantly fewer electronic structure force calculations than the string method or the nudged elastic band method.