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.

A combination of interpolation methods and local saddle-point search algorithms is probably the most efficient way of finding transition states in chemical reactions. Interpolation methods such as the growing-string method and the nudged-elastic band are able to find an approximation to the minimum-energy pathway and thereby provide a good initial guess for a transition state and imaginary mode connecting both reactant and product states. Since interpolation methods employ usually just a small number of configurations and converge slowly close to the minimum-energy pathway, local methods such as partitioned rational function optimization methods using either exact or approximate Hessians or minimum-mode-following methods such as the dimer or the Lanczos method have to be used to converge to the transition state. A modification to the original dimer method proposed by [Henkelman and Jonnson J. Chem. Phys. 111, 7010 (1999)] is presented, reducing the number of gradient calculations per cycle from six to four gradients or three gradients and one energy, and significantly improves the overall performance of the algorithm on quantum-chemical potential-energy surfaces, where forces are subject to numerical noise. A comparison is made between the dimer methods and the well-established partitioned rational function optimization methods for finding transition states after the use of interpolation methods. Results for 24 different small- to medium-sized chemical reactions covering a wide range of structural types demonstrate that the improved dimer method is an efficient alternative saddle-point search algorithm on medium-sized to large systems and is often even able to find transition states when partitioned rational function optimization methods fail to converge.

Our civilization relies on synthetic polymers for all aspects of modern life; yet, inefficient recycling and extremely slow environmental degradation of plastics are causing increasing concern about their widespread use. After a single use, many of these materials are currently treated as waste, underutilizing their inherent chemical and energy value. In this study, energy-rich polyethylene (PE) macromolecules are catalytically transformed into value-added products by hydrogenolysis using well-dispersed Pt nanoparticles (NPs) supported on SrTiO3 perovskite nanocuboids by atomic layer deposition. Pt/SrTiO3 completely converts PE (Mn = 8000–158,000 Da) or a single-use plastic bag (Mn = 31,000 Da) into high-quality liquid products, such as lubricants and waxes, characterized by a narrow distribution of oligomeric chains, at 170 psi H2 and 300 °C under solvent-free conditions for reaction durations up to 96 h. The binding of PE onto the catalyst surface contributes to the number averaged molecular weight (Mn) and the narrow polydispersity (Đ) of the final liquid product. Solid-state nuclear magnetic resonance of 13C-enriched PE adsorption studies and density functional theory computations suggest that PE adsorption is more favorable on Pt sites than that on the SrTiO3 support. Smaller Pt NPs with higher concentrations of undercoordinated Pt sites over-hydrogenolyzed PE to undesired light hydrocarbons.

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.