Multiscale QM/MM modelling of catalytic systems with ChemShell

Hybrid quantum mechanical/molecular mechanical (QM/MM) methods are a powerful computational tool for the investigation of all forms of catalysis, as they allow for an accurate description of reactions occurring at catalytic sites in the context of a complicated electrostatic environment. The scriptable computational chemistry environment ChemShell is a leading software package for QM/MM calculations, providing a flexible, high performance framework for modelling both biomolecular and materials catalysis. We present an overview of recent applications of ChemShell to problems in catalysis and review new functionality introduced into the redeveloped Python-based version of ChemShell to support catalytic modelling. These include a fully guided workflow for biomolecular QM/MM modelling, starting from an experimental structure, a periodic QM/MM embedding scheme to support modelling of metallic materials, and a comprehensive set of tutorials for biomolecular and materials modelling.

High-Pressure Synthesis of Cubic ZnO and Its Solid Solutions with MgO Doped with Li, Na, and K

The possibility of doping ZnO in its metastable rock salt structure with Li, Na, and K intended to act as acceptor dopants was investigated. For the first time, MgxZn1-xO alloys and pure ZnO with a rock salt structure doped with Li, Na, and K metals was obtained by high-pressure synthesis from pure oxides with the addition of carbonates or acetates of the corresponding metals as dopant sources. Successful stabilization of the metastable rock salt structure and phase purity were confirmed by X-ray diffraction. Transmission electron microscopy was used to study the particle size of nanocrystalline precursors, while the presence of Li, Na, and K metals in rock salt ZnO was detected by electron energy-loss spectroscopy and X-ray photoelectron spectroscopy in MgxZn1-xO alloys. Electron paramagnetic resonance measurements revealed the acceptor behavior of Li, Na, and K dopants based on the influence of the latter on native defects and natural impurities in ZnO-MgO alloys. In addition, diffuse reflectance spectroscopy was used to derive band gaps of quenched rock salt ZnO and its alloys with MgO.

The application of QM/MM simulations in heterogeneous catalysis

The QM/MM simulation method is provenly efficient for the simulation of biological systems, where an interplay of extensive environment and delicate local interactions drives a process of interest through a funnel on a complex energy landscape. Recent advances in quantum chemistry and force-field methods present opportunities for the adoption of QM/MM to simulate heterogeneous catalytic processes, and their related systems, where similar intricacies exist on the energy landscape. Herein, the fundamental theoretical considerations for performing QM/MM simulations, and the practical considerations for setting up QM/MM simulations of catalytic systems, are introduced; then, areas of heterogeneous catalysis are explored where QM/MM methods have been most fruitfully applied. The discussion includes simulations performed for adsorption processes in solvent at metallic interfaces, reaction mechanisms within zeolitic systems, nanoparticles, and defect chemistry within ionic solids. We conclude with a perspective on the current state of the field and areas where future opportunities for development and application exist.

A combined periodic DFT and QM/MM approach to understand the radical mechanism of the catalytic production of methanol from glycerol

The production of methanol from glycerol over a basic oxide, such as MgO, using high reaction temperatures (320 °C) is a promising new approach to improving atom efficiency in the production of biofuels. The mechanism of this reaction involves the homolytic cleavage of the C₃ feedstock, or its dehydration product hydroxyacetone, to produce a hydroxymethyl radical species which can then abstract an H atom from other species. Obtaining a detailed reaction mechanism for this type of chemistry is difficult due to the large number of products present when the system is operated at high conversions. In this contribution we show how DFT based modelling studies can provide new insights into likely reaction pathways, in particular the source of H atoms for the final step of converting hydroxymethyl radicals to methanol. We show that water is unlikely to be important in this stage of the process, C-H bonds of C₂ and C₃ species can give an energetically favourable pathway and that the disproportionation of hydroxymethyl radicals to methanol and formaldehyde produces a very favourable route. Experimental analysis of reaction products confirms the presence of formaldehyde. The calculations presented in this work also provide new insight into the role of the catalyst surface in the reaction showing that the base sites of the MgO(100) are able to deprotonate hydroxymethyl radicals but not methanol itself. In carrying out the calculations we also show how periodic DFT and QM/MM approaches can be used together to obtain a rounded picture of molecular adsorption to surfaces and homolytic bond cleavage which are both central to the reactions studied.

Open-Source, Python-Based Redevelopment of the ChemShell Multiscale QM/MM Environment

ChemShell is a scriptable computational chemistry environment with an emphasis on multiscale simulation of complex systems using combined quantum mechanical and molecular mechanical (QM/MM) methods. Motivated by a scientific need to efficiently and accurately model chemical reactions on surfaces and within microporous solids on massively parallel computing systems, we present a major redevelopment of the ChemShell code, which provides a modern platform for advanced QM/MM embedding models. The new version of ChemShell has been re-engineered from the ground up with a new QM/MM driver module, an improved parallelization framework, new interfaces to high performance QM and MM programs, and a user interface written in the Python programming language. The redeveloped package is capable of performing QM/MM calculations on systems of significantly increased size, which we illustrate with benchmarks on zirconium dioxide nanoparticles of over 160000 atoms.