Level-Shifted Embedded Cluster Method for Modeling the Chemistry of Metal Oxides

The embedded cluster method has been used extensively in the study of the chemical and physical properties of metal oxides. This method has been a popular tool due to its relatively high accuracy and low computational cost. An even more promising option may entail integrating the embedded cluster method with the combined quantum mechanical and molecular mechanical (QM/MM) approach, thereby enabling further consideration of interactions within the entire system for superior results. We aim to accurately model the chemistry of metal oxides using this combined scheme. Here, using the prototypical MgO(100) surface as a test system, with Mg9O14 as the cluster in the quantum mechanical region, we show that the embedded cluster with untailored boundary effective core potentials (ECPs) can have frontier orbital energy levels that substantially deviate from the quantum mechanical reference results. This occurs even when Mg9O9, which retains the stoichiometry of MgO, is used as the cluster in the quantum mechanical region. As a result, the chemical properties of the embedded cluster models differ from those of the quantum mechanical reference model. To address this issue, we propose a new variant of the embedded cluster method called the level-shifted embedded cluster (LSEC) method, which allows the energy levels to be shifted to match the reference levels by tuning the boundary ECPs. Our validation calculations on the adsorption of various adsorbates with different properties on the MgO(100) surface show that the overall performance of QM/MM with the LSEC method is excellent for the adsorption energies, geometries, and charge properties. The excellent performance holds for both the nonstoichiometric and stoichiometric clusters (i.e., Mg9O14 and Mg9O9, respectively), demonstrating the robustness of the LSEC method. We expect that the LSEC method can be combined with QM/MM or used separately for future chemical studies of metal oxides and other ionically bonded systems.

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.

Heterogeneous catalytic hydrogenation of CO2by metal oxides: defect engineering – perfecting imperfection

In this review, we discuss how metal oxides with designed defects can be synthesized and engineered, to enable heterogeneous catalytic hydrogenation of gaseous carbon dioxide to chemicals and fuels.

Modelling the chemistry of Mn-doped MgO for bulk and (100) surfaces

We have investigated the energetic properties of Mn-doped MgO bulk and (100) surfaces using a QM/MM embedding computational method, calculating the formation energy for doped systems, as well as for surface defects, and the subsequent effect on chemical reactivity.