Hybrid-DFT Modeling of Lattice and Surface Vacancies in MnO

We have investigated the properties of defects in MnO bulk and at (100) surfaces, as used in catalytic applications, using hybrid-level density functional theory (i.e., inclusion of exact exchange within the exchange-correlation evaluation) in a hybrid QM/MM embedded-cluster approach. Initially, we calculate the formation energy for bulk Mn and O vacancies, comparing charged-defect compensation with charge carriers at the Fermi Level (ϵf) and through Schottky defect formation. Oxygen vacancies were also investigated at the (100) surface, where the vacancy formation energy is very similar to the bulk. Defect levels associated with the most stable vacancies are calculated using the ΔSCF method: all are positioned mid band gap, with surface environments failing to alter strongly the overall nature of the defect relative to bulk. Chemical activity of the (100) MnO surface was considered through the adsorption of a probe CO2 molecule, which is considered the initial step in the transformation of CO2 into hydrocarbons. CO2 adsorption was strongest over a neutral oxygen vacancy, where the associated trapped electrons of the defect transfer to the adsorbate and thus activate it. However, we have shown with our embedded-cluster approach that the neutral oxygen vacancy is not necessarily the dominant species, which has implications when interpreting results for future catalytic applications

An 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 160,000 atoms

Determination of the nitrogen vacancy as a shallow compensating center in GaN doped with divalent metals

We report accurate energetics of defects introduced in GaN on doping with divalent metals, focussing on the technologically important case of Mg doping, using a model which takes into consideration both the effect of hole localisation and dipolar polarisation of the host material, and includes a well-defined reference level. Defect formation and ionisation energies show that divalent dopants are counterbalanced in GaN by nitrogen vacancies and not by holes, which explains both the difficulty in achieving p-type conductivity in GaN and the associated major spectroscopic features, including the ubiquitous 3.46 eV photoluminescence line, a characteristic of all lightly divalent metal-doped GaN materials that has also been shown to occur in pure GaN samples. Our results give a comprehensive explanation for the observed behaviour of GaN doped with low concentrations of divalent metals in good agreement with relevant experiment

Demonstration of the donor characteristics of Si and O defects in GaN using hybrid QM/MM

Using hybrid quantum mechanical/molecular mechanical (QM/MM) embedded cluster calculations, we investigate the stabilization of silicon and oxygen dopants in GaN. Formation energies of Si on a Ga site and O on an N site are calculated at two levels of theory using conventional thermochemical and kinetic exchange and correlation density functionals (B97-2 and BB1k). We confirm the shallow donor nature of these substitutional defects. We find that the 0/1+ transition levels for both Si and O species lie well above the bottom of the conduction band, in agreement with previous supercell-based simulations. The origin of this artifact is discussed in the context of relevant experimental results and we show how correct in-gap shallow levels can be ascertained in good agreement with experiment

Demonstration of the donor characteristics of Si and O defects in GaN using hybrid QM/MM

Using hybrid quantum mechanical/molecular mechanical (QM/MM) embedded cluster calculations, we investigate the stabilization of silicon and oxygen dopants in GaN. Formation energies of Si on a Ga site and O on an N site are calculated at two levels of theory using conventional thermochemical and kinetic exchange and correlation density functionals (B97-2 and BB1k). We confirm the shallow donor nature of these substitutional defects. We find that the 0/1+ transition levels for both Si and O species lie well above the bottom of the conduction band, in agreement with previous supercell-based simulations. The origin of this artifact is discussed in the context of relevant experimental results and we show how correct in-gap shallow levels can be ascertained in good agreement with experiment

π-π stacking tackled with density functional theory

Through comparison with ab initio reference data, we have evaluated the performance of various density functionals for describing π-π interactions as a function of the geometry between two stacked benzenes or benzene analogs, between two stacked DNA bases, and between two stacked Watson–Crick pairs. Our main purpose is to find a robust and computationally efficient density functional to be used specifically and only for describing π-π stacking interactions in DNA and other biological molecules in the framework of our recently developed QM/QM approach "QUILD". In line with previous studies, most standard density functionals recover, at best, only part of the favorable stacking interactions. An exception is the new KT1 functional, which correctly yields bound π-stacked structures. Surprisingly, a similarly good performance is achieved with the computationally very robust and efficient local density approximation (LDA). Furthermore, we show that classical electrostatic interactions determine the shape and depth of the π-π stacking potential energy surface

Materials and Molecular Modelling at the Exascale

Progression of computational resources towards exascale computing makes possible simulations of unprecedented accuracy and complexity in the fields of materials and molecular modelling (MMM), allowing high fidelity in silico experiments on complex materials of real technological interest. However, this presents demanding challenges for the software used, especially the exploitation of the huge degree of parallelism available on exascale hardware, and the associated problems of developing effective workflows and data management on such platforms. As part of the UKs ExCALIBUR exascale computing initiative, the UK-led MMM Design and Development Working Group has worked with the broad MMM community to identify a set of high priority application case studies which will drive future exascale software developments. We present an overview of these case studies, categorized by the methodological challenges which will be required to realize them on exascale platforms, and discuss the exascale requirements, software challenges and impact of each application area