Computational infrared and Raman spectra by hybrid QM/MM techniques: a study on molecular and catalytic material systems.

Vibrational spectroscopy is one of the most well-established and important techniques for characterizing chemical systems. To aid the interpretation of experimental infrared and Raman spectra, we report on recent theoretical developments in the ChemShell computational chemistry environment for modelling vibrational signatures. The hybrid quantum mechanical and molecular mechanical approach is employed, using density functional theory for the electronic structure calculations and classical forcefields for the environment. Computational vibrational intensities at chemical active sites are reported using electrostatic and fully polarizable embedding environments to achieve more realistic vibrational signatures for materials and molecular systems, including solvated molecules, proteins, zeolites and metal oxide surfaces, providing useful insight into the effect of the chemical environment on the signatures obtained from experiment. This work has been enabled by the efficient task-farming parallelism implemented in ChemShell for high-performance computing platforms.  This article is part of a discussion meeting issue 'Supercomputing simulations of advanced materials'.

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.

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.

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. Low-concentration Mn doping is endothermic for isovalent species in the bulk but exothermic for higher oxidation states under p-type conditions, and compensated by electrons going to the Fermi level rather than cation vacancies. The highest occupied dopant Mn 3d states are positioned in the MgO band gap, about 4.2 eV below the vacuum level. Surface Mn-doping is more favourable than subsurface doping, and marginally exothermic on a (100) surface at high O2 pressures. For both types of isovalent Mn-doped (100) surfaces, the formation energy for catalytically important oxygen defects is less than for pristine MgO, with F0 and F2+-centres favoured in n- and p-type conditions, respectively. In addition, F+-centres are stabilised by favourable exchange coupling between the Mn 3d states and the vacancy-localised electrons, as verified through calculation of the vertical ionisation potential. The adsorption of CO2 on to the pristine and defective (100) surface is used as a probe of chemical reactivity, with isovalent subsurface Mn dopants mildly affecting reactivity, whereas isovalent surface-positioned Mn strongly alters the chemical interactions between the substrate and adsorbate. The differing chemical reactivity, when compared to pristine MgO, justifies further detailed investigations for more varied oxidation states and dopant species.

Embedded-cluster calculations in a numeric atomic orbital density-functional theory framework.

We integrate the all-electron electronic structure code FHI-aims into the general ChemShell package for solid-state embedding quantum and molecular mechanical (QM/MM) calculations. A major undertaking in this integration is the implementation of pseudopotential functionality into FHI-aims to describe cations at the QM/MM boundary through effective core potentials and therewith prevent spurious overpolarization of the electronic density. Based on numeric atomic orbital basis sets, FHI-aims offers particularly efficient access to exact exchange and second order perturbation theory, rendering the established QM/MM setup an ideal tool for hybrid and double-hybrid level density functional theory calculations of solid systems. We illustrate this capability by calculating the reduction potential of Fe in the Fe-substituted ZSM-5 zeolitic framework and the reaction energy profile for (photo-)catalytic water oxidation at TiO2(110).

Band alignment of rutile and anatase TiO2.

The most widely used oxide for photocatalytic applications owing to its low cost and high activity is TiO2. The discovery of the photolysis of water on the surface of TiO2 in 1972 launched four decades of intensive research into the underlying chemical and physical processes involved. Despite much collected evidence, a thoroughly convincing explanation of why mixed-phase samples of anatase and rutile outperform the individual polymorphs has remained elusive. One long-standing controversy is the energetic alignment of the band edges of the rutile and anatase polymorphs of TiO2 (ref. ). We demonstrate, through a combination of state-of-the-art materials simulation techniques and X-ray photoemission experiments, that a type-II, staggered, band alignment of ~ 0.4 eV exists between anatase and rutile with anatase possessing the higher electron affinity, or work function. Our results help to explain the robust separation of photoexcited charge carriers between the two phases and highlight a route to improved photocatalysts.

Activation of carbon dioxide over zinc oxide by localised electrons.

The unique mechanism of activation of carbon dioxide over zinc oxide is unravelled using advanced quantum mechanical methods. The key process is the CO(2) chemisorption catalysed by a highly localized electron carrier trapped at a vacant oxygen interstitial surface site. At the top of the reaction barrier CO(2) pulls the electron from the vacancy and thus becomes active.

The Quixote project: Collaborative and Open Quantum Chemistry data management in the Internet age.

Computational Quantum Chemistry has developed into a powerful, efficient, reliable and increasingly routine tool for exploring the structure and properties of small to medium sized molecules. Many thousands of calculations are performed every day, some offering results which approach experimental accuracy. However, in contrast to other disciplines, such as crystallography, or bioinformatics, where standard formats and well-known, unified databases exist, this QC data is generally destined to remain locally held in files which are not designed to be machine-readable. Only a very small subset of these results will become accessible to the wider community through publication.In this paper we describe how the Quixote Project is developing the infrastructure required to convert output from a number of different molecular quantum chemistry packages to a common semantically rich, machine-readable format and to build respositories of QC results. Such an infrastructure offers benefits at many levels. The standardised representation of the results will facilitate software interoperability, for example making it easier for analysis tools to take data from different QC packages, and will also help with archival and deposition of results. The repository infrastructure, which is lightweight and built using Open software components, can be implemented at individual researcher, project, organisation or community level, offering the exciting possibility that in future many of these QC results can be made publically available, to be searched and interpreted just as crystallography and bioinformatics results are today.Although we believe that quantum chemists will appreciate the contribution the Quixote infrastructure can make to the organisation and and exchange of their results, we anticipate that greater rewards will come from enabling their results to be consumed by a wider community. As the respositories grow they will become a valuable source of chemical data for use by other disciplines in both research and education.The Quixote project is unconventional in that the infrastructure is being implemented in advance of a full definition of the data model which will eventually underpin it. We believe that a working system which offers real value to researchers based on tools and shared, searchable repositories will encourage early participation from a broader community, including both producers and consumers of data. In the early stages, searching and indexing can be performed on the chemical subject of the calculations, and well defined calculation meta-data. The process of defining more specific quantum chemical definitions, adding them to dictionaries and extracting them consistently from the results of the various software packages can then proceed in an incremental manner, adding additional value at each stage.Not only will these results help to change the data management model in the field of Quantum Chemistry, but the methodology can be applied to other pressing problems related to data in computational and experimental science.

Acceleration of the GAMESS-UK electronic structure package on graphical processing units.

The approach used to calculate the two-electron integral by many electronic structure packages including generalized atomic and molecular electronic structure system-UK has been designed for CPU-based compute units. We redesigned the two-electron compute algorithm for acceleration on a graphical processing unit (GPU). We report the acceleration strategy and illustrate it on the (ss|ss) type integrals. This strategy is general for Fortran-based codes and uses the Accelerator compiler from Portland Group International and GPU-based accelerators from Nvidia. The evaluation of (ss|ss) type integrals within calculations using Hartree Fock ab initio methods and density functional theory are accelerated by single and quad GPU hardware systems by factors of 43 and 153, respectively. The overall speedup for a single self consistent field cycle is at least a factor of eight times faster on a single GPU compared with that of a single CPU.

DL-FIND: an open-source geometry optimizer for atomistic simulations.

Geometry optimization, including searching for transition states, accounts for most of the CPU time spent in quantum chemistry, computational surface science, and solid-state physics, and also plays an important role in simulations employing classical force fields. We have implemented a geometry optimizer, called DL-FIND, to be included in atomistic simulation codes. It can optimize structures in Cartesian coordinates, redundant internal coordinates, hybrid-delocalized internal coordinates, and also functions of more variables independent of atomic structures. The implementation of the optimization algorithms is independent of the coordinate transformation used. Steepest descent, conjugate gradient, quasi-Newton, and L-BFGS algorithms as well as damped molecular dynamics are available as minimization methods. The partitioned rational function optimization algorithm, a modified version of the dimer method and the nudged elastic band approach provide capabilities for transition-state search. Penalty function, gradient projection, and Lagrange-Newton methods are implemented for conical intersection optimizations. Various stochastic search methods, including a genetic algorithm, are available for global or local minimization and can be run as parallel algorithms. The code is released under the open-source GNU LGPL license. Some selected applications of DL-FIND are surveyed.

An embedded cluster study of the formation of water on interstellar dust grains.

The formation of water in the interstellar medium from hydrogen and oxygen atoms on a pristine olivine surface (forsterite (010)) is investigated with an embedded cluster approach. The 55-atom quantum cluster is described at the density functional level while the remaining 1629 atoms of the surface cluster are described with atomistic potentials. Transition states are most easily calculated with our modified implementation of the climbing-image nudged elastic band method in ChemShell. With these computational techniques, we find that gas phase hydrogen atoms can chemisorb (-102 kJ mol(-1)) without an activation barrier on the forsterite (010) surface, concomitantly creating a surface electron at the adjacent magnesium atom site. Subsequently, an oxygen atom chemisorbs strongly to this surface electron site (-432 kJ mol(-1)). The rearrangement of the adjacently chemisorbed O and H to a chemisorbed OH-radical is endothermic by 4 kJ mol(-1) and activated by 27 kJ mol(-1). This chemisorbed OH can then react barrierlessly with a second hydrogen atom to yield adsorbed water (-511 kJ mol(-1)). Alternatively, if O and H do not recombine to form OH, but instead thermally equilibrate, a second hydrogen atom can react with the chemisorbed oxygen atom (-501 kJ mol(-1)) to yield dissociatively adsorbed water (OH(-) and H(+)), which then can rearrange to associatively adsorbed water (-5 kJ mol(-1), DeltaE(double dagger) = 18 kJ mol(-1)) or gas phase water (+91 kJ mol(-1)). The formation of water on a bare dust grain from hydrogen and oxygen atoms is thus catalysed by an olivine surface by stabilising the reaction intermediates and product. Since the reaction proceeds via three chemisorbed intermediates, thermal equilibration is facilitated and back-dissociation of the freshly formed reaction products OH and H(2)O would not occur as frequently as it would in the gas phase or when the reactants are physisorbed on a surface.

Multiscale methods for macromolecular simulations.

In this article we review the key modeling tools available for simulating biomolecular systems. We consider recent developments and representative applications of mixed quantum mechanics/molecular mechanics (QM/MM), elastic network models (ENMs), coarse-grained molecular dynamics, and grid-based tools for calculating interactions between essentially rigid protein assemblies. We consider how the different length scales can be coupled, both in a sequential fashion (e.g. a coarse-grained or grid model using parameterization from MD simulations), and via concurrent approaches, where the calculations are performed together and together control the progression of the simulation. We suggest how the concurrent coupling approach familiar in the context of QM/MM calculations can be generalized, and describe how this has been done in the CHARMM macromolecular simulation package.

Superlinearly converging dimer method for transition state search.

Algorithmic improvements of the dimer method [G. Henkelman and H. Jonsson, J. Chem. Phys. 111, 7010 (1999)] are described in this paper. Using the limited memory Broyden-Fletcher-Goldfarb-Shanno (L-BFGS) optimizer for the dimer translation greatly improves the convergence compared to the previously used conjugate gradient algorithm. It also saves one energy and gradient calculation per dimer iteration. Extrapolation of the gradient during repeated dimer rotations reduces the computational cost to one gradient calculation per dimer rotation. The L-BFGS algorithm also improves convergence of the rotation. Thus, three to four energy and gradient evaluations are needed per iteration at the beginning of a transition state search, while only two are required close to convergence. Moreover, we apply the dimer method in internal coordinates to reduce coupling between the degrees of freedom. Weighting the coordinates can be used to apply chemical knowledge about the system and restrict the transition state search to only part of the system while minimizing the remainder. These improvements led to an efficient method for the location of transition states without the need to calculate the Hessian. Thus, it is especially useful in large systems with expensive gradient evaluations.

Point defects in ZnO.

We have investigated intrinsic point defects in ZnO and extended this study to Li, Cu and Al impurity centres. Atomic and electronic structures as well as defect energies have been obtained for the main oxidation states of all defects using our embedded cluster hybrid quantum mechanical/molecular mechanical approach to the treatment of localised states in ionic solids. With these calculations we were able to explain the nature of a number of experimentally observed phenomena. We show that in zinc excess materials the energetics of zinc interstitial are very similar to those for oxygen vacancy formation. Our results also suggest assignments for a number of bands observed in photoluminescence and other spectroscopic studies of the material.

Exploiting QM/MM Capabilities in Geometry Optimization: A Microiterative Approach Using Electrostatic Embedding.

We present a microiterative adiabatic scheme for quantum mechanical/molecular mechanical (QM/MM) energy minimization that fully optimizes the MM part in each QM macroiteration. This scheme is applicable not only to mechanical embedding but also to electrostatic and polarized embedding. The electrostatic QM/MM interactions in the microiterations are calculated from electrostatic potential charges fitted on the fly to the QM density. Corrections to the energy and gradient expressions ensure that macro- and microiterations are performed on the same energy surface. This results in excellent convergence properties and no loss of accuracy compared to standard optimization. We test our implementation on water clusters and on two enzymes using electrostatic embedding, as well as on a surface example using polarized embedding with a shell model. Our scheme is especially well-suited for systems containing large MM regions, since the computational effort for the optimization is almost independent of the MM system size. The microiterations reduce the number of required QM calculations typically by a factor of 2-10, depending on the system.

On the performance of molecular dynamics applications on current high-end systems.

The effective exploitation of current high performance computing (HPC) platforms in molecular simulation relies on the ability of the present generation of parallel molecular dynamics code to make effective utilisation of these platforms and their components, including CPUs and memory. In this paper, we investigate the efficiency and scaling of a series of popular molecular dynamics codes on the UK's national HPC resources, an IBM p690+ cluster and an SGI Altix 3700. Focusing primarily on the AMBER, DL_POLY and NAMD simulation codes, we demonstrate the major performance and scalability advantages that arise through a distributed, rather than a replicated data approach.

Supramolecular chemistry of halogens: complementary features of inorganic (M-X) and organic (C-X') halogens applied to M-X...X'-C halogen bond formation.

Electronic differences between inorganic (M-X) and organic (C-X) halogens in conjunction with the anisotropic charge distribution associated with terminal halogens have been exploited in supramolecular synthesis based upon intermolecular M-X...X'-C halogen bonds. The synthesis and crystal structures of a family of compounds trans-[MCl(2)(NC(5)H(4)X-3)(2)] (M = Pd(II), Pt(II); X = F, Cl, Br, I; NC(5)H(4)X-3 = 3-halopyridine) are reported. With the exception of the fluoropyridine compounds, network structures propagated by M-Cl...X-C halogen bonds are adopted and involve all M-Cl and all C-X groups. M-Cl...X-C interactions show Cl...X separations shorter than van der Waals values, shorter distances being observed for heavier halogens (X). Geometries with near linear Cl...X-C angles (155-172 degrees ) and markedly bent M-Cl...X angles (92-137 degrees ) are consistently observed. DFT calculations on the model dimers {trans-[MCl(2)(NH(3))(NC(5)H(4)X-3)]}(2) show association through M-Cl...X-C (X not equal F) interactions with geometries similar to experimental values. DFT calculations of the electrostatic potential distributions for the compounds trans-[PdCl(2)(NC(5)H(4)X-3)(2)] (X = F, Cl, Br, I) demonstrate the effectiveness of the strategy to activate C-X groups toward halogen bond formation by enhancing their electrophilicity, and explain the absence of M-Cl...F-C interactions. The M-Cl...X-C halogen bonds described here can be viewed unambiguously as nucleophile-electrophile interactions that involve an attractive electrostatic contribution. This contrasts with some types of halogen-halogen interactions previously described and suggests that M-Cl...X-C halogen bonds could provide a valuable new synthon for supramolecular chemists.