Quantum Nature of the Proton in Water-Hydroxyl Overlayers on Metal Surfaces

Using ab initio path-integral molecular dynamics, we show that water-hydroxyl overlayers on transition metal surfaces exhibit surprisingly pronounced quantum nuclear effects. The metal substrates serve to reduce the classical proton transfer barriers within the overlayers and, in analogy to ice under high pressure, to shorten the corresponding intermolecular hydrogen bonds. Depending on the substrate and the intermolecular separations it imposes, the traditional distinction between covalent and hydrogen bonds is lost partially [e.g., on Pt(111) and Ru(0001)] or almost entirely [e.g., on Ni(111)]. We suggest that these systems provide an excellent platform on which to systematically explore the magnitude of quantum nuclear effects in hydrogen bonds

Langevin dynamics in constant pressure extended systems

The advantages of performing Langevin dynamics in extended systems are discussed. A simple Langevin dynamics scheme for producing the canonical ensemble is reviewed, and is then extended to the Hoover ensemble. We show that the resulting equations of motion generate the isobaric–isothermal ensemble. The Parrinello–Rahman ensemble is then discussed and we show that despite the presence of intrinsic probability gradients in this system, a Langevin dynamics approach samples the extended phase space in the correct fashion. The implementation of these methods in the ab initio plane wave density functional theory code CASTEP [M. D. Segall, P. L. D. Lindan, M. J. Probert, C. J. Pickard, P. J. Hasnip, S. J. Clarke, and M. C. Payne, J. Phys.: Condens. Matter 14, 2717 (2003)] is demonstrated

A periodic genetic algorithm with real-space representation for crystal structure and polymorph prediction

A genetic algorithm is described that is suitable for determining the global minimum energy configurations of crystal structures and which can also be used as a polymorph search technique. This algorithm requires no prior assumptions about unit cell size, shape, or symmetry, nor about the ionic configuration within the unit cell. This therefore enables true ab initio crystal structure and polymorph prediction. Our algorithm uses a real-space representation of the population members, and makes use of a periodic cut for the crossover operation. Results on large Lennard-Jones systems with fcc- and hcp-commensurate cells show robust convergence to the bulk structure from a random initial assignment and an ability to successfully discriminate between competing low enthalpy configurations. Results from an ab initio carbon polymorph search show the spontaneous emergence of both Lonsdaleite and graphite-like structures

Improving the convergence of defect calculations in supercells: An ab initio study of the neutral silicon vacancy

We present a systematic methodology for the accurate calculation of defect structures in supercells, which we illustrate with a study of the neutral vacancy in silicon. This is a prototypical defect which has been studied extensively using ab initio methods, yet remarkably there is still no consensus about the energy or structure of this defect, or even whether the nearest-neighbor atoms relax inwards or outwards. In this paper, we show that the differences between previous calculations can be attributed to supercell convergence errors, and we demonstrate how to systematically reduce each such source of error. The various sources of scatter in previous theoretical studies are discussed and a different effect, that of supercell symmetry, is identified. It is shown that a consistent treatment of this effect is crucial in understanding the systematic effects of increasing the supercell size. This work therefore also presents the best converged ab initio study of the neutral silicon vacancy to date

Electron and vibrational spectroscopies using DFT, plane waves and pseudopotentials: CASTEP implementation

Density functional theory can be used to interpret and predict spectroscopic properties of solid-state materials. The relevant computational solutions are usually available in disparate DFT codes, so that it is difficult to use a consistent approach for analyzing various spectroscopic features of a given material. We review the latest developments that are aimed to provide a collection of analytical tools within one DFT package, CASTEP. The applications covered include core-level EELS, solid-state NMR, optical properties, IR and Raman spectroscopy. We present also results of the EELS analysis of NbO and Nb2O5 that show the first published example of CASTEP spectra from d-states. Raman activities calculated for a test set of small molecules and the convergence requirements for such calculations are discussed. (C) 2010 Elsevier B.V. All rights reserved

Front-end process modeling in silicon

Front-end processing mostly deals with technologies associated to junction formation in semiconductor devices. Ion implantation and thermal anneal models are key to predict active dopant placement and activation. We review the main models involved in process simulation, including ion implantation, evolution of point and extended defects, amorphization and regrowth mechanisms, and dopant-defect interactions. Hierarchical simulation schemes, going from fundamental calculations to simplified models, are emphasized in this Colloquium. Although continuum modeling is the mainstream in the semiconductor industry, atomistic techniques are starting to play an important role in process simulation for devices with nanometer size features. We illustrate in some examples the use of atomistic modeling techniques to gain insight and provide clues for process optimization