Abstract
We present an implementation in a linear-scaling density-functional theory code of an electronic enthalpy method, which has been found to be natural and efficient for the ab initio calculation of finite systems under hydrostatic pressure. Based on a definition of the system volume as that enclosed within an electronic density isosurface [M. Cococcioni, F. Mauri, G. Ceder, and N. Marzari, Phys. Rev. Lett. 94, 145501 (2005)], it supports both geometry optimizations and molecular dynamics simulations. We introduce an approach for calibrating the parameters defining the volume in the context of geometry optimizations and discuss their significance. Results in good agreement with simulations using explicit solvents are obtained, validating our approach. Size-dependent pressure-induced structural transformations and variations in the energy gap of hydrogenated silicon nanocrystals are investigated, including one comparable in size to recent experiments. A detailed analysis of the polyamorphic transformations reveals three types of amorphous structures and their persistence on depressurization is assessed.
Highlights
While empirical potentials are good for modelling a variety of materials, the complex bonding rearrangements associated with structural transformations of materials such as covalent semiconductors mean that ab initio methods such as density-functional theory (DFT) are essential to capture the details of the structure and dynamics with accuracy
We turn our attention to structural transformations in the Si nanocrystals Si35H36 and Si71H60, which have been studied by other methods
We have applied this method to the structural transformations of hydrogenated Si nanocrystals of different sizes and obtained results in good agreement with simulations using explicit solvents
Summary
While empirical potentials are good for modelling a variety of materials, the complex bonding rearrangements associated with structural transformations of materials such as covalent semiconductors mean that ab initio methods such as density-functional theory (DFT) are essential to capture the details of the structure and dynamics with accuracy. The large length- and time-scales associated with the structural transformations of experimentally relevant systems pose a significant computational challenge. The O(N 3) scaling of the computational effort in traditional methods such as the plane-wave pseudopotential (PWPP) formulation of DFT limits the number of atoms N that can be simulated to a few hundred and thereby seriously constrains the attainable sizes of nanocrystals. This can be addressed by working with a linear-scaling DFT code such as ONETEP, for which the favorable balance of cost and accuracy allows the investigation of nanocrystals with many thousands of atoms..
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