Accurate ionic forces and geometry optimisation in linear scaling density-functional theory with local orbitals

TL;DR

This paper introduces an improved linear-scaling DFT method using localised orbitals and psinc basis functions, achieving accurate ionic forces and geometry optimisations for complex systems.

Contribution

The work demonstrates that using psinc functions and on-the-fly orbital optimisation in local-orbital DFT yields smooth energy surfaces and accurate forces, enabling reliable geometry optimisations.

Findings

Smooth potential energy surfaces achieved

Accurate ionic forces consistent with Hellmann-Feynman theorem

Successful geometry optimisation for diverse systems

Abstract

Linear scaling methods for density-functional theory (DFT) simulations are formulated in terms of localised orbitals in real-space, rather than the delocalised eigenstates of conventional approaches. In local-orbital methods, relative to conventional DFT, desirable properties can be lost to some extent, such as the translational invariance of the total energy of a system with respect to small displacements and the smoothness of the potential energy surface. This has repercussions for calculating accurate ionic forces and geometries. In this work we present results from \textsc{onetep}, our linear scaling method based on localised orbitals in real-space. The use of psinc functions for the underlying basis set and on-the-fly optimisation of the localised orbitals results in smooth potential energy surfaces that are consistent with ionic forces calculated using the Hellmann-Feynman theorem. This enables accurate geometry optimisation to be performed. Results for surface reconstructions in silicon are presented, along with three example systems demonstrating the performance of a quasi-Newton geometry optimisation algorithm: an organic zwitterion, a point defect in an ionic crystal, and a semiconductor nanostructure.