Arash A. Mostofi

Introducing ONETEP: Linear-scaling density functional simulations on parallel computers

We present ONETEP (order-N electronic total energy package), a density functional program for parallel computers whose computational cost scales linearly with the number of atoms and the number of processors. ONETEP is based on our reformulation of the plane wave pseudopotential method which exploits the electronic localization that is inherent in systems with a nonvanishing band gap. We summarize the theoretical developments that enable the direct optimization of strictly localized quantities expressed in terms of a delocalized plane wave basis. These same localized quantities lead us to a physical way of dividing the computational effort among many processors to allow calculations to be performed efficiently on parallel supercomputers. We show with examples that ONETEP achieves excellent speedups with increasing numbers of processors and confirm that the time taken by ONETEP as a function of increasing number of atoms for a given number of processors is indeed linear. What distinguishes our approach is that the localization is achieved in a controlled and mathematically consistent manner so that ONETEP obtains the same accuracy as conventional cubic-scaling plane wave approaches and offers fast and stable convergence. We expect that calculations with ONETEP have the potential to provide quantitative theoretical predictions for problems involving thousands of atoms such as those often encountered in nanoscience and biophysics.

Nonorthogonal generalized Wannier function pseudopotential plane-wave method

We present a reformulation of the plane-wave pseudopotential method for insulators. This new approach allows us to perform density-functional calculations by solving directly for “nonorthogonal generalized Wannier functions” rather than extended Bloch states. We outline the theory on which our method is based and present test calculations on a variety of systems. Comparison of our results with a standard plane-wave code shows that they are equivalent. Apart from the usual advantages of the plane-wave approach such as the applicability to any lattice symmetry and the high accuracy, our method also benefits from the localization properties of our functions in real space. The localization of all our functions greatly facilitates the future extension of our method to linear-scaling schemes or calculations of the electric polarization of crystalline insulators.

Preconditioned iterative minimization for linear-scaling electronic structure calculations

Linear-scaling electronic structure methods are essential for calculations on large systems. Some of these approaches use a systematic basis set, the completeness of which may be tuned with an adjustable parameter similar to the energy cut-off of plane-wave techniques. The search for the electronic ground state in such methods suffers from an ill-conditioning which is related to the kinetic contribution to the total energy and which results in unacceptably slow convergence. We present a general preconditioning scheme to overcome this ill-conditioning and implement it within our own first-principles linear-scaling density functional theory method. The scheme may be applied in either real space or reciprocal space with equal success. The rate of convergence is improved by an order of magnitude and is found to be almost independent of the size of the basis.

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

Linear scaling methods for density-functional theory (DFT) simulations are formulated in terms of localized orbitals in real space, rather than the delocalized 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 onetep, our linear scaling method based on localized orbitals in real space. The use of psinc functions for the underlying basis set and on-the-fly optimization of the localized orbitals results in smooth potential-energy surfaces that are consistent with ionic forces calculated using the Hellmann-Feynman theorem. This enables accurate geometry optimization to be performed. Results for surface reconstructions in silicon are presented, along with three example systems demonstrating the performance of a quasi-Newton geometry optimization algorithm: an organic zwitterion, a point defect in an ionic crystal, and a semiconductor nanostructure.

Total-energy calculations on a real space grid with localized functions and a plane-wave basis

We present a novel real space formalism for ab initio electronic structure calculations. We use localized non-orthogonal functions that are expressed in terms of a basis set that is equivalent to a plane-wave basis. As a result, advantages of the plane-wave approach also apply to our method: its applicability to any lattice symmetry, and systematic basis set improvement via the kinetic energy cut-off parameter. The localization of our functions enables the use of fast Fourier transforms over small regions of the simulation cell to calculate the total energy with efficiency and accuracy. With just one further variational approximation, namely the truncation of the density matrix, the calculation may be performed with a cost that scales linearly with system size for insulating systems.

Minimal parameter implicit solvent model for ab initio electronic-structure calculations

We present an implicit solvent model for ab initio electronic-structure calculations which is fully self-consistent and is based on direct solution of the nonhomogeneous Poisson equation. The solute cavity is naturally defined in terms of an isosurface of the electronic density according to the formula of Fattebert and Gygi (J. Comput. Chem., 23 (2002) 662). While this model depends on only two parameters, we demonstrate that by using appropriate boundary conditions and dispersion-repulsion contributions, solvation energies obtained for an extensive test set including neutral and charged molecules show dramatic improvement compared to existing models. Our approach is implemented in, but not restricted to, a linear-scaling density functional theory (DFT) framework, opening the path for self-consistent implicit solvent DFT calculations on systems of unprecedented size, which we demonstrate with calculations on a 2615-atom protein-ligand complex.

Dimensionality of carbon nanomaterials determines the binding and dynamics of amyloidogenic peptides: multiscale theoretical simulations

Experimental studies have demonstrated that nanoparticles can affect the rate of protein self-assembly, possibly interfering with the development of protein misfolding diseases such as Alzheimers, Parkinsons and prion disease caused by aggregation and fibril formation of amyloid-prone proteins. We employ classical molecular dynamics simulations and large-scale density functional theory calculations to investigate the effects of nanomaterials on the structure, dynamics and binding of an amyloidogenic peptide apoC-II(60-70). We show that the binding affinity of this peptide to carbonaceous nanomaterials such as C60, nanotubes and graphene decreases with increasing nanoparticle curvature. Strong binding is facilitated by the large contact area available for π-stacking between the aromatic residues of the peptide and the extended surfaces of graphene and the nanotube. The highly curved fullerene surface exhibits reduced efficiency for π-stacking but promotes increased peptide dynamics. We postulate that the increase in conformational dynamics of the amyloid peptide can be unfavorable for the formation of fibril competent structures. In contrast, extended fibril forming peptide conformations are promoted by the nanotube and graphene surfaces which can provide a template for fibril-growth.

Accurate kinetic energy evaluation in electronic structure calculations with localized functions on real space grids

We present a method for calculating the kinetic energy of localized functions represented on a regular real space grid. This method uses fast Fourier transforms applied to restricted regions commensurate with the simulation cell and is applicable to grids of any symmetry. In the limit of large systems it scales linearly with system size. Comparison with the finite difference approach shows that our method offers significant improvements in accuracy without loss of efficiency.

Subspace representations inab initiomethods for strongly correlated systems

We present a generalized definition of subspace occupancy matrices in ab initio methods for strongly correlated materials, such as DFT+U and DFT+DMFT, which is appropriate to the case of nonorthogonal projector functions. By enforcing the tensorial consistency of all matrix operations, we are led to a subspace projection operator for which the occupancy matrix is tensorial and accumulates only contributions which are local to the correlated subspace at hand. For DFT+U in particular, the resulting contributions to the potential and ionic forces are automatically Hermitian, without resort to symmetrization, and localized to their corresponding correlated subspace. The tensorial invariance of the occupancies, energies and ionic forces is preserved. We illustrate the effect of this formalism in a DFT+U study using self-consistently determined projectors.

Density kernel optimization in the ONETEP code

ONETEP is a linear scaling code for performing first-principles total energy calculations within density-functional theory (DFT). The method is based on the density-matrix formulation of DFT and involves the iterative minimization of the total energy with respect to a set of local orbitals and a density kernel. An overview is given of the kernel optimization methods proposed in the literature and implemented in ONETEP, focusing in particular on the constraints of compatibility, idempotency and normalization that must be applied. A method is proposed for locating the chemical potential which may be useful in applying the normalization constraint and analysing the electronic structure near the Fermi level.