Stefan Maintz

Analytic projection from plane-wave and PAW wavefunctions and application to chemical-bonding analysis in solids

Quantum‐chemical computations of solids benefit enormously from numerically efficient plane‐wave (PW) basis sets, and together with the projector augmented‐wave (PAW) method, the latter have risen to one of the predominant standards in computational solid‐state sciences. Despite their advantages, plane waves lack local information, which makes the interpretation of local densities‐of‐states (DOS) difficult and precludes the direct use of atom‐resolved chemical bonding indicators such as the crystal orbital overlap population (COOP) and the crystal orbital Hamilton population (COHP) techniques. Recently, a number of methods have been proposed to overcome this fundamental issue, built around the concept of basis‐set projection onto a local auxiliary basis. In this work, we propose a novel computational technique toward this goal by transferring the PW/PAW wavefunctions to a properly chosen local basis using analytically derived expressions. In particular, we describe a general approach to project both PW and PAW eigenstates onto given custom orbitals, which we then exemplify at the hand of contracted multiple‐ζ Slater‐type orbitals. The validity of the method presented here is illustrated by applications to chemical textbook examples—diamond, gallium arsenide, the transition‐metal titanium—as well as nanoscale allotropes of carbon: a nanotube and the C60 fullerene. Remarkably, the analytical approach not only recovers the total and projected electronic DOS with a high degree of confidence, but it also yields a realistic chemical‐bonding picture in the framework of the projected COHP method.

LOBSTER: A tool to extract chemical bonding from plane-wave based DFT

The computer program LOBSTER (Local Orbital Basis Suite Towards Electronic‐Structure Reconstruction) enables chemical‐bonding analysis based on periodic plane‐wave (PAW) density‐functional theory (DFT) output and is applicable to a wide range of first‐principles simulations in solid‐state and materials chemistry. LOBSTER incorporates analytic projection routines described previously in this very journal [J. Comput. Chem. 2013, 34, 2557] and offers improved functionality. It calculates, among others, atom‐projected densities of states (pDOS), projected crystal orbital Hamilton population (pCOHP) curves, and the recently introduced bond‐weighted distribution function (BWDF). The software is offered free‐of‐charge for non‐commercial research.

Speeding up plane-wave electronic-structure calculations using graphics-processing units

Abstract We report on a source-code modification of the density-functional program suite VASP which benefits from the use of graphics-processing units (GPUs). For the electronic minimization needed to achieve the ground state using an implementation of the blocked Davidson iteration scheme (EDDAV), speed-ups of up to 3.39 on S1070 devices or 6.97 on a C2050 device were observed when calculating an ion–conductor system of actual research interest. Concerning the GPU specialty – memory throughput – the low double-precision performance forms the bottleneck on the S1070, whereas on Fermi cards the code reaches 61.7% efficiency while not suffering from any accuracy losses compared to well-established calculations performed on a central processing unit (CPU). The algorithmic bottleneck was found to be the multiplication of rectangular matrices. An initial idea to solve this problem is given.

Unexpected Ge–Ge Contacts in the Two-Dimensional Ge4Se3Te Phase and Analysis of Their Chemical Cause with the Density of Energy (DOE) Function

A hexagonal phase in the ternary Ge-Se-Te system with an approximate composition of GeSe0.75 Te0.25 has been known since the 1960s but its structure has remained unknown. We have succeeded in growing single crystals by chemical transport as a prerequisite to solve and refine the Ge4 Se3 Te structure. It consists of layers that are held together by van der Waals type weak chalcogenide-chalcogenide interactions but also display unexpected Ge-Ge contacts, as confirmed by electron microscopy analysis. The nature of the electronic structure of Ge4 Se3 Te was characterized by chemical bonding analysis, in particular by the newly introduced density of energy (DOE) function. The Ge-Ge bonding interactions serve to hold electrons that would otherwise go into antibonding Ge-Te contacts.

Automated first‐principles mapping for phase‐change materials

Plotting materials on bi‐coordinate maps according to physically meaningful descriptors has a successful tradition in computational solid‐state science spanning more than four decades. Equipped with new ab initio techniques introduced in this work, we generate an improved version of the treasure map for phase‐change materials (PCMs) as introduced previously by Lencer et al. which, other than before, charts all industrially used PCMs correctly. Furthermore, we suggest seven new PCM candidates, namely SiSb4Te7, Si2Sb2Te5, SiAs2Te4, PbAs2Te4, SiSb2Te4, Sn2As2Te5, and PbAs4Te7, to be used as synthetic targets. To realize aforementioned maps based on orbital mixing (or “hybridization”) and ionicity coordinates, structural information was first included into an ab initio numerical descriptor for sp3 orbital mixing and then generalized beyond high‐symmetry structures. In addition, a simple, yet powerful quantum‐mechanical ionization measure also including structural information was introduced. Taken together, these tools allow for (automatically) generating materials maps solely relying on first‐principles calculations.

cuVASP: A GPU-Accelerated Plane-Wave Electronic-Structure Code

We report about a source-code modification of the density-functional program suite VASP which greatly benefits from the use of graphics-processing units (GPUs). The blocked Davidson iteration scheme (EDDAV) has been optimized for GPUs and gains speed-ups of up to 3.39 on S1070 devices and of 6.97 on a C2050 device. Using the Fermi card, the code reaches an impressive 61.7% efficiency but does not suffer from any accuracy losses. The algorithmic bottleneck lies in the multiplication of rectangular matrices. We also give some initial thoughts about introducing a different level of parallelism in order to harness the computational power of multi-GPU installations.