Concepedia

TLDR

DFT has become a cornerstone of computational materials science, enabling interpretation of experimental data, prediction of material properties, and design of new materials. This article reviews plane‑wave pseudopotential DFT methods for large periodic systems and discusses future improvements in accuracy and scalability. The review highlights algorithmic implementations such as ultrasoft pseudopotentials, efficient iterative solvers, and parallelized plane‑wave codes. The methods are illustrated by predicting crystal structures, studying mineral compressibility, and modeling pressure‑induced phase transitions. © 2000 John Wiley & Sons, Inc., Int J Quant Chem 77: 895–910.

Abstract

Recent developments in density functional theory (DFT) methods applicable to studies of large periodic systems are outlined. During the past three decades, DFT has become an essential part of computational materials science, addressing problems in materials design and processing. The theory allows us to interpret experimental data and to generate property data (such as binding energies of molecules on surfaces) for known materials, and also serves as an aid in the search for and design of novel materials and processes. A number of algorithmic implementations are currently being used, including ultrasoft pseudopotentials, efficient iterative schemes for solving the one-electron DFT equations, and computationally efficient codes for massively parallel computers. The first part of this article provides an overview of plane-wave pseudopotential DFT methods. Their capabilities are subsequently illustrated by examples including the prediction of crystal structures, the study of the compressibility of minerals, and applications to pressure-induced phase transitions. Future theoretical and computational developments are expected to lead to improved accuracy and to treatment of larger systems with a higher computational efficiency. © 2000 John Wiley & Sons, Inc. Int J Quant Chem 77: 895–910, 2000

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