Density functional theory in the solid state

TLDR

Density functional theory has become the most successful computational tool in solid‑state physics, enabling accurate predictions of structural, electronic, optical, and thermodynamic properties across materials science, high‑pressure physics, mineralogy, and solid‑state chemistry. The authors aim to showcase DFT as an exploratory tool for materials discovery, including ex nihilo crystal‑structure prediction from chemical composition alone. They review solid‑state DFT capabilities and illustrate them with recent CASTEP examples.

Abstract

Density functional theory (DFT) has been used in many fields of the physical sciences, but none so successfully as in the solid state. From its origins in condensed matter physics, it has expanded into materials science, high-pressure physics and mineralogy, solid-state chemistry and more, powering entire computational subdisciplines. Modern DFT simulation codes can calculate a vast range of structural, chemical, optical, spectroscopic, elastic, vibrational and thermodynamic phenomena. The ability to predict structure-property relationships has revolutionized experimental fields, such as vibrational and solid-state NMR spectroscopy, where it is the primary method to analyse and interpret experimental spectra. In semiconductor physics, great progress has been made in the electronic structure of bulk and defect states despite the severe challenges presented by the description of excited states. Studies are no longer restricted to known crystallographic structures. DFT is increasingly used as an exploratory tool for materials discovery and computational experiments, culminating in ex nihilo crystal structure prediction, which addresses the long-standing difficult problem of how to predict crystal structure polymorphs from nothing but a specified chemical composition. We present an overview of the capabilities of solid-state DFT simulations in all of these topics, illustrated with recent examples using the CASTEP computer program.