Lattice anharmonicity and thermal conductivity from compressive sensing of first-principles calculations

TL;DR

This paper introduces a novel method called compressive sensing lattice dynamics (CSLD) that accurately predicts lattice thermal conductivity in strongly anharmonic crystals using first-principles calculations and quasi-random atomic configurations.

Contribution

The paper presents a systematic approach using compressive sensing to identify key terms in lattice dynamics models from first-principles data, improving accuracy for anharmonic materials.

Findings

Accurately predicts thermal conductivity of Si, NaCl, and Cu12Sb4S13.

Demonstrates effectiveness in materials with strong phonon interactions.

Achieves near-amorphous limit thermal conductivity predictions.

Abstract

First-principles prediction of lattice thermal conductivity $\kappa_L$ of strongly anharmonic crystals is a long-standing challenge in solid state physics. Making use of recent advances in information science, we propose a systematic and rigorous approach to this problem, compressive sensing lattice dynamics (CSLD). Compressive sensing is used to select the physically important terms in the lattice dynamics model and determine their values in one shot. Non-intuitively, high accuracy is achieved when the model is trained on first-principles forces in {\it quasi-random\/} atomic configurations. The method is demonstrated for Si, NaCl, and Cu$_{12}$Sb$_4$S$_{13}$, an earth-abundant thermoelectric with strong phonon-phonon interactions that limit the room-temperature $\kappa_L$ to values near the amorphous limit.