Lattice dynamics of <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"><mml:mrow><mml:msub><mml:mi>Yb</mml:mi><mml:mi>x</mml:mi></mml:msub><mml:msub><mml:mi>Co</mml:mi><mml:mn>4</mml:mn></mml:msub><mml:msub><mml:mi>Sb</mml:mi><mml:mn>12</mml:mn></mml:msub></mml:mrow></mml:math> skutterudite by machine-learning interatomic potentials: Effect of filler concentration and disorder
Pavel Korotaev, Alexander V. Shapeev
Abstract
Lattice dynamics determines a number of important properties of solids. While computational methods with predictive power have been developed in this area, the task is still difficult for the complex compounds. We present a method for automatic on-the-fly generation of multicomponent interatomic potentials. The method is based on active learning, which ensures effective extrapolation to new atomic environments. The accuracy is then demonstrated on the example of the Yb-filled skutterudite compound ${\mathrm{Yb}}_{x}{\mathrm{Co}}_{4}{\mathrm{Sb}}_{12}$, which is a family of the promising thermoelectric materials. Atomic displacements, vibrational spectrum, and lattice thermal conductivity were obtained and the effect of the Yb filling and ordering was studied as 700 K. The potential allowed us to reproduce fine features of the vibrational spectrum, as well as the reduction of the lattice thermal conductivity with filling. We found only a small effect of the disorder on the vibrational spectrum and the thermal conductivity.