Tracing Ion Migration in Halide Perovskites with Machine Learned Force Fields

• Main Authors: Tyagi, Viren, Pols, Mike, Brocks, Geert, Tao, Shuxia
• Format: Journal Article
• Language: English
• Published: 24-09-2024
• Subjects: Physics - Materials Science
• DOI: 10.48550/arxiv.2409.16051

Halide perovskite optoelectronic devices suffer from chemical degradation and
current-voltage hysteresis induced by migration of highly mobile charged
defects. Atomic scale molecular dynamics simulations can capture the motion of
these ionic defects, but classical force fields are too inflexible to describe
their dynamical charge states. Using CsPbI3 as a case study, we develop machine
learned force fields from density functional theory calculations and study the
diffusion of charged halide interstitial and vacancy defects in bulk CsPbI3. We
find that negative iodide interstitials and positive iodide vacancies, the most
stable charge states for their respective defect type, migrate at similar rates
at room temperature. Neutral interstitials are faster, but neutral vacancies
are one order of magnitude slower. Oppositely charged interstitials and
vacancies, as they can occur in device operation or reverse bias conditions,
are significantly slower and can be considered relatively immobile.