The effect of the A-site cation on the phase transition temperature of metal halide perovskites
Tom Braeckevelt, Sander Vandenhaute, Sven M. J. Rogge, Johan Hofkens, Veronique Van Speybroeck

TL;DR
This study develops a multistep thermodynamic integration method combined with machine learning potentials to accurately predict phase transition temperatures in metal halide perovskites, addressing challenges posed by organic cation dynamics.
Contribution
The paper introduces a novel thermodynamic integration approach with replica exchange and machine learning potentials for phase stability analysis of MHPs, improving accuracy and efficiency.
Findings
Phase stability mainly depends on ground-state energy differences.
Methodology is applicable to various MHPs for stability prediction.
Temperature dependence of free energy differences is similar across studied materials.
Abstract
A key challenge for the practical application of metal halide perovskites (MHPs) is the instability of the desired perovskite phase relative to the optically non-active phase. To determine the phase stability, we previously developed a procedure to compute the harmonic free energy as a function of temperature, which was suited for CsPbI but fails when Cs is replaced by organic cations due to their rotational freedom. Herein we propose a multistep thermodynamic integration (TI) approach that corrects the harmonic free energy to obtain the Gibbs free energy. Given the abundance of local minima in these materials, we employ replica exchange to prevent simulations from getting trapped, while introducing an intermediate potential energy surface to improve convergence and reduce computational cost. Benchmarking energy and forces from different exchange-correlation functionals and…
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Taxonomy
TopicsPerovskite Materials and Applications · Machine Learning in Materials Science · Heusler alloys: electronic and magnetic properties
