Machine-learned force fields predict that methylammonium suppresses the beta-to-gamma transition in mixed lead-halide perovskites unless the organic cations rearrange, while formamidinium stabilizes a cubic low-temperature phase with a+a+a+ tilts.
Dynamic Nanodomains Dictate Macroscopic Properties in Lead Halide Perovskites
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abstract
Empirical A-site cation substitution has advanced the stability and efficiency of hybrid organic-inorganic lead halide perovskites solar cells and the functionality of X-ray detectors. Yet, the fundamental mechanisms underpinning their unique performance remain elusive. This multi-modal study unveils the link between nanoscale structural dynamics and macroscopic optoelectronic properties in these materials by utilising X-ray diffuse scattering, inelastic neutron spectroscopy and optical microscopy complemented by state-of-the-art machine learning-assisted molecular dynamics simulations. Our approach uncovers the presence of dynamic, lower-symmetry local nanodomains embedded within the higher-symmetry average phase in various perovskite compositions. The properties of these nanodomains are tunable via the A-site cation selection: methylammonium induces a high density of anisotropic, planar nanodomains of out-of-phase octahedral tilts, while formamidinium favours sparsely distributed isotropic, spherical nanodomains with in-phase tilting, even when crystallography reveals cubic symmetry on average. The observed variations in the properties of dynamic nanodomains are in agreement with our simulations and are directly linked to the differing macroscopic optoelectronic and ferroelastic behaviours of these compositions. By demonstrating the influence of A-site cation on local nanodomains and consequently, on macroscopic properties, we propose leveraging this relationship to engineer the optoelectronic response of these materials, propelling further advancements in perovskite-based photovoltaics, optoelectronics, and X-ray imaging.
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Phase Stability and Transformations in Lead Mixed Halide Perovskites from Machine Learning Force Fields
Machine-learned force fields predict that methylammonium suppresses the beta-to-gamma transition in mixed lead-halide perovskites unless the organic cations rearrange, while formamidinium stabilizes a cubic low-temperature phase with a+a+a+ tilts.