  The atomic scale dynamics of halide perovskites have a direct impact not only
on their thermal stability but their optoelectronic properties. Progress in
machine learned potentials has only recently enabled modeling the finite
temperature behavior of these material using fully atomistic methods with near
first-principles accuracy. Here, we systematically analyze the impact of
heating and cooling rate, simulation size, model uncertainty, and the role of
the underlying exchange-correlation functional on the phase behavior of CsPbX3
with X=Cl, Br, and I, including both the perovskite and the delta-phases. We
show that rates below approximately 30 K/ns and system sizes of at least a few
ten thousand atoms are indicated to achieve convergence with regard to these
parameters. By controlling these factors and constructing models that are
specific for different exchange-correlation functionals we then show that the
semi-local functionals considered in this work (SCAN, vdW-DF-cx, PBEsol, and
PBE) systematically underestimate the transition temperatures separating the
perovskite phases while overestimating the lattice parameters. Among the
considered functionals the vdW-DF-cx functional yields the closest agreement
with experiment, followed by SCAN, PBEsol, and PBE. Our work provides
guidelines for the systematic analysis of dynamics and phase transitions in
inorganic halide perovskites and similar systems. It also serves as a benchmark
for the further development of machine-learned potentials as well as
exchange-correlation functionals.
