Prussian blue (PB)
and its analogues (PBAs) are drawing attention
as promising materials for sodium-ion batteries and other applications,
such as desalination of water. Because of the possibilities to explore
many analogous materials with engineered, defect-rich environments,
computational optimization of ion-transport mechanisms that are key
to the device performance could facilitate real-world applications.
In this work, we have applied a multiscale approach involving quantum
chemistry, self-consistent mean-field theory, and finite-element modeling
to investigate ion transport in PBAs. We identify a cyanide-mediated
ladder mechanism as the primary process of ion transport. Defects
are found to be impermissible to diffusion, and a random distribution
model accurately predicts the impact of defect concentrations. Notably,
the inclusion of intermediary local minima in the models is key for
predicting a realistic diffusion constant. Furthermore, the intermediary
landscape is found to be an essential difference between both the
intercalating species and the type of cation doping in PBAs. We also
show that the ladder mechanism, when employed in multiscale computations,
properly predicts the macroscopic charging performance based on atomistic
results. In conclusion, the findings in this work may suggest the
guiding principles for the design of new and effective PBAs for different
applications.
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