3D-to-2D Transition of Anion Vacancy Mobility in CsPbBr3 under Hydrostatic Pressure
Thijs Smolders a, Alison Walker a, Matthew Wolf a
a University of Bath, Department of Physics, Claverton Down, Bath BA2 7AY, United Kingdom
International Conference on Hybrid and Organic Photovoltaics
Proceedings of 13th Conference on Hybrid and Organic Photovoltaics (HOPV21)
Online, Spain, 2021 May 24th - 28th
Organizers: Marina Freitag, Feng Gao and Sam Stranks
Invited Speaker Session, Thijs Smolders, presentation 088
Publication date: 11th May 2021

Unlike typical inorganic semiconductors, lead-halide perovskites (LHPs) exhibit significant ionic conductivity, which is believed to affect their performance and stability. Motivated by a recent experimental study that suggested pressure as a means to control ionic conductivity in CsPbBr3 [1], we present a detailed theoretical analysis of the atomic scale effects of pressure on anion migration in the low-temperature orthorhombic Pnma phase of CsPbBr3 [2]. Using density functional theory, we compute the transition state structures and activation enthalpies and entropies associated with anion vacancy hopping between nearby lattice sites. We use those data to parametrise a kinetic model for anion vacancy migration, which takes into account the non-trivial topology of the Pnma anion sublattice, and solve it to determine the mobility tensor as a function of applied pressure.

As the pressure is increased, we find that the mobility tends to become increasingly anisotropic, such that at 2.0 GPa the mobility in the [010] direction is three orders of magnitude lower than the mobility in the (010) plane to which it is normal. This can be explained by the fact that a network of only a small subset of possible hops dominates the mobility at elevated pressures, leading to a strongly anisotropic response of the mobility tensor to increasing pressure. Our results demonstrate the potential importance of pressure in controlling both the rate and direction of anion migration in LHPs.

We acknowledge funding from the European Union’s Horizon 2020 MSCA Innovative Training Network under grant agreement number 764787, and the Energy Oriented Centre of Excellence (EoCoE-II), grant agreement number 676629. This research made use of the Balena High Performance Computing (HPC) Service at the University of Bath; and the Isambard UK National Tier-2 HPC Service (http://gw4.ac.uk/isambard/) operated by GW4 and the UK Meteorological Office, and funded by EPSRC (EP/P020224/1). We thank Dr. I. R. Thompson and Dr. W. R. Saunders for discussions pertaining to kinetic modelling, and Dr. T. Duchon, Dr. J. Kullgren, Prof. R. A. De Souza and the anonymous reviewers for their constructive criticism of the manuscript.

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