Matthew V. Cowley | Searcharxiv

arXiv2026

An Investigation into the Effect of Mobile Ions on the Steady State Performance of Perovskite Solar Cells

In perovskite solar cells, the interplay between mobile ions and photo-excited charge carriers is complex,with recent studies suggesting mobile ions can be either beneficial or detrimental to cell efficiency depending on the cell properties. In this study we use drift diffusion modelling and factorial analysis to simulate 601 pairs of perovskite solar cells (1202 total cells) across a broad range of physically relevant materials parameters. In each pair of devices, one cell contains mobile ions that can move freely. The second paired cell is identical but has no mobile ions. This approach allows us to systematically investigate the impact of mobile ions on cell performance. We deconvolve the contributions of key cell parameters including ion density, recombination rate and band offsets, for n-i-p and p-i-n devices with both organic and inorganic contact layers. Importantly, we find that in efficient devices, mobile ions have only a small impact on steady-state performance.

physics.chem-ph↗

arXiv2023

Bayesian parameter estimation for characterising mobile ion vacancies in perovskite solar cells

To overcome the challenges associated with poor temporal stability of perovskite solar cells, methods are required that allow for fast iteration of fabrication and characterisation, such that optimal device performance and stability may be actively pursued. Currently, establishing the causes of underperformance is both complex and time-consuming, and optimisation of device fabrication thus inherently slow. Here, we present a means of computational device characterisation of mobile halide ion parameters from room temperature current-voltage (J-V) measurements only, requiring $\sim 2$ hours of computation on basic computing resources. With our approach, the physical parameters of the device may be reverse modelled from experimental J-V measurements. In a drift-diffusion model, the set of coupled drift-diffusion partial differential equations cannot be inverted explicitly, so a method for inverting the drift-diffusion simulation is required. We show how Bayesian Parameter Estimation (BPE) coupled with a drift-diffusion perovskite solar cell model can determine the extent to which device parameters affect performance measured by J-V characteristics. Our method is demonstrated by investigating the extent to which device performance is influenced by mobile halide ions for a specific fabricated device. The ion vacancy density $N_0$ and diffusion coefficient $D_I$ were found to be precisely characterised for both simulated and fabricated devices. This result opens up the possibility of pinpointing origins of degradation by finding which parameters most influence device J-V curves as the cell degrades.

cond-mat.mtrl-sci↗