Impact of precursor dosing on the surface passivation of AZO/AlOx stacks formed using atomic layer deposition
Energy Advances Royal Society of Chemistry 4 (2025) 553-564
Abstract:
High-efficiency solar cell architectures, including silicon heterojunction (SHJ) and perovskite/silicon tandems, rely heavily on the unique properties of transparent conducting oxides (TCOs). The push towards terawatt-scale PV manufacturing means it is increasingly desirable to develop indium-free TCOs to facilitate the upscaled manufacturing of high-efficiency cell designs. Aluminium-doped ZnO (AZO) deposited by atomic layer deposition (ALD) has emerged as a promising candidate due to its combination of optical transparency and electrical conductivity. In addition, AZO has also been shown to passivate the c-Si surface. The ability for one material to provide all three properties without requiring any indium is advantageous in single junction and tandem solar devices. Herein, we demonstrate exceptional silicon surface passivation using AZO/AlOx stacks deposited with ALD, with a J0 < 1 fA cm−2 and corresponding implied open circuit voltage (iVOC) of 740 mV. We provide a comprehensive analysis of the role of ALD precursor dosing to achieve optimised performance. A broad range of characterisation approaches were used to probe the structural, compositional, and chemical properties of AZO films. These indicated that the passivation properties are governed by a delicate interplay between the Zn and Al concentrations in the film, highlighting the importance of precise process control. Optical modelling in a single junction SHJ architecture indicates these AZO films are close in performance to high-mobility indium-containing TCOs. The insights provided by this work may help to further the case of indium-free TCOs, which is critical for upscaled production of high-efficiency solar cells.Determining material parameters of metal halide perovskites using time-resolved photoluminescence
PRX Energy American Physical Society 4:1 (2025) 013001
Abstract:
In this work we demonstrate that time-resolved photoluminescence data of metal halide perovskites can be effectively evaluated by combining Bayesian inference with a Markov-Chain Monte-Carlo algorithm and a physical model. This approach enables us to infer a high number of parameters which govern the performance of metal halide perovskite-based devices, alongside the probability distributions of those parameters, as well as correlations among all parameters. Via studying a set of "half-stacks’‘, comprising electron and hole transport materials contacting perovskite thin-films, we determine surface recombination velocities at these interfaces with high precision. From the probability distributions of all inferred parameters, we can simulate intensity-dependent photoluminescence quantum efficiency and compare it to the experimental data. Finally, we estimate mobility values for the "vertical’’ charge carrier transport, that perpendicular to the plane of the substrate, for all samples using our approach. Since this mobility estimation is derived from charge carrier diffusion over the length-scale of the film thickness and in the vertical direction, it is highly relevant to transport in photovoltaic and light emitting devices. Our approach of coupling spectroscopic measurements with advanced, computational analysis will help speed up scientific research in the field of optoelectronic materials and devices and exemplifies how carefully constructed computational algorithms can derive valuable plurality of information from simple datasets. We expect that our approach will be expandable to a variety of other analysis techniques and that our method will be applicable to other semiconductors.Determining parameters of metal-halide perovskites using photoluminescence with Bayesian inference
PRX Energy American Physical Society 4:1 (2025) 13001
Abstract:
In this work, we demonstrate that time-resolved photoluminescence data of metal halide perovskites can be effectively evaluated by combining Bayesian inference with a Markov-chain Monte-Carlo algorithm and a physical model. This approach enables us to infer a high number of parameters that govern the performance of metal halide perovskite-based devices, alongside the probability distributions of those parameters, as well as correlations among all parameters. Via studying a set of halfstacks, comprising electron- and hole-transport materials contacting perovskite thin films, we determine surface recombination velocities at these interfaces with high precision. From the probability distributions of all inferred parameters, we can simulate intensity-dependent photoluminescence quantum efficiency and compare it to experimental data. Finally, we estimate mobility values for vertical charge-carrier transport, which is perpendicular to the plane of the substrate, for all samples using our approach. Since this mobility estimation is derived from charge-carrier diffusion over the length scale of the film thickness and in the vertical direction, it is highly relevant for transport in photovoltaic and light-emitting devices. Our approach of coupling spectroscopic measurements with advanced computational analysis will help speed up scientific research in the field of optoelectronic materials and devices and exemplifies how carefully constructed computational algorithms can derive valuable plurality of information from simple datasets. We expect that our approach can be expanded to a variety of other analysis techniques and that our method will be applicable to other semiconductors.
Data in support of Impact of precursor dosing on the surface passivation of AZO/AlOx stacks formed using atomic layer deposition
University of Oxford (2025)
Abstract:
All data reported in publication: Impact of precursor dosing on the surface passivation of AZO/AlOx stacks formed using atomic layer depositionSteering perovskite precursor solutions for multijunction photovoltaics
Nature Nature Research (2024)