Akash Dasgupta

Abstract:

Improved understanding of heterojunction interfaces has enabled multijunction photovoltaic devices to achieve power conversion efficiencies that exceed the detailed-balance limit for single-junctions. For wide-bandgap perovskites, however, the pronounced energy loss across the heterojunctions of the active and charge transport layers impedes multijunction devices from reaching their full efficiency potential. Here we find that for polycrystalline perovskite films with mixed-halide compositions, the crystal termination—a factor influencing the reactivity and density of surface sites—plays a crucial role in interfacial passivation for wide-bandgap perovskites. We demonstrate that by templating the growth of polycrystalline perovskite films toward a preferred (100) facet, we can reduce the density of deep-level trap states and enhance the binding of modification ligands. This leads to a much-improved heterojunction interface, resulting in open-circuit voltages of 1.38 V for 1.77-eV single-junction perovskite solar cells. In addition, monolithic all-perovskite double-junction solar cells achieve open-circuit voltage values of up to 2.22 V, with maximum power point tracking efficiencies reaching 28.6% and 27.7% at 0.25 and 1.0 cm2 cell areas, respectively, along with improved operational and thermal stability at 85 °C. This work provides universally applicable insights into the crystalline facet-favourable surface modification of perovskite films, advancing their performance in optoelectronic applications.

Abstract:

Narrow bandgap lead-tin perovskites are essential components of next-generation all-perovskite multi-junction solar cells. However, their poor stability under operating conditions hinders successful implementation. In this work, we systematically investigate the underlying mechanisms of this instability under combined heat and light stress (ISOS L-2 conditions) by measuring changes in phase, conductivity, recombination and current-voltage characteristics. We find an increased impact of the redistribution of mobile ions during device operation to be the primary driver of performance loss during stressing, with further losses caused by a slower increase in non-radiative recombination and background hole density. Crucially, the dominant degradation mode changes with different hole transport materials, which we attribute to variations in iodine vacancy generation rates. By quantifying the impact of these mechanisms on device performance, we provide critical insights for improving the operational stability of lead-tin perovskite solar cells.

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.

Abstract:

Abstract:

All data reported in publication: Impact of precursor dosing on the surface passivation of AZO/AlOx stacks formed using atomic layer deposition