Approaching the radiative limits for wide bandgap perovskite solar cells using fullerene blend electron transport interlayers †
EES Solar Royal Society of Chemistry (2025)
Abstract:
Performance losses in positive–intrinsic–negative architecture perovskite solar cells are dominated by nonradiative recombination at the perovskite/organic electron transport layer interface, which is particularly problematic for wider bandgap perovskites. Large endeavours have been dedicated to the replacement of fullerenes, which are the most commonly used class of electron transport layers, with limited success thus far. In this work, we demonstrate blending the fullerene derivatives [6,6]-phenyl C61 butyric acid methyl ester (PCBM) and indene-C60 bis-adduct (ICBA) as a thin interlayer between 1.77 eV bandgap perovskite and an evaporated C60 layer. By tuning the fullerene blend to a trace 2% by mass of PCBM in ICBA, we remarkably form an interlayer which features improved energetic alignment with the perovskite and the PCBM : ICBA fullerene mixture, together with a stronger molecular ordering and an order of magnitude higher electron mobility than either neat PCBM or ICBA. Additional molecular surface passivation approaches are found to be beneficial in conjunction with this approach, resulting in devices with 19.5% steady state efficiency, a fill factor of 0.85 and an open-circuit voltage of 1.33 V, which is within 10% of the radiative limit of the latter two device parameters for this bandgap. This work highlights the complex nonlinear energetic behaviour with fullerene mixing, and how control of the energetics and crystallinity of these materials is crucial in overcoming the detrimental recombination losses that have historically limited perovskite solar cells.Present status of and future opportunities for all-perovskite tandem photovoltaics
Nature Energy Springer Nature (2025) 1-16
Determining Parameters of Metal-Halide Perovskites Using Photoluminescence with Bayesian Inference
PRX Energy American Physical Society (APS) 4:1 (2025) 13001
Abstract:
<jats:p>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.</jats:p> <jats:sec> <jats:title/> <jats:supplementary-material> <jats:permissions> <jats:copyright-statement>Published by the American Physical Society</jats:copyright-statement> <jats:copyright-year>2025</jats:copyright-year> </jats:permissions> </jats:supplementary-material> </jats:sec>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.Steering perovskite precursor solutions for multijunction photovoltaics
Nature Nature Research (2024)