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Lead-halide perovskites have emerged as high-performance photovoltaic materials. We mapped the propagation of photogenerated luminescence and charges from a local photoexcitation spot in thin films of lead tri-iodide perovskites. We observed light emission at distances of ≥50 micrometers and found that the peak of the internal photon spectrum red-shifts from 765 to ≥800 nanometers. We used a lateral-contact solar cell with selective electron- and hole-collecting contacts and observed that charge extraction for photoexcitation >50 micrometers away from the contacts arose from repeated recycling between photons and electron-hole pairs. Thus, energy transport is not limited by diffusive charge transport but can occur over long distances through multiple absorption-diffusion-emission events. This process creates high excitation densities within the perovskite layer and allows high open-circuit voltages.

Thermophotovoltaic power conversion utilizes thermal radiation from a local heat source to generate electricity in a photovoltaic cell. It was shown in recent years that the addition of a highly reflective rear mirror to a solar cell maximizes the extraction of luminescence. This, in turn, boosts the voltage, enabling the creation of record-breaking solar efficiency. Now we report that the rear mirror can be used to create thermophotovoltaic systems with unprecedented high thermophotovoltaic efficiency. This mirror reflects low-energy infrared photons back into the heat source, recovering their energy. Therefore, the rear mirror serves a dual function; boosting the voltage and reusing infrared thermal photons. This allows the possibility of a practical >50% efficient thermophotovoltaic system. Based on this reflective rear mirror concept, we report a thermophotovoltaic efficiency of 29.1 ± 0.4% at an emitter temperature of 1,207 °C.

In lead halide perovskite solar cells, there is at least one recycling event of electron–hole pair to photon to electron–hole pair at open circuit under solar illumination. This can lead to a significant reduction in the external photoluminescence yield from the internal yield. Here we show that, for an internal yield of 70%, we measure external yields as low as 15% in planar films, where light out-coupling is inefficient, but observe values as high as 57% in films on textured substrates that enhance out-coupling. We analyse in detail how externally measured rate constants and photoluminescence efficiencies relate to internal recombination processes under photon recycling. For this, we study the photo-excited carrier dynamics and use a rate equation to relate radiative and non-radiative recombination events to measured photoluminescence efficiencies. We conclude that the use of textured active layers has the ability to improve power conversion efficiencies for both LEDs and solar cells. Recombinations govern losses in solar cells. Here, Richter et al . use transient spectroscopy to evaluate how re-absorption and re-emission of photons in perovskite absorbers affect intrinsic recombination coefficients, and to differentiate between external and internal photoluminescence quantum yields.

Lead-halide perovskites have triggered the latest breakthrough in photovoltaic technology. Despite the great promise shown by these materials, their instability towards water even in the presence of low amounts of moisture makes them, a priori , unsuitable for their direct use as light harvesters in aqueous solution for the production of hydrogen through water splitting. Here, we present a simple method that enables their use in photoelectrocatalytic hydrogen evolution while immersed in an aqueous solution. Field’s metal, a fusible InBiSn alloy, is used to efficiently protect the perovskite from water while simultaneously allowing the photogenerated electrons to reach a Pt hydrogen evolution catalyst. A record photocurrent density of −9.8 mA cm −2 at 0 V versus RHE with an onset potential as positive as 0.95±0.03 V versus RHE is obtained. The photoelectrodes show remarkable stability retaining more than 80% of their initial photocurrent for ∼1 h under continuous illumination. Lead-halide perovskites are sensitive to humidity, which limits their use in water splitting applications. Here, the authors protect the perovskite layer with Field’s metal, driving photoelectrocatalytic hydrogen evolution in an aqueous solution for approximately one hour under constant illumination.

Reducing non-radiative recombination in semiconducting materials is a prerequisite for achieving the highest performance in light-emitting and photovoltaic applications. Here, we characterize both external and internal photoluminescence quantum efficiency and quasi-Fermi-level splitting of surface-treated hybrid perovskite (CH3NH3PbI3) thin films. With respect to the material bandgap, these passivated films exhibit the highest quasi-Fermi-level splitting measured to date, reaching 97.1 ± 0.7% of the radiative limit, approaching that of the highest performing GaAs solar cells. We confirm these values with independent measurements of internal photoluminescence quantum efficiency of 91.9 ± 2.7% under 1 Sun illumination intensity, setting a new benchmark for these materials. These results suggest hybrid perovskite solar cells are inherently capable of further increases in power conversion efficiency if surface passivation can be combined with optimized charge carrier selective interfaces.

The new record efficiency in Thermophotovoltaics relies upon a highly reflective rear mirror. The excellent rear mirror boosts voltage by enhancing the luminescence extraction, and separately also reflects low energy photons, which would otherwise be useless in thermophotovoltaics. The reflected low energy photons reheat the thermal emitter, and regenerate above-bandgap energy photons. The efficiency calibration for such regenerative thermophotovoltaics depends on several factors, yet predominantly on the accurate measurement of the rear mirror reflectivity. Here, we report on the technique for accurate measurement of mirror reflectivity, and of record thermophotovoltaic efficiency 29.1 ± 0.6%, at 1207 °C.

Thermophotovoltaic power conversion utilizes thermal radiation from a local heat source to generate electricity in a photovoltaic cell. It was shown in recent years that the addition of a highly reflective rear mirror to a solar cell maximizes the extraction of luminescence. This, in turn, boosts the voltage, enabling the creation of record-breaking solar efficiency. Now we report that the rear mirror can be used to create thermophotovoltaic systems with unprecedented high thermophotovoltaic efficiency. This mirror reflects low-energy infrared photons back into the heat source, recovering their energy. Therefore, the rear mirror serves a dual function; boosting the voltage and reusing infrared thermal photons. This allows the possibility of a practical >50% efficient thermophotovoltaic system. Based on this reflective rear mirror concept, we report a thermophotovoltaic efficiency of 29.1 ± 0.4% at an emitter temperature of 1,207 °C.

Recent advancements in foundation models have significantly impacted various fields, including natural language processing, computer vision, and multi-modal tasks. One area that stands to benefit greatly is Earth observation, where these models can efficiently process large-scale, unlabeled geospatial data. In this work we extend the SwinMAE model to integrate temporal information for satellite time-series data. The architecture employs a hierarchical 3D Masked Autoencoder (MAE) with Video Swin Transformer blocks to effectively capture multi-scale spatio-temporal dependencies in satellite imagery. To enhance transfer learning, we incorporate both encoder and decoder pretrained weights, along with skip connections to preserve scale-specific information. This forms an architecture similar to SwinUNet with an additional temporal component. Our approach shows significant performance improvements over existing state-of-the-art foundation models for all the evaluated downstream tasks: land cover segmentation, building density prediction, flood mapping, wildfire scar mapping and multi-temporal crop segmentation. Particularly, in the land cover segmentation task of the PhilEO Bench dataset, it outperforms other geospatial foundation models with a 10.4% higher accuracy.