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Photovoltaics (PVs) are a critical technology for curbing growing levels of anthropogenic greenhouse gas emissions, and meeting increases in future demand for low-carbon electricity. In order to fulfil ambitions for net-zero carbon dioxide equivalent (CO2eq) emissions worldwide, the global cumulative capacity of solar PVs must increase by an order of magnitude from 0.9 TWp in 2021 to 8.5 TWp by 2050 according to the International Renewable Energy Agency, which is considered to be a highly conservative estimate. In 2020, the Henry Royce Institute brought together the UK PV community to discuss the critical technological and infrastructure challenges that need to be overcome to address the vast challenges in accelerating PV deployment. Herein, we examine the key developments in the global community, especially the progress made in the field since this earlier roadmap, bringing together experts primarily from the UK across the breadth of the photovoltaics community. The focus is both on the challenges in improving the efficiency, stability and levelized cost of electricity of current technologies for utility-scale PVs, as well as the fundamental questions in novel technologies that can have a significant impact on emerging markets, such as indoor PVs, space PVs, and agrivoltaics. We discuss challenges in advanced metrology and computational tools, as well as the growing synergies between PVs and solar fuels, and offer a perspective on the environmental sustainability of the PV industry. Through this roadmap, we emphasize promising pathways forward in both the short- and long-term, and for communities working on technologies across a range of maturity levels to learn from each other., Comment: 160 pages, 21 figures

Semiconducting polycrystalline thin films are cheap to produce and can be deposited on flexible substrates, yet high-performance electronic devices usually utilize single-crystal semiconductors, owing to their superior electrical mobilities and longer diffusion lengths. Here we show that the electrical performance of polycrystalline films of metal-halide perovskites (MHPs) approaches that of single crystals at room temperature. Combining temperature-dependent terahertz conductivity measurements and ab initio calculations we uncover a complete picture of the origins of charge scattering in single crystals and polycrystalline films of CH$_3$NH$_3$PbI$_3$. We show that Fr\"ohlich scattering of charge carriers with multiple phonon modes is the dominant mechanism limiting mobility, with grain-boundary scattering further reducing mobility in polycrystalline films. We reconcile the large discrepancy in charge diffusion lengths between single crystals and films by considering photon reabsorption. Thus, polycrystalline films of MHPs offer great promise for devices beyond solar cells, including transistors and modulators., Comment: 33 pages, 4 figures (including the toc figure)

Building robust deep learning-based models requires large quantities of diverse training data. In this study, we investigate the use of federated learning (FL) to build medical imaging classification models in a real-world collaborative setting. Seven clinical institutions from across the world joined this FL effort to train a model for breast density classification based on Breast Imaging, Reporting & Data System (BI-RADS). We show that despite substantial differences among the datasets from all sites (mammography system, class distribution, and data set size) and without centralizing data, we can successfully train AI models in federation. The results show that models trained using FL perform 6.3% on average better than their counterparts trained on an institute's local data alone. Furthermore, we show a 45.8% relative improvement in the models' generalizability when evaluated on the other participating sites' testing data., Comment: Accepted at the 1st MICCAI Workshop on "Distributed And Collaborative Learning"; add citation to Fig. 1 & 2 and update Fig. 5; fix typo in affiliations

Many optoelectronic properties have been reported for lead halide perovskite polycrystalline films. However, ambiguities in the evaluation of these properties remain, especially for long-range lateral charge transport, where ionic conduction can complicate interpretation of data. Here we demonstrate a new technique to measure the long-range charge carrier mobility in such materials. We combine quasi-steady-state photo-conductivity measurements (electrical probe) with photo-induced transmission and reflection measurements (optical probe) to simultaneously evaluate the conductivity and charge carrier density. With this knowledge we determine the lateral mobility to be ~ 2 cm2/Vs for CH3NH3PbI3 (MAPbI3) polycrystalline perovskite films prepared from the acetonitrile/methylamine solvent system. Furthermore, we present significant differences in long-range charge carrier mobilities, from 2.2 to 0.2 cm2/Vs, between films of contemporary perovskite compositions prepared via different fabrication processes, including solution and vapour phase deposition techniques. Arguably, our work provides the first accurate evaluation of the long-range lateral charge carrier mobility in lead halide perovskite films, with charge carrier density in the range typically achieved under photovoltaic operation.

We demonstrate four and two-terminal perovskite-perovskite tandem solar cells with ideally matched bandgaps. We develop an infrared absorbing 1.2eV bandgap perovskite, $FA_{0.75}Cs_{0.25}Sn_{0.5}Pb_{0.5}I_3$, that can deliver 14.8 % efficiency. By combining this material with a wider bandgap $FA_{0.83}Cs_{0.17}Pb(I_{0.5}Br_{0.5})_3$ material, we reach monolithic two terminal tandem efficiencies of 17.0 % with over 1.65 volts open-circuit voltage. We also make mechanically stacked four terminal tandem cells and obtain 20.3 % efficiency. Crucially, we find that our infrared absorbing perovskite cells exhibit excellent thermal and atmospheric stability, unprecedented for Sn based perovskites. This device architecture and materials set will enable 'all perovskite' thin film solar cells to reach the highest efficiencies in the long term at the lowest costs.