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DDC: 333.7 × Publisher: London : Nature Publishing Group ×

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    Perovskite phase heterojunction solar cells
    (London : Nature Publishing Group, 2022) Ji, Ran; Zhang, Zongbao; Hofstetter, Yvonne J.; Buschbeck, Robin; Hänisch, Christian; Paulus, Fabian; Vaynzof, Yana
    Modern photovoltaic devices are often based on a heterojunction structure where two components with different optoelectronic properties are interfaced. The properties of each side of the junction can be tuned by either utilizing different materials (for example, donor/acceptor) or doping (for example, p–n junction) or even varying their dimensionality (for example, 3D/2D). Here we demonstrate the concept of phase heterojunction (PHJ) solar cells by utilizing two polymorphs of the same material. We demonstrate the approach by forming γ-CsPbI3/β-CsPbI3 perovskite PHJ solar cells. We find that all of the photovoltaic parameters of the PHJ device significantly surpass those of each of the single-phase devices, resulting in a maximum power conversion efficiency of 20.1%. These improvements originate from the efficient passivation of the β-CsPbI3 by the larger bandgap γ-CsPbI3, the increase in the built-in potential of the PHJ devices enabled by the energetic alignment between the two phases and the enhanced absorption of light by the PHJ structure. The approach demonstrated here offers new possibilities for the development of photovoltaic devices based on polymorphic materials.
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    Future tree survival in European forests depends on understorey tree diversity
    (London : Nature Publishing Group, 2022) Billing, Maik; Thonicke, Kirsten; Sakschewski, Boris; Bloh, Werner von; Walz, Ariane
    Climate change heavily threatens forest ecosystems worldwide and there is urgent need to understand what controls tree survival and forests stability. There is evidence that biodiversity can enhance ecosystem stability (Loreau and de Mazancourt in Ecol Lett 16:106–115, 2013; McCann in Nature 405:228–233, 2000), however it remains largely unclear whether this also holds for climate change and what aspects of biodiversity might be most important. Here we apply machine learning to outputs of a flexible-trait Dynamic Global Vegetation Model to unravel the effects of enhanced functional tree trait diversity and its sub-components on climate-change resistance of temperate forests (http://www.pik-potsdam.de/~billing/video/Forest_Resistance_LPJmLFIT.mp4). We find that functional tree trait diversity enhances forest resistance. We explain this with 1. stronger complementarity effects (~ 25% importance) especially improving the survival of trees in the understorey of up to + 16.8% (± 1.6%) and 2. environmental and competitive filtering of trees better adapted to future climate (40–87% importance). We conclude that forests containing functionally diverse trees better resist and adapt to future conditions. In this context, we especially highlight the role of functionally diverse understorey trees as they provide the fundament for better survival of young trees and filtering of resistant tree individuals in the future.