The synthesis of hollow opening polyhedral cages has always been an attractive but challenging goal, especially with regard to inorganic polyhedral cages. Herein, we present a novel, 240-nuclearity giant polymolybdate cage prepared via hydrothermal synthesis. This cage is composed of 20 tripod-shaped [Mo6O22(SO3)] n−/[Mo6O21(SO4)] n− building blocks with three connected vertices and 30 cubane-type [Mo4O16] n− edge building blocks, featuring a rare, nearly regular pentagonal dodecahedron with a large inner cavity (diameter up to 1.8 nm) and 12 opening pentagonal windows. This is the highest nuclearity hollow opening dodecahedral cage reported to date. Importantly, this cage exhibits good stability in solution, as revealed by scanning transmission electron microscopy (STEM), TEM, UV–vis, and Raman spectra. In addition, the bulk sample of this compound exhibits an ultrahigh proton conductivity of 1.03 × 10–1 S cm–1 at 80 °C and 98% relative humidity, which is the highest among polyoxometalate-based crystalline proton conductors.

Land surface temperature (LST) plays a critical role in the water cycle and energy balance at global and regional scales. Large-scale LST estimates can be obtained from satellite observations and reanalysis data. In this study, we first investigate the long-term changes of LST during 2003–2017 on a per-pixel basis using three different datasets derived from (i) the Atmospheric Infrared Sounder (AIRS) onboard Aqua satellite, (ii) the Moderate Resolution Imaging Spectroradiometer (MODIS) also aboard Aqua, and (iii) the recently released ERA5-Land reanalysis data. It was found that the spatio-temporal patterns of these data agree very well. All three products globally showed an uptrend in the annual average LST during 2003–2017 but with considerable spatial variations. The strongest increase was found over the region north of 45° N, particularly over Asian Russia, whereas a slight decrease was observed over Australia. The regression analysis indicated that precipitation (P), incoming surface solar radiation (SW↓), and incoming surface longwave radiation (LW↓) can together explain the inter-annual LST variations over most regions, except over tropical forests, where the inter-annual LST variation is low. Spatially, the LST changes during 2003–2017 over the region north of 45° N were mainly influenced by LW↓, while P and SW↓ played a more important role over other regions. A detailed look at Asian Russia and the Amazon rainforest at a monthly time scale showed that warming in Asian Russia is dominated by LST increases in February–April, which are closely related with the simultaneously increasing LW↓ and clouds. Over the southern Amazon, the most apparent LST increase is found in the dry season (August–September), primarily affected by decreasing P. In addition, increasing SW↓ associated with decreasing atmospheric aerosols was another factor found to cause LST increases. This study shows a high level of consistency among LST trends derived from satellite and reanalysis products, thus providing more robust characteristics of the spatio-temporal LST changes during 2003–2017. Furthermore, the major climatic drivers of LST changes during 2003–2017 were identified over different regions, which might help us predict the LST in response to changing climate in the future.

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