Browsing by Author "Chen, Gang"
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Item Open Access Ag/Ag2O confined visible-light driven catalyst for highly efficient selective hydrogenation of nitroarenes in pure water medium at room temperature(Elsevier, 2020-04-10) Yin, Zhengliang; Xie, Liangxu; Cao, Shunsheng; Xiao, Yingguan; Chen, Gang; Jiang, Ying; Wei, Wenxian; Wu, LiminAlthough photocatalysis has attracted tremendous research interest, there still remains critical challenges (e.g., low visible-light quantum efficiency, organic media, etc.), especially for selective hydrogenation of nitroarenes. Herein, we design and synthesize the first confined photocatalyst by introducing the nanospace of double-shelled hollow silica sphere as a photocatalytic nanoreactor to promote the hydrogenation reaction with the fast reaction kinetics. This photocatalyst exhibits excellent activity, selectivity, and recyclability. Especially, superior selectivity (>99%) is achieved when used for the hydrogenation of nitroarenes under visible-light irradiation in pure water medium. Both experimental and theoretical simulation results indicate that the Ag/Ag2O structure and confined nanospace of the photocatalyst greatly increase the contact probability between photogenerated atomic hydrogen and nitroarenes. Additionally, corresponding anilines are obtained almost quantitatively towards the hydrogenation of nitroarenes in pure water medium at room temperature. Therefore, this work provides a rational design concept of highly efficient visible-light photocatalyst for green chemistry industry.Item Open Access Exploring the coupled ocean and atmosphere system with a data science approach applied to observations from the Antarctic Circumnavigation Expedition(EGU: European Geophysical Union, 2021-11-30) Landwehr, Sebastian; Volpi, Michele; Haumann, F. Alexander; Robinson, Charlotte M.; Thurnherr, Iris; Ferracci, Valerio; Baccarini, Andrea; Thomas, Jenny; Gorodetskaya, Irina; Tatzelt, Christian; Henning, Silvia; Modini, Rob L.; Forrer, Heather J.; Lin, Yajuan; Cassar, Nicolas; Simó, Rafel; Hassler, Christel; Moallemi, Alireza; Fawcett, Sarah E.; Harris, Neil; Airs, Ruth; Derkani, Marzieh H.; Alberello, Alberto; Toffoli, Alessandro; Chen, Gang; Rodríguez-Ros, Pablo; Zamanillo, Marina; Cortés-Greus, Pau; Xue, Lei; Bolas, Conor G.; Leonard, Katherine C.; Perez-Cruz, Fernando; Walton, David; Schmale, JuliaThe Southern Ocean is a critical component of Earth's climate system, but its remoteness makes it challenging to develop a holistic understanding of its processes from the small scale to the large scale. As a result, our knowledge of this vast region remains largely incomplete. The Antarctic Circumnavigation Expedition (ACE, austral summer 2016/2017) surveyed a large number of variables describing the state of the ocean and the atmosphere, the freshwater cycle, atmospheric chemistry, and ocean biogeochemistry and microbiology. This circumpolar cruise included visits to 12 remote islands, the marginal ice zone, and the Antarctic coast. Here, we use 111 of the observed variables to study the latitudinal gradients, seasonality, shorter-term variations, geographic setting of environmental processes, and interactions between them over the duration of 90 d. To reduce the dimensionality and complexity of the dataset and make the relations between variables interpretable we applied an unsupervised machine learning method, the sparse principal component analysis (sPCA), which describes environmental processes through 14 latent variables. To derive a robust statistical perspective on these processes and to estimate the uncertainty in the sPCA decomposition, we have developed a bootstrap approach. Our results provide a proof of concept that sPCA with uncertainty analysis is able to identify temporal patterns from diurnal to seasonal cycles, as well as geographical gradients and “hotspots” of interaction between environmental compartments. While confirming many well known processes, our analysis provides novel insights into the Southern Ocean water cycle (freshwater fluxes), trace gases (interplay between seasonality, sources, and sinks), and microbial communities (nutrient limitation and island mass effects at the largest scale ever reported). More specifically, we identify the important role of the oceanic circulations, frontal zones, and islands in shaping the nutrient availability that controls biological community composition and productivity; the fact that sea ice controls sea water salinity, dampens the wave field, and is associated with increased phytoplankton growth and net community productivity possibly due to iron fertilisation and reduced light limitation; and the clear regional patterns of aerosol characteristics that have emerged, stressing the role of the sea state, atmospheric chemical processing, and source processes near hotspots for the availability of cloud condensation nuclei and hence cloud formation. A set of key variables and their combinations, such as the difference between the air and sea surface temperature, atmospheric pressure, sea surface height, geostrophic currents, upper-ocean layer light intensity, surface wind speed and relative humidity played an important role in our analysis, highlighting the necessity for Earth system models to represent them adequately. In conclusion, our study highlights the use of sPCA to identify key ocean–atmosphere interactions across physical, chemical, and biological processes and their associated spatio-temporal scales. It thereby fills an important gap between simple correlation analyses and complex Earth system models. The sPCA processing code is available as open-access from the following link: https://renkulab.io/gitlab/ACE-ASAID/spca-decomposition (last access: 29 March 2021). As we show here, it can be used for an exploration of environmental data that is less prone to cognitive biases (and confirmation biases in particular) compared to traditional regression analysis that might be affected by the underlying research question.Item Open Access High photocatalytic activity of Cu2O embedded in hierarchically hollow SiO2 for efficient chemoselective hydrogenation of nitroarenes(Springer, 2020-10-20) Yin, Zhengliang; Xiao, Yingguan; Wan, Xiong; Jiang, Ying; Chen, Gang; Shi, Qingye; Cao, ShunshengPhotocatalytic organic conversion is a crucial process in the hydrogenation of nitroarenes, but harsh reaction conditions such as long reaction time, high hydrogen pressure, and organic medium still need to be considerably overcome under visible-light irradiation. Here, we have constructed a transition metal oxide photocatalyst by embedding low-cost Cu2O with strong visible-light absorption into hierarchically hollow SiO2 sphere (SiO2-Cu2O@SiO2) that can suppress the escape of photogenerated atomic hydrogen and promote the contact probability between hydrogen atom and nitroarene molecules due to confinement effect. Remarkably, the SiO2-Cu2O@SiO2 photocatalyst can exhibit efficient chemoselectivity toward the hydrogenation of various nitroarenes in an aqueous system at ambient conditions, successfully working out the requirement of strict hydrogenation conditions, especially for organic medium over almost all of the reported photocatalysts. Notably, quantitative aniline can be produced for the visible-light catalytic reduction of nitroarenes, suggesting a considerable potential for industrial application