Nankai University

About: Nankai University is a education organization based out in Tianjin, China. It is known for research contribution in the topics: Catalysis & Enantioselective synthesis. The organization has 42964 authors who have published 51866 publications receiving 1127896 citations. The organization is also known as: Nánkāi Dàxué.

Biomimetic enzyme nanocomplexes and their use as antidotes and preventive measures for alcohol intoxication

Abstract: Organisms have sophisticated subcellular compartments containing enzymes that function in tandem These confined compartments ensure effective chemical transformation and transport of molecules, and the elimination of toxic metabolic wastes Creating functional enzyme complexes that are confined in a similar way remains challenging Here we show that two or more enzymes with complementary functions can be assembled and encapsulated within a thin polymer shell to form enzyme nanocomplexes These nanocomplexes exhibit improved catalytic efficiency and enhanced stability when compared with free enzymes Furthermore, the co-localized enzymes display complementary functions, whereby toxic intermediates generated by one enzyme can be promptly eliminated by another enzyme We show that nanocomplexes containing alcohol oxidase and catalase could reduce blood alcohol levels in intoxicated mice, offering an alternative antidote and prophylactic for alcohol intoxication

JL-DCF: Joint Learning and Densely-Cooperative Fusion Framework for RGB-D Salient Object Detection

Abstract: This paper proposes a novel joint learning and densely-cooperative fusion (JL-DCF) architecture for RGB-D salient object detection. Existing models usually treat RGB and depth as independent information and design separate networks for feature extraction from each. Such schemes can easily be constrained by a limited amount of training data or over-reliance on an elaborately-designed training process. In contrast, our JL-DCF learns from both RGB and depth inputs through a Siamese network. To this end, we propose two effective components: joint learning (JL), and densely-cooperative fusion (DCF). The JL module provides robust saliency feature learning, while the latter is introduced for complementary feature discovery. Comprehensive experiments on four popular metrics show that the designed framework yields a robust RGB-D saliency detector with good generalization. As a result, JL-DCF significantly advances the top-1 D3Net model by an average of ~1.9% (S-measure) across six challenging datasets, showing that the proposed framework offers a potential solution for real-world applications and could provide more insight into the cross-modality complementarity task. The code will be available at https://github.com/kerenfu/JLDCF/.

Recent Progress in the Electrolytes of Aqueous Zinc-Ion Batteries

Abstract: Rechargeable aqueous zinc-ion batteries (ZIBs) have garnered tremendous attention in the field of next energy storage devices due to their high safety, low cost, abundant resources, and eco-friendliness. As an important component of the zinc-ion battery, the electrolyte plays a vital role in the electrochemical properties, since it will provide a pathway for the migrations of the zinc ions between the cathode and anode, and determine the ionic conductivity, electrochemically stable potential window, and reaction mechanism. In this Minireview, a brief introduction of electrochemical principles of the aqueous ZIBs is discussed and the recent advances of various aqueous electrolytes for ZIBs, including liquid, gel, and multifunctional hydrogel electrolytes are also summarized. Furthermore, the remaining challenges and future directions of electrolytes in aqueous ZIBs are also discussed, which could provide clues for the following development.

A stable compound of helium and sodium at high pressure

Abstract: Helium is generally understood to be chemically inert and this is due to its extremely stable closed-shell electronic configuration, zero electron affinity and an unsurpassed ionization potential. It is not known to form thermodynamically stable compounds, except a few inclusion compounds. Here, using the ab initio evolutionary algorithm USPEX and subsequent high-pressure synthesis in a diamond anvil cell, we report the discovery of a thermodynamically stable compound of helium and sodium, Na2He, which has a fluorite-type structure and is stable at pressures >113 GPa. We show that the presence of He atoms causes strong electron localization and makes this material insulating. This phase is an electride, with electron pairs localized in interstices, forming eight-centre two-electron bonds within empty Na8 cubes. We also predict the existence of Na2HeO with a similar structure at pressures above 15 GPa.