Xiamen University

About: Xiamen University is a education organization based out in Amoy, Fujian, China. It is known for research contribution in the topics: Catalysis & Population. The organization has 50472 authors who have published 54480 publications receiving 1058239 citations. The organization is also known as: Amoy University & Xiàmén Dàxué.

Hydrothermal Continuous Flow Synthesis and Exfoliation of NiCo Layered Double Hydroxide Nanosheets for Enhanced Oxygen Evolution Catalysis

Abstract: We report the controlled synthesis of NiCo layered double hydroxide (LDH) nanoplates using a newly developed high temperature high pressure hydrothermal continuous flow reactor (HCFR), which enables direct growth onto conductive substrates in high yield and, most importantly, better control of the precursor supersaturation and, thus, nanostructure morphology and size. The solution coordination chemistry of metal–ammonia complexes was utilized to synthesize well-defined NiCo LDH nanoplates directly in a single step without topochemical oxidation. The as-grown NiCo LDH nanoplates exhibit a high catalytic activity toward the oxygen evolution reaction (OER). By chemically exfoliating LDH nanoplates to thinner nanosheets, the catalytic activity can be further enhanced to yield an electrocatalytic current density of 10 mA cm–2 at an overpotential of 367 mV and a Tafel slope of 40 mV dec–1. Such enhancement could be due to the increased surface area and more exposed active sites. X-ray photoelectron spectroscopy...

Removing Rain from Single Images via a Deep Detail Network

Abstract: We propose a new deep network architecture for removing rain streaks from individual images based on the deep convolutional neural network (CNN). Inspired by the deep residual network (ResNet) that simplifies the learning process by changing the mapping form, we propose a deep detail network to directly reduce the mapping range from input to output, which makes the learning process easier. To further improve the de-rained result, we use a priori image domain knowledge by focusing on high frequency detail during training, which removes background interference and focuses the model on the structure of rain in images. This demonstrates that a deep architecture not only has benefits for high-level vision tasks but also can be used to solve low-level imaging problems. Though we train the network on synthetic data, we find that the learned network generalizes well to real-world test images. Experiments show that the proposed method significantly outperforms state-of-the-art methods on both synthetic and real-world images in terms of both qualitative and quantitative measures. We discuss applications of this structure to denoising and JPEG artifact reduction at the end of the paper.

Synthesis of "clean" and well-dispersive Pd nanoparticles with excellent electrocatalytic property on graphene oxide

Abstract: Ultrafine Pd nanoparticles monodispersed on graphene oxide (GO) surfaces were successfully prepared by the redox reaction between PdCl42− and GO. The as-made catalyst is very “clean” as a result of the surfactant-free formation process, allowing it to express high electrocatalytic ability in formic acid and ethanol oxidation relative to a commercial Pd/C catalyst. This simple and straightforward method is of significance for the facile preparation metal nanocatalysts with high catalytic activity on proper supporting materials.

Core–shell nanoparticles: synthesis and applications in catalysis and electrocatalysis

Abstract: Core–shell nanoparticles (CSNs) are a class of nanostructured materials that have recently received increased attention owing to their interesting properties and broad range of applications in catalysis, biology, materials chemistry and sensors. By rationally tuning the cores as well as the shells of such materials, a range of core–shell nanoparticles can be produced with tailorable properties that can play important roles in various catalytic processes and offer sustainable solutions to current energy problems. Various synthetic methods for preparing different classes of CSNs, including the Stober method, solvothermal method, one-pot synthetic method involving surfactants, etc., are briefly mentioned here. The roles of various classes of CSNs are exemplified for both catalytic and electrocatalytic applications, including oxidation, reduction, coupling reactions, etc.