Wuhan University

About: Wuhan University is a education organization based out in Wuhan, China. It is known for research contribution in the topics: Computer science & Population. The organization has 92849 authors who have published 92882 publications receiving 1691049 citations. The organization is also known as: WHU & Wuhan College.

Size Dependence of Gas Sensitivity of ZnO Nanorods

Abstract: We report the structure, optical, and gas-sensing properties of ZnO nanorods with different diameters. Vertically well-aligned homogeneous nanorods were grown along the c-axis orientation. The shift of Raman scattering E2 (high) mode and photoluminescence (PL) spectra were used to study the dependences of nanorod diameters on the stress and oxygen vacancy. Gas sensors were prepared and tested for the detection of C2H5OH and H2S (100 ppm) in air. It was found that the thin nanorods have a significantly better sensing performance than the thick nanorods. We provide a possible explanation from the aspect of the sensing mechanism of the surface reaction process.

Hierarchical Carbon Framework Wrapped Na3V2(PO4)3 as a Superior High‐Rate and Extended Lifespan Cathode for Sodium‐Ion Batteries

Abstract: Hierarchical carbon framework wrapped Na3 V2 (PO4 )3 (HCF-NVP) is successfully synthesized through chemical vapor deposition on pure Na3 V2 (PO4 )3 particles. Electrochemical experiments show that the HCF-NVP electrode can deliver a large reversible capacity (115 mA h g(-1) at 0.2 C), superior high-rate rate capability (38 mA h g(-1) at 500 C), and ultra-long cycling stability (54% capacity retention after 20 000 cycles).

Photocatalytic reduction of CO2 into hydrocarbon solar fuels over g-C3N4–Pt nanocomposite photocatalysts

Abstract: Photocatalytic reduction of CO2 into renewable hydrocarbon fuels is an alternative way to develop reproducible energy, which is also a promising way to solve the problem of the greenhouse effect. In this work, graphitic carbon nitride (g-C3N4) was synthesized by directly heating thiourea at 550 °C and then a certain amount of Pt was deposited on it to form g-C3N4–Pt nanocomposites used as catalysts for photocatalytic reduction of CO2 under simulated solar irradiation. The main products of photocatalysis were CH4, CH3OH and HCHO. The deposited Pt acted as an effective cocatalyst, which not only influenced the selectivity of the product generation, but also affected the activity of the reaction. The yield of CH4 first increased upon increasing the amount of Pt deposited on the g-C3N4 from 0 to 1 wt%, then decreased at 2 wt% Pt loading. The production rates of CH3OH and HCHO also increased with the content of Pt increasing from 0 to 0.75 wt% and the maximum yield was observed at 0.75 wt%. The Pt nanoparticles (NPs) could facilitate the transfer and enrichment of photogenerated electrons from g-C3N4 to its surface for photocatalytic reduction of CO2. At the same time, Pt was also used a catalyst to promote the oxidation of products. The transient photocurrent response further confirmed the proposed photocatalytic reduction mechanism of CO2. This work indicates that the deposition of Pt is a good strategy to improve the photoactivity and selectivity of g-C3N4 for CO2 reduction.

Locality Preserving Matching

Abstract: Seeking reliable correspondences between two feature sets is a fundamental and important task in computer vision. This paper attempts to remove mismatches from given putative image feature correspondences. To achieve the goal, an efficient approach, termed as locality preserving matching (LPM), is designed, the principle of which is to maintain the local neighborhood structures of those potential true matches. We formulate the problem into a mathematical model, and derive a closed-form solution with linearithmic time and linear space complexities. Our method can accomplish the mismatch removal from thousands of putative correspondences in only a few milliseconds. To demonstrate the generality of our strategy for handling image matching problems, extensive experiments on various real image pairs for general feature matching, as well as for point set registration, visual homing and near-duplicate image retrieval are conducted. Compared with other state-of-the-art alternatives, our LPM achieves better or favorably competitive performance in accuracy while intensively cutting time cost by more than two orders of magnitude.

Optimization of mesoporous carbon structures for lithium–sulfur battery applications

Abstract: Mesoporous carbon (MC) with tunable pore sizes (22 nm, 12 nm, 7 nm, and 3 nm) and pore volumes (from 1.3 to 4.8 cm3 g−1) containing sulfur in the pores was studied as a mesoporous carbon–sulfur (MCS) composite electrode for lithium–sulfur (Li–S) batteries. Systematic investigation of these MCS composites reveals that MC with a larger pore volume can hold a higher maximum sulfur loading, but overall the battery performance is very similar for different MCS composites at full sulfur-filling conditions (i.e., the condition at which the sulfur loading approaches the maximum limit set by the pore volume of the individual MC and, therefore, the pores of each MC are fully filled by sulfur). For the same MC, partial sulfur-filling (i.e., the condition at which the sulfur loading is lower than the maximum limit and, therefore, the pores are only partially filled with sulfur) leads to an improved initial discharge capacity and cycle stability, probably because of improved electrical and ionic transport during electrochemical reactions. Based on this understanding, an MCS composite electrode using MC with a large pore volume, partial sulfur filling, and a novel surface modification was designed for Li–S batteries. An initial capacity of ∼1390 mA h g−1 (based on sulfur) and a capacity retention of ∼840 mA h g−1 over 100 cycles at a 0.1 C rate were obtained using MC (22 nm, 4.8 cm3 g−1) with 50 wt% sulfur loading and a commercially available Clevios P (poly(3,4-ethylenedioxythiophene)poly(styrenesulfonate) (PEDT/PSS)) coating.