Wuhan University

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

Microwave-assisted hydrothermal synthesis of graphene based Au–TiO2 photocatalysts for efficient visible-light hydrogen production

Abstract: The construction and application of visible-light-driven photocatalysts falls in the central focus for the efficient utilization of renewable solar energy, which provides unprecedented opportunities for addressing the increasing concerns on energy and environmental sustainability. Herein, graphene based Au–TiO2 photocatalysts were fabricated by a simple, one-step microwave-assisted hydrothermal method, using Degussa P25 TiO2 powder (P25), graphene oxide and HAuCl4 aqueous solution as the raw materials. The effects of graphene introduction and gold loading on the photocatalytic hydrogen production rates of the as-prepared samples in a methanolic aqueous solution were investigated. The results indicated that Au–TiO2–graphene composite had a significantly increased visible light absorption and enhanced photocatalytic H2-production activity compared to the Au–TiO2 composite. In comparison, the pure TiO2, graphene–TiO2 and graphene–Au had no appreciable visible-light-driven H2 production. The enhanced photocatalytic H2-production activity of the Au–TiO2–graphene composite is ascribed to (1) the load of the Au nanoparticles which broadens the visible light response of TiO2 due to the surface plasmon resonance (SPR) effect, and (2) the introduction of graphene, which functions as rapid electron transfer units, facilitating the space separation of photoelectron and hole pairs. The proposed H2-production activity enhancement mechanism was further confirmed by the transient photocurrent response and electrochemical impedance spectroscopy (EIS) experiments.

Electrocatalytic destruction of the antibiotic tetracycline in aqueous medium by electrochemical advanced oxidation processes: Effect of electrode materials

Abstract: a b s t r a c t This paper presents the removal of the antibiotic tetracycline (TeC) from water using electrochemi- cal advanced oxidation processes (EAOPs); namely electrochemical oxidation (EO) and electro-Fenton (EF). The effect of different cathode materials (carbon-felt and stainless steel) on the direct/indirect electro-oxidation of tetracycline, and that of different anode materials (Ti/RuO2-IrO2, Pt and BDD) on both processes was systematically investigated for the first time. The EO process was found to be more efficient in using the carbon-felt cathode than the stainless steel cathode. The EO and the EF processes using BDD anode demonstrated superior oxidation/mineralization power. Almost total mineralization (TOC removal up to 98%) of 100 mg L−1 TeC solutions was achieved after 6 h treatment either by EO and/or EF treatment with BDD anode. The oxidative degradation of TeC followed pseudo-first-order- reaction kinetics in using all tested electrodes and anode/cathode configurations. Apparent rate constants of different anode/cathode configurations increased in the following sequence: Ti/RuO2-IrO2/stainless steel < Ti/RuO2-IrO2/carbon-felt < BDD/carbon-felt (EO) < BDD/carbon-felt (EF). The electrical energy con- sumed per gram of TOC removal was calculated for different electrode configurations to assess the cost effectiveness of the EO and the EF processes to mineralize TeC in water. © 2013 Elsevier B.V. All rights reserved.

Text-Attentional Convolutional Neural Network for Scene Text Detection

Abstract: Recent deep learning models have demonstrated strong capabilities for classifying text and non-text components in natural images. They extract a high-level feature globally computed from a whole image component (patch), where the cluttered background information may dominate true text features in the deep representation. This leads to less discriminative power and poorer robustness. In this paper, we present a new system for scene text detection by proposing a novel text-attentional convolutional neural network (Text-CNN) that particularly focuses on extracting text-related regions and features from the image components. We develop a new learning mechanism to train the Text-CNN with multi-level and rich supervised information, including text region mask, character label, and binary text/non-text information. The rich supervision information enables the Text-CNN with a strong capability for discriminating ambiguous texts, and also increases its robustness against complicated background components. The training process is formulated as a multi-task learning problem, where low-level supervised information greatly facilitates the main task of text/non-text classification. In addition, a powerful low-level detector called contrast-enhancement maximally stable extremal regions (MSERs) is developed, which extends the widely used MSERs by enhancing intensity contrast between text patterns and background. This allows it to detect highly challenging text patterns, resulting in a higher recall. Our approach achieved promising results on the ICDAR 2013 data set, with an F-measure of 0.82, substantially improving the state-of-the-art results.

Highly efficient luminescence from space-confined charge-transfer emitters.

Abstract: Charge-transfer (CT) complexes, formed by electron transfer from a donor to an acceptor, play a crucial role in organic semiconductors. Excited-state CT complexes, termed exciplexes, harness both singlet and triplet excitons for light emission, and are thus useful for organic light-emitting diodes (OLEDs). However, present exciplex emitters often suffer from low photoluminescence quantum efficiencies (PLQEs), due to limited control over the relative orientation, electronic coupling and non-radiative recombination channels of the donor and acceptor subunits. Here, we use a rigid linker to control the spacing and relative orientation of the donor and acceptor subunits, as demonstrated with a series of intramolecular exciplex emitters based on 10-phenyl-9,10-dihydroacridine and 2,4,6-triphenyl-1,3,5-triazine. Sky-blue OLEDs employing one of these emitters achieve an external quantum efficiency (EQE) of 27.4% at 67 cd m−2 with only minor efficiency roll-off (EQE = 24.4%) at a higher luminous intensity of 1,000 cd m−2. As a control experiment, devices using chemically and structurally related but less rigid emitters reach substantially lower EQEs. These design rules are transferrable to other donor/acceptor combinations, which will allow further tuning of emission colour and other key optoelectronic properties. The use of rigid linkers to control the relative position and interaction of donor and acceptor units in exciplex emitters leads to the realization of organic light-emitting devices with enhanced external quantum efficiency.