Tuning the Morphological Structure and Photocatalytic Activity of Nitrogen-Doped (BiO) 2

Various nitrogen-doped hierarchical (BiO)2CO3 nanosheets architectures were synthesized by a facile one-step template-free hydrothermal method through controlling the hydrothermal temperature (HT). The as-synthesized samples were characterized by XRD, SEM, FT-IR, XPS, and UV-vis DRS. The photocatalytic activity of the samples was evaluated towards degradation of NO at ppb level in air under visible light (VIL). It was found that HT acted as a crucial factor in determining the morphology of the samples. The rosa chinensis-like, red camellia-like, and lamina-like of nitrogen-doped (BiO)2CO3 (N-BOC) micro-/nanostructures can be selectively fabricated under hydrothermal temperatures of 150, 180, and 210°C. The thickness of the nanosheets was in direct proportion to the increasing HT. Nitrogen-doping can extend the light absorption spectra of (BiO)3CO3 to visible light region and enhance the VIL photocatalytic activity. Especially, the red camellia-like N-BOC-180 exhibited the highest photocatalytic performance, superior to the well-known VIL-driven photocatalyst C-doped TiO2 and N-doped TiO2. The high photocatalytic performance of N-BOC was attributed to the synergetic effects of enhanced visible light absorption, multiple light-reflections between the nanosheets, and accelerated transfer of reactants and product. This research could provide new insights to the development of excellent photocatalyst with efficient performance for pollution control

Enhanced visible-light photo-oxidation of nitric oxide using bismuth-coupled graphitic carbon nitride composite heterostructures

Pure bismuth (Bi) metal-modified graphitic carbon nitride (g-C3N4) composites (Bi-CN) with a pomegranate-like structure were prepared by an in situ method. The Bi-CN composites were used as photocatalysts for the oxidation of nitric oxide (NO) under visible-light irradiation. The inclusion of pure Bi metal in the g-C3N4 layers markedly improved the light absorption of the Bi-CN composites from the ultraviolet to the near-infrared region because of the typical surface plasmon resonance of Bi metal. The separation and transfer of photogenerated charge carriers were greatly accelerated by the presence of built-in Mott-Schottky effects at the interface between Bi metal and g-C3N4. As a result, the Bi-CN composite photocatalysts exhibited considerably enhanced efficiency in the photocatalytic removal of NO compared with that of Bi metal or g-C3N4 alone. The pomegranate-like structure of the Bi-CN composites and an explanation for their improved photocatalytic activity were proposed. This work not only provides a design for highly efficient g-C3N4-based photocatalysts through modification with Bi metal, but also offers new insights into the mechanistic understanding of g-C3N4-based photocatalysis.(C) 2016, Dalian Institute of Chemical Physics, Chinese Academy of Sciences. Published by Elsevier B.V. All rights reserved

Robust Lidar-Inertial Odometry with Ground Condition Perception and Optimization Algorithm for UGV

Unmanned ground vehicles (UGVs) are making more and more progress in many application scenarios in recent years, such as exploring unknown wild terrain, working in precision agriculture and serving in emergency rescue. Due to the complex ground conditions and changeable surroundings of these unstructured environments, it is challenging for these UGVs to obtain robust and accurate state estimations by using sensor fusion odometry without prior perception and optimization for specific scenarios. In this paper, based on an error-state Kalman filter (ESKF) fusion model, we propose a robust lidar-inertial odometry with a novel ground condition perception and optimization algorithm specifically designed for UGVs. The probability distribution gained from the raw inertial measurement unit (IMU) measurements during a certain time period and the state estimation of ESKF were both utilized to evaluate the flatness of ground conditions in real-time; then, by analyzing the relationship between the current ground condition and the accuracy of the state estimation, the tightly coupled lidar-inertial odometry was dynamically optimized further by adjusting the related parameters of the processing algorithm of the lidar points to obtain robust and accurate ego-motion state estimations of UGVs. The method was validated in various types of environments with changeable ground conditions, and the robustness and accuracy are shown through the consistent accurate state estimation in different ground conditions compared with the state-of-art lidar-inertial odometry systems

Contents of Heavy Metals in Typical Aquatic Products from a Market in Binzhou

To evaluate the levels of heavy metal pollution and risks in consumption of aquatic products from a market in Binzhou, the contents of Cu, Zn, Cd, Cr and Pb in the edible part of eight aquatic species such as Ctenopharyngodon idellus were determined by inductively coupled plasma mass spectrometry. The results show that the levels of the five elements differed among different species of aquatic products. The ability of bivalves to accumulate heavy metals was significantly higher than that of fish. Compared with relevant food hygiene standards, there was a certain excess of Cr in Ruditapes philippinarum and Penaeus vannamei. The results of human exposure risk assessment show that the THQ values of the heavy metals in the eight aquatic species were all less than 1, indicating that the consumption of these aquatic products had no potential non-carcinogenic risks

Dense Dilated Network With Probability Regularized Walk for Vessel Detection

The detection of retinal vessel is of great importance in the diagnosis and treatment of many ocular diseases. Many methods have been proposed for vessel detection. However, most of the algorithms neglect the connectivity of the vessels, which plays an important role in the diagnosis. In this paper, we propose a novel method for retinal vessel detection. The proposed method includes a dense dilated network to get an initial detection of the vessels and a probability regularized walk algorithm to address the fracture issue in the initial detection. The dense dilated network integrates newly proposed dense dilated feature extraction blocks into an encoder-decoder structure to extract and accumulate features at different scales. A multi-scale Dice loss function is adopted to train the network. To improve the connectivity of the segmented vessels, we also introduce a probability regularized walk algorithm to connect the broken vessels. The proposed method has been applied on three public data sets: DRIVE, STARE and CHASE_DB1. The results show that the proposed method outperforms the state-of-the-art methods in accuracy, sensitivity, specificity and also area under receiver operating characteristic curve

Boosting the Photoreactivity of g-C₃N₄ towards CO₂ Reduction by Polymerization of Dicyandiamide in Ammonium Chloride

As a typical organic semiconductor photocatalyst, graphitic carbon nitride (g-C3N4) suffers from low photocatalytic activity. In this paper, g-C3N4 was prepared by polymerization of dicyandiamide (C2H4N4) in the presence of ammonium chloride (NH4Cl). It was found that the addition of ammonium chloride can greatly improve the photocatalytic activity of g-C3N4 towards CO2 reduction. The optimal photocatalyst (CN-Cl 20) exhibited a CO2-to-CO conversion activity of 50.6 μmolg−1h−1, which is 3.1 times that of pristine bulk g-C3N4 (BCN) that was prepared in the absence of any ammonium chloride. The enhanced photoactivity of g-C3N4 was attributed to the combined effects of chloride modification and an enlarged specific surface area. Chloride modification of g-C3N4 can not only reduce the bandgap, but also causes a negatively shifted conduction band (CB) potential level, while ammonia (NH3) gas from the decomposition of NH4Cl can act as a gas template to exfoliate layered structure g-C3N4, improving the specific surface from 6.8 to 21.3 m2g−1. This study provides new ideas for the synthesis of highly efficient g-C3N4-based photocatalytic materials for CO2 conversion and utilization