Antimony-doped tin oxide(ATO) nanoparticles with an average size of ~ 6 nm were prepared by co-precipitation and subsequent heat treatment. Graphitic carbon nitride(g-CN)/ATO hybrid nanocomposite was designed by the combination of thermally synthesized g-CN and ATO nanoparticles by ultrasonication. The materials were characterized using N2 adsorption/desorption(BET), X-ray diffraction(XRD), scanning electron microscopy(SEM), energy dispersive spectroscopy(EDS), transmission electron microscopy(TEM) and Fourier transform infrared spectroscopy(FTIR). A mixture of five volatile organic compounds(VOCs, chloroform, benzene, toluene, xylene and styrene) was used to compare the adsorption capacity of the samples. The adsorption capacity of ATO nanoparticles was improved by the addition of g-CN. Experimental data showed that, among the five VOCs,chloroform was the least adsorbed, regardless of the samples. The g-CN/ATO showed nearly three times greater adsorption capacity for the VOC mixture than pure ATO. The unchanged efficiency of VOC adsorption during cyclic use demonstrated the completely reversible adsorption and desorption behavior of the nanocomposite at room conditions. This economically and environmentally friendly material can be a practical solution for outdoor and indoor VOC removal. 相似文献
Environmental pollution, a major problem worldwide, poses considerable threat to human health and ecological environment. Efficient and reliable detection technologies, which focus on the appearance of emerging environmental and trace pollutants, are urgently needed. Surface-enhanced Raman scattering(SERS) has become an attractive analytical tool for sensing trace targets in environmental field because of its inherent molecular fingerprint specificity and high sensitivity. In this review, we focused on the recent developments in the integration of magnetic nanoparticles(MNPs) with SERS for facilitating sensitive detection of environmental pollutants. An overview and classification of different types of MNPs for SERS detection were initially provided, enabling us to categorize the huge amount of literature that was available in the interdisciplinary research field of MNPs based SERS technology. Then, the basic working principles and applications of MNPs in SERS detection were presented. Subsequently, the detection technologies integrating MNPs with SERS that eventually were used for the detection of various environmental pollutions were reviewed. Finally, the advantages of MNP-basedSERS detection technology for environmental pollutants were concluded, and the current challenges and future outlook of this technology in practical applications were highlighted. The application of the MNPsbasedSERS techniques for environmental analysis will be significantly advanced with the great progresses of the nanotechnologies, optics, and materials. 相似文献
Objectives: The uncertainties of pedestrian mobility are important factors affecting the accuracy and robustness of an active pedestrian protection system. This study is to provide the means for probabilistic risk evaluation of pedestrian–vehicle collision by counting the uncertainties in pedestrian motion.
Method: The pedestrian is modeled by a first-order Markov model to characterize the stochastic properties in mobility according to field experiments of pedestrians crossing an uncontrolled road. Based on the assumption of Gaussian distribution, unscented transformation (UT) is employed to predict the collision risk probability with the symmetric σ-set constructed on the basis of discrete trajectory simulation. Simulation experiments were carried out with 10,000 Monte Carlo (MC) simulations as the reference.
Results: The probability density distributions of time-to-collision, minimal distance, and collision probability estimated by UT coincide with the reference ones under various vehicle–pedestrian conflict scenarios, and the maximal deviation of collision probability from the reference is 5.33%. The UT method is about 600 times faster than the MC method (10,000 runs), which means that the proposed method has the potential for online application.
Conclusions: This article presents an effective and efficient algorithm to estimate the collision probability by using a UT method to solve the nonlinear transformation of uncertainties in pedestrian motion. Simulation results show that the UT-based method achieves accurate collision probability estimation and higher computation efficiency than MC and provides more valuable information concerning collision avoidance than the deterministic methods in the design of a pedestrian collision avoidance system. 相似文献