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2018年5月ESI热点论文

    20185我校有4 第一作者单位SCI论文进入ESI 热点论文

30D7A

 

1.   Noble metal-metal oxide nanohybrids with tailored nanostructures for efficient solar energy conversion, photocatalysis and environmental remediation

作者:Liu, XQ (Liu, Xueqin); Iocozzia, J (Iocozzia, James) ; Wang, Y (Wang, Yang) ; Cui, X (Cui, Xun); Chen, YH (Chen, Yihuang); Zhao, SQ (Zhao, Shiqiang) ; Li, Z (Li, Zhen); Lin, ZQ (Lin, Zhiqun)

ENERGY & ENVIRONMENTAL SCIENCE,卷: 10 ,: 2 : 402-434

DOI: 10.1039/c6ee02265k

出版年: FEB 1 2017

摘要:The controlled synthesis of nanohybrids composed of noble metals (Au, Ag, Pt and Pd, as well as AuAg alloy) and metal oxides (ZnO, TiO2, Cu2O and CeO2) have received considerable attention for applications in photocatalysis, solar cells, drug delivery, surface enhanced Raman spectroscopy and many other important areas. The overall architecture of nanocomposites is one of the most important factors dictating the physical properties of nanohybrids. Noble metals can be coupled to metal oxides to yield diversified nanostructures, including noble metal decorated-metal oxide nanoparticles (NPs), nanoarrays, noblemetal/metal oxide core/shell, noble metal/metal oxide yolk/shell and Janus. noblemetal-metal oxide nanostructures. In this review, we focus on the significant advances in tailored nanostructures of noble metal-metal oxide nanohybrids. The improvement in performance in the representative solar energy conversion applications including photocatalytic degradation of organic pollutants, photocatalytic hydrogen generation, photocatalytic CO2 reduction, dye-sensitized solar cells (DSSCs) and perovskite solar cells (PSCs) are discussed. Finally, we conclude with a perspective on the future direction and prospects of these controllable nanohybrid materials

 

2.  Solar radiation prediction using different techniques: model evaluation and comparison

作者:Wang, LC (Wang, Lunche); Kisi, O (Kisi, Ozgur) ; Zounemat-Kermani, M (Zounemat-Kermani, Mohammad); Salazar, GA (Ariel Salazar, German) ; Zhu, ZM (Zhu, Zhongmin); Gong, W (Gong, Wei)

RENEWABLE & SUSTAINABLE ENERGY REVIEWS ,: 61 : 384-397

DOI: 10.1016/j.rser.2016.04.024

出版年: AUG 2016

摘要Daily observations of meteorological parameters, air temperature, air pressure, relative humidity, water vapor pressure and sunshine duration hours observed at 12 stations in different climatic zones during 1961-2014 are reported for testing, validating and comparing different solar radiation models. Three types of Artificial Neural Network (ANN)methods, Multilayer Perceptron (MLP), Generalized Regression Neural Network (GRNN) and Radial Basis Neural Network (RBNN) are applied in this study for predicting the daily global solar radiation (Hg) using above meteorological variables as model inputs. The Bristow Campbell model has also been improved by considering the factors influencing the incoming solar radiation, such as relative humidity, cloud cover, etc. The results indicate that there are large differences in model accuracies for each model at different stations, the ANN models can estimate daily Hg with satisfactory accuracy at most stations in different climate zones, and MLP and RBNN models provide better accuracy than the GRNN and IBC models, for example, the MAE and RMSE values range 1.53-2.29 and 1.94-3.27 MJ m(-2) day(-1), respectively for MLP model. The model performances also show some differences at different stations for each model, for example, the RMSE values from MLP model are 1.94 and 3.27 MJ m(-2) day(-1) at NN and HZ stations, respectively. Meanwhile, ANN models underestimate few high radiation values at some stations, which may due to the differences in training and testing data ranges and distributions of the stations. Finally, the differences in model performances from different solar radiation models have been further analyzed. (C) 2016 Elsevier Ltd. All rights reserved. 

 

3.   Delay-dependent stability analysis of neural networks with time-varying delay: A generalized free-weighting-matrix approach

作者:Zhang, CK (Zhang, Chuan-Ke); He, Y (He, Yong) ; Jiang, L (Jiang, Lin); Lin, WJ (Lin, Wen-Juan) ; Wu, M (Wu, Min)

APPLIED MATHEMATICS AND COMPUTATION, : 294 ,: 102-120

DOI: 10.1016/j.amc.2016.08.043

出版年: FEB 1 2017

摘要This paper investigates the delay-dependent stability problem of continuous neural networks with a bounded time-varying delay via Lyapunov-Krasovskii functional (LKF) method. This paper focuses on reducing the conservatism of stability criteria by estimating the derivative of the LKF more accurately. Firstly, based on several zero-value equalities, a generalized free-weighting-matrix (GFWM) approach is developed for estimating the single integral term. It is also theoretically proved that the GFWM approach is less conservative than the existing methods commonly used for the same task. Then, the GFWM approach is applied to investigate the stability of delayed neural networks, and several stability criteria are derived. Finally, three numerical examples are given to verify the advantages of the proposed criteria. (C) 2016 Elsevier Inc. All rights reserved.

 

4.   Electrical conductivity models in saturated porous media: A review

作者:Cai, JC (Cai, Jianchao) ; Wei, W (Wei, Wei); Hu, XY (Hu, Xiangyun) ; Wood, DA (Wood, David A.)

EARTH-SCIENCE REVIEWS, : 171 ,: 419-433

DOI: 10.1016/j.earscirev.2017.06.013

出版年: AUG 2017

摘要Electrical transport properties of saturated porous media, such as soils, rocks and fractured networks, typically composed of a non-conductive solid matrix and a conductive brine in the pore space, have numerous applications in reservoir engineering and petrophysics. One of the widely used electrical conductivity models is the empirical Archie's law that has a practical application in well-log interpretation of reservoir rocks. The Archie equation does not take into account the contributions of clay minerals, isolated porosity, heterogeneity in grains and pores and their distributions, as well as anisotropy. In the literature, either some modifications were presented to apply Archie's law to tight and clay-rich reservoirs or more modern models were developed to describe electrical conductivity in such reservoirs. In the former, a number of empirically derived parameters were proposed, which typically vary from one reservoir to another. In the latter, theoretical improvements by including detailed characteristics of pore space morphology led to developing more complex electrical conductivity models. Such models enabled us to address the electrical properties in a wider range of potential reservoir rocks through theoretical parameters related to key reservoir-defining petrophysical properties. This paper presents a review of the electrical conductivity models developed using fractal, percolation and effective medium theories. Key results obtained by comparing experiential and theoretical models with experiments/simulations, as well as advantages and drawbacks of each model are analyzed. Approaches to obtaining more reasonable electrical conductivity models are discussed. Experiments suggest more complex relationships between electrical conductivity and porosity than experiential models, particularly in low-porosity formations. However, the available theoretical models combined with simulations do provide insight to how microscale physics affects macroscale electrical conductivity in porous media.