Design of Ti4+-doped Li3V2(PO4)3/C fibers for lithium energy storage

In this work, we propose a facile approach to fabricate Ti⁴⁺-doped Li₃V₂(PO₄)₃/C (abbreviated as C-LVTP) nanofibers using an electrospinning route followed by a high temperature treatment. In this designed nanocomposite, the ultrafine LVTP dots are homogeneously dispersed into one-dimensional carbon nanofibers and the Ti⁴⁺ doping does not destroy the crystal structure of monoclinic Li₃V₂(PO₄)₃. Compared to the undoped Li₃V₂(PO₄)₃/C (abbreviated as C-LVP), the as-fabricated C-LVTP fibers present higher reversible capacity, superior high-rate capability as well as better cyclic property. Especially, the C-LVT_7%P cathode delivers not only high capacities of 187.2 and 160.3 mAh g^?1 at 0.5 and 10 C respectively, but also stable cyclic property with the reversible capacity of 135.8 mAh g^?1 at 20 C following 500-cycle spans. The good battery characteristics of C-LVT_7%P can be mainly ascribed to Ti⁴⁺ doping, which can increase the electrical conductivity and Li⁺ diffusion coefficient.     

Multi-innovation auto-constructed least squares identification for 4 DOF ship manoeuvring modelling with full-scale trial data

This research is concerned with the problem of 4 degrees of freedom (DOF) ship manoeuvring identification modelling with the full-scale trial data. To avoid the multi-innovation matrix inversion in the conventional multi-innovation least squares (MILS) algorithm, a new transformed multi-innovation least squares (TMILS) algorithm is first developed by virtue of the coupling identification concept. And much effort is made to guarantee the uniformly ultimate convergence. Furthermore, the auto-constructed TMILS scheme is derived for the ship manoeuvring motion identification by combination with a statistic index. Comparing with the existing results, the proposed scheme has the significant computational advantage and is able to estimate the model structure. The illustrative examples demonstrate the effectiveness of the proposed algorithm, especially including the identification application with full-scale trial data.     

Protein hydrolysates from animal processing by-products as a source of bioactive molecules with interest in animal feeding: A review

Industrial processing of livestock, poultry and fish produces a large amount of waste in a solid or liquid form that can either be destroyed or be used to make compost, biogas or other low-added value products. However, the by-products from animal processing industries have a potential for conversion into useful products of higher value, such as protein hydrolysates, with interesting applications in animal feed. Low amounts of animal protein hydrolysates included in aqua-feeds may enhance growth rate and feed conversion of farmed fish and crustacean. Animal protein hydrolysates may also be incorporated in diets to enhance the nonspecific immunity of fish. As well, these hydrolysates can be used as a good source of amino acids for newly weaned animals. Protein hydrolysates from animal by-products including antimicrobials, antioxidants, opioid-like and/or other interesting bioactive molecules have promising and interesting applications on companion and production animals. By-products from animal processing industries are therefore a promising source of bioactive peptides of considerable interest for animal care, always within the framework of the existing legislation. Possible drawbacks and future trends of the use of animal by-products and/or production of protein hydrolysates from those materials are also discussed.     

Influence of the ZrB2 content on the anti-oxidation ability of ZrB2-SiC coatings in aerobic environments with broad temperature range

ZrB₂-SiC coatings with different ZrB₂ contents were prepared by liquid phase sintering. The oxidation processes of coatings were explained according to TG results of ZrB₂-SiC coatings and powders tested from 298 K to 1773 K. Results show that, increasing ZrB₂ content made the weight of the samples changed from weight-loss of 10.04% to weight-gain of 0.14%, while the fastest weight-loss regions were narrowed, whose inflection points reduced from 1310℃ to 1050℃. Increasing ZrB₂ content made the relative oxygen permeability of the ZrB₂-SiC/SiC coatings reduced from 40%–60% to -10%-5%. Increasing ZrB₂ content enhanced high-temperature stability of coatings, making final weight of samples changed from weight-loss of 0.16% to weight-gain of 0.11% after oxidation at 1773 K for 200 h. The peeling and dispersion of Zr-oxides formed Zr-B-Si-O compound glass layer, presenting enhanced stability, dispersion strengthening and pinning effect of Zr-oxides, which were responsible for the excellent anti-oxidation protective effect of coatings in a broad temperature region.     

Adaptive Neural Network Finite-Time Control for Uncertain Robotic Manipulators

An adaptive neural network finite-time controller (NNFTC) for a class of uncertain nonlinear systems is proposed by using the backstepping method, which employs an adaptive neural network (NN) system to approximate the structure uncertainties and uses a variable structure term to compensate the approximation errors, thus improving the robustness of the system to external disturbances. The controller is then applied to uncertain robotic manipulators, with a control objective of driving the system state to the original equilibrium point. It is proved that the closed-loop system is finite-time stable. Moreover, simulated and experimental results indicate that the proposed NNFTC is effective and robust.     

Efficient synthesis of benzophenone derivatives in Lewis acid ionic liquids

Benzophenone and its derivatives were prepared via Friedel–Crafts acylation reactions using ionic liquids (ILs) of BmimCl–FeCl₃, BmimCl–AlCl₃ and BmimCl–ZnCl₂ as dual catalyst–solvent. Among them, BmimCl–FeCl₃ showed much higher catalytic activity than that observed for the other two ILs, and in conventional organic solvents. In these reaction systems, good to excellent yields (up to 97%) of acylation products were obtained in a short reaction time. This method features high yield, a simple product isolation procedure, ILs reusability and reduced waste discharge, thus rendering this catalytic system both efficient and environmentally friendly.     

WSN中基于线性规划的多类别目标覆盖算法

多类别目标覆盖问题是目前无线传感器网络中的研究热点。针对现有目标覆盖算法在时间效率、网络生命周期等方面的不足,将多类别目标覆盖问题建模为基于线性规划的网络生命周期最大化问题,提出一种基于分簇的目标覆盖算法。该算法依据节点的剩余能量和感应能力,在每个簇结构内求解最优覆盖集的基础上得到接近于最优解的全局覆盖集,进而调度节点相应的感应模块去覆盖其感知范围内同属性的目标。实验结果表明,该算法是有效的,在网络生命周期和时间效率等方面均优于CWGC方案,接近于线性规划最优值。     

基于神经网络的面波迭代反演应用研究

根据滩浅海近地表结构特征,尝试利用地震记录中的面波进行近地表结构研究,以便了解滩浅海地区的近地表地层介质结构变化,为深层油气勘探提供准确的低降速带资料.针对面波频散反演已有方法存在的不足,引入一种基于BP神经网络的迭代反演方法对面波的频散曲线进行拟合迭代,用于反演预测滩浅海低降速带地层参数.由于神经网络具有很强的自学习、自适应、自组织和容错能力,它的反演预测能力非常强大,能够较精确地预测出所要求解的目标数据,同时结合传统迭代反演方法的优点,增强了该方法的反演预测能力.通过对滩浅海近地表结构模型试算,获得好的效果,同时进一步对实际记录进行了计算,也取得了比较满意的结果.     

Mechanical,thermal, and dielectric properties of SiCf/SiC composites reinforced with electrospun SiC fibers by PIP

Electrospun unidirectional SiC fibers reinforced SiC_f/SiC composites (e-SiC_f/SiC) were prepared with ∼10% volume fraction by polymer infiltration and pyrolysis (PIP) process. Pyrolysis temperature was varied to investigate the changes in microstructures, mechanical, thermal, and dielectric properties of e-SiC_f/SiC composites. The composites prepared at 1100 °C exhibit the highest flexural strength of 286.0 ± 33.9 MPa, then reduced at 1300 °C, mainly due to the degradation of electrospun SiC fibers, increased porosity, and reaction-controlled interfacial bonding. The thermal conductivity of e-SiC_f/SiC prepared at 1300 °C reached 2.663 W/(m∙K). The dielectric properties of e-SiC_f/SiC composites were also investigated and the complex permittivities increase with raising pyrolysis temperature. The e-SiC_f/SiC composites prepared at 1300 °C exhibited EMI shielding effectiveness exceeding 24 dB over the whole X band. The electrospun SiC fibers reinforced SiC_f/SiC composites can serve as a potential material for structural components and EMI shielding applications in the future.