Updates on the development of nanostructured transition metal nitrides for electrochemical energy storage and water splitting

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Social impacts of road traffic: perceptions and priorities of local residents

The assessment of the social impacts of road traffic is usually based on objective indicators or on expert judgement, without input from the affected communities. This paper considers the perceptions and priorities of local residents about traffic impacts and possible mitigation measures, using as a case study a rural area that will be affected by traffic associated with the construction of a nuclear power station. The study consisted of a qualitative phase followed by a stated preference survey. Econometric models were used to measure the relative priority of different impacts and mitigation measures. The most impactful aspects were noise, vibration and increased car or bus travel times. The most preferred measures were night-time restrictions to HGVs, parking restrictions and safety measures for pedestrians and cyclists. There were significant differences in preferences according to residence location, gender, employment status and household composition. The results provide information about aspects that tend to be aggregated in existing assessment frameworks, separating the reduction in the utility of some activities (like walking and driving) and the suppression of those activities.     

Ultrathin Co3O4 nanosheets highly dispersed on reduced graphene oxide: An efficient bi-functional catalyst for Li-O2 battery

Ultrathin Co₃O₄ nanosheets grown on the reduced graphene oxide (Co₃O₄/rGO) was synthesized by a simple hydrothermal method and was investigated as a cathode in a Li-O₂ battery. Benefited from the synergistic effect between Co₃O₄ and rGO, the hybrid exhibits a high initial capacity of 10,528 mAh g^?1 along with a high coulombic efficiency (84.4%) at 100 mA g^?1. In addition, the batteries show an enhanced cycling stability and after 113 cycles, the cut-off discharge voltage remains above 2.5 V. The outstanding performance is intimately related to the high surface area of rGO, which not only provide carbon skeleton for the uniform distribution of Co₃O₄ nanosheets but also facilitate the reversible formation and decomposition of insoluble Li₂O₂. The results of electrochemical tests confirm that the Co₃O₄/rGO hybrid is a promising candidate for the Li-O₂ batteries.     

Silica shell-assisted synthetic route for mono-disperse persistent nanophosphors with enhanced in vivo recharged near-infrared persistent luminescence

Near-infrared (NIR) persistent-luminescence nanoparticles have emerged as a new class of background-free contrast agents that are promising for in vivo imaging.The next key roadblock is to establish a robust and controllable method for synthesizing monodisperse nanoparticles with high luminescence brightness and long persistent duration.Herein,we report a synthesis strategy involving the coating/etching of the SiO2 shell to obtain a new class of small NIR highly persistent luminescent ZnGa2O4∶Cr3+,Sn4+ (ZGOCS) nanoparticles.The optimized ZGOCS nanoparticles have an excellent size distribution of ～15 nm without any agglomeration and an NIR persistent luminescence that is enhanced by a factor of 13.5,owing to the key role of the SiO2 shell in preventing nanoparticle agglomeration after annealing.The ZGOCS nanoparticles have a signal-to-noise ratio ～3 times higher than that of previously reported ZnGa2O4∶Cr3+ (ZGC-1) nanoparticles as an NIR persistent-luminescence probe for in vivo bioimaging.Moreover,the persistent-luminescence signal from the ZGOCS nanoparticles can be repeatedly re-charged in situ with external excitation by a white lightemitting diode;thus,the nanoparticles are suitable for long-term in vivo imaging applications.Our study suggests an improved strategy for fabricating novel high-performance optical nanoparticles with good biocompatibility.     

Crystallographic analysis on small fatigue crack propagation behaviour of a nickel-based single crystal superalloy

In situ observations by scanning electron microscopy show that small fatigue cracks in a nickel-based single crystal superalloy are inclined to the loading direction and propagate in dominant crystallographic manners. In order to evaluate the driving forces for inclined crack propagation, three-dimensional anisotropic linear elastic finite-element analysis is conducted. The plastic zone size on the dominant slip plane has been calculated and proposed to correlate the fatigue crack growth. It is shown that this parameter takes into account both material anisotropy and octahedral fracture modes, and it can effectively characterize small crack propagation behaviour.     

Modelling and joint monitoring of input and output of systems with arbitrary order autoregressive disturbance

Considerable studies have been done on modelling and joint monitoring of input and output of systems with autoregressive moving average (ARMA) disturbance. Most of these studies focus on systems with ARMA (1, 1) disturbance. However, many kinds of systems are not conform to ARMA(1, 1) disturbance. Motivated by the fact that an autoregressive (AR) model with high order can be implemented to approximate the stationary ARMA model at any precision, a new generic model and a joint monitoring scheme of systems with arbitrary order AR(p) disturbance are developed. A minimum mean squared error (MMSE) controller with arbitrary order AR disturbance is designed to reduce the system variability. The mathematical expectation and average run length of MMSE-controlled outputs are derived. A new joint chart for monitoring the input and output simultaneously is explored. Two out-of-control rules for the joint monitoring chart are developed. The monitoring performances of the input chart, the output chart and the joint monitoring chart are also discussed. The results of simulation experiments and case studies validate the effectiveness of the developed model and joint monitoring chart.     

Research on lease and sale of electric vehicles based on value engineering

Electric vehicles (EVs) acknowledged as potential means of transportation tools in the near future are widely accepted as the development trend of automobile industry due to its environment protection and fuel energy saving properties. As a product containing new technologies and concepts with little market experience and consumer identification, studying its life cycle operation modes will help to figure out an optimal approach to conduct EVs manufacturing and service. The two common operation modes, lease and sale of EVs, have their own advantages and weaknesses under different scenarios and consumer psychological status. Research and comparisons on the function, cost and value of two operation modes in full life cycle will simulate the rapid development of EVs forming a mature and dynamic operation mechanism. This paper utilised approaches in value engineering, putting forward customer requirements and technical elements of EV lease and sale based on quality assessment and customer-perceived value, proposing the metric method of function and cost coefficient by mathematical modelling, and conducting value coefficient analysis and comparison based on customer’s risk aversion psychology. An illustrative example raised for studying operation mode of three different kinds of EVs based on the analysis of value coefficient, providing guideline for manufacturer and servicers of EVs.     

A Change-Point Approach for Phase-I Analysis in Multivariate Profile Monitoring and Diagnosis

Process monitoring and fault diagnosis using profile data remains an important and challenging problem in statistical process control (SPC). Although the analysis of profile data has been extensively studied in the SPC literature, the challenges associated with monitoring and diagnosis of multichannel (multiple) nonlinear profiles are yet to be addressed. Motivated by an application in multioperation forging processes, we propose a new modeling, monitoring, and diagnosis framework for phase-I analysis of multichannel profiles. The proposed framework is developed under the assumption that different profile channels have similar structure so that we can gain strength by borrowing information from all channels. The multidimensional functional principal component analysis is incorporated into change-point models to construct monitoring statistics. Simulation results show that the proposed approach has good performance in identifying change-points in various situations compared with some existing methods. The codes for implementing the proposed procedure are available in the supplementary material.