Nitrogen-Mediated Graphene Oxide Enables Highly Efficient Proton Transfer

Two-dimensional (2D) graphene and graphene oxide (GO) offer great potential as a new type of cost-efficient proton-exchange membranes (PEM) for electrochemical devices. However, fundamental issues of proton transfer mechanism via 2D membranes are unclear and the transfer barrier for perfect graphene are too high for practical application. Using ab initio molecular dynamic simulations, we screened the proton transfer barrier for different un-doped and nitrogen doped GO membranes, and clarified the corresponding transfer mechanisms. More significantly, we further identify that N-mediated GO can be built into a highly efficient PEM with a proton transfer rate of seven orders of magnitude higher than an un-doped case via. a proton relay mechanism between a ketone-like oxygen and a pyridine-like nitrogen across the vacancy site. The N-doped 2D GO is also impermeable to small molecules, and hence a highly efficient PEM for practical applications

Bearing angle based cooperative source localization

© 2014 IEEE. This paper deals with the cooperative source localization problem with the goal of having an accurate estimate of the coordinate of the source cooperatively by a group of unicycle-type mobile agents. Neither absolute positioning information nor a common sense of direction is shared by the agents. Each agent gets its estimate about the source's coordinate in its own local frame based on the bearing measurements about its neighbors (that may or may not include the source) together with its own linear and angular speed information. A continuous time estimation scheme and a distributed fusion scheme are proposed for this goal such that the source's relative coordinate can be estimated at any time by each agent no matter whether it can directly detect the source or not. The globally asymptotic convergence of the estimation scheme and the fusion scheme is rigorously analyzed. Simulation results are also provided to verify the effectiveness of the proposed algorithms

Cost-Efficient NFV-Enabled Mobile Edge-Cloud for Low Latency Mobile Applications

Mobile edge-cloud (MEC) aims to support low la- tency mobile services by bringing remote cloud services nearer to mobile users. However, in order to deal with dynamic workloads, MEC is deployed in a large number of fixed-location micro- clouds, leading to resource wastage during stable/low work- load periods. Limiting the number of micro-clouds improves resource utilization and saves operational costs, but faces service performance degradations due to insufficient physical capacity during peak time from nearby micro-clouds. To efficiently support services with low latency requirement under varying workload conditions, we adopt the emerging Network Function Virtualization (NFV)-enabled MEC, which offers new flexibility in hosting MEC services in any virtualized network node, e.g., access points, routers, etc. This flexibility overcomes the limitations imposed by fixed-location solutions, providing new freedom in terms of MEC service-hosting locations. In this paper, we address the questions on where and when to allocate resources as well as how many resources to be allocated among NFV- enabled MECs, such that both the low latency requirements of mobile services and MEC cost efficiency are achieved. We propose a dynamic resource allocation framework that consists of a fast heuristic-based incremental allocation mechanism that dynamically performs resource allocation and a reoptimization algorithm that periodically adjusts allocation to maintain a near- optimal MEC operational cost over time. We show through ex- tensive simulations that our flexible framework always manages to allocate sufficient resources in time to guarantee continuous satisfaction of applications’ low latency requirements. At the same time, our proposal saves up to 33% of cost in comparison to existing fixed-location MEC solutions

Highly Efficient Oxygen Reduction Catalysts by Rational Synthesis of Nanoconfined Maghemite in a Nitrogen-Doped Graphene Framework

The oxygen reduction reaction (ORR) is critical for electrochemical energy storage and conversion: e.g., in fuel cells and metal–air batteries. A major challenge is to develop cost-effective and durable ORR catalysts, to replace the relatively expensive platinum-loaded carbon (PtC) counterparts, particularly for large-scale applications. Despite progress over the past few decades in developing efficient non-precious-metal (NPM) catalysts, such as Fe/N/C-based materials (the best-known alternatives), most of the reported catalytic activities have yet to match that of PtC. Herein we propose a two-step process for the production of highly efficient NPM catalysts that outperform PtC in alkaline media: (1) a hierarchical porosity of a supporting substrate is generated and optimized in advance, especially to achieve a high total pore volume for rapid mass transfer, and (2) an appropriate amount of NPM precursor is added to the optimized substrate to boost the reduction potential while maintaining the hierarchically porous structure. Such a scheme was successfully applied to a case of nanoconfined maghemite (γ-Fe2O3) in a nitrogen-doped graphene framework. The resulting catalyst system surpasses the performance of the equivalent commercial PtC, in terms of a higher reduction potential, a significantly lower peroxide formation ratio, more than tripled kinetic current density, smaller Tafel slope, better durability, etc. The reported catalyst is also among the best of all the existing Fe-based ORR catalysts, indicating the great potential of γ-Fe2O3 for ORR in practical applications

Regulation of the flowering time of Arabidopsis thaliana by thylakoid ascorbate peroxidase

Flowering time of higher plants is precisely controlled by various exogenous and endogenous factors. Recent researches implied that H2O2 is a potential flowering initiation factor. In order to confirm this hypothesis, thylakoid ascorbate peroxidase (tAPX) overexpressing Arabidopsis, the mutant line containing a T-DNA insertion and the wild type have been analyzed in this study, since APX was an important enzyme scavenging H2O2 in plant cells. It was found that during the vegetative growth stage there was no phenotypic difference among the three lines under common conditions, but 3,3’-diaminobenzidinetetrahydrochloride (DAB) staining showed that the endogenous H2O2 content varied: the mutant line had the highest content; the wild type took the second place, while the tAPX-overexpressing line had the lowest H2O2 content. This trend was in accordance with the bolting and flowering time during the following reproductive growth stage: the mutant bolted and flowered first, followed by the wild type, and the overexpressing line bolted and flowered last. This correlation confirmed the previous hypothesis that “H2O2 is a possible factor in flowering induction”.Keywords: Ascorbate peroxidase, Arabidopsis thaliana, flowering time, hydrogen peroxide

Pore-scale direct numerical simulation of particle transport in porous media

A computational platform for direct numerical simulation of fluid-particle two-phase flow in porous media is presented in this study. In the proposed platform, the Navier-Stokes equations are used to describe the motion of the continuous phase, while the discrete element method (DEM) is employed to evaluate particle-particle and particle-wall interactions, with a fictitious domain method being adopted to evaluate particle-fluid interactions. Particle-wall contact states are detected by the ERIGID scheme. Moreover, a new scheme, namely, base point-increment method is developed to improve the accuracy of particle tracking in porous media. In order to improve computationally efficiency, a time splitting strategy is applied to couple the fluid and DEM solvers, allowing different time steps to be used which are adaptively determined according to the stability conditions of each solver. The proposed platform is applied to particle transport in a porous medium with its pore structure being reconstructed from micro-CT scans from a real rock. By incorporating the effect of pore structure which has a comparable size to the particles, numerical results reveal a number of distinct microscopic flow mechanisms and the corresponding macroscopic characteristics. The time evolution of the inlet to outlet pressure-difference consists of large-scale spikes and small-scale fluctuations. Apart from the influence through direct contacts between particles, the motion of a particle can also be affected by particles without contact through blocking a nearby passage for fluid flow. Particle size has a profound influence on the macroscopic motion behavior of particles. Small particles are easier to move along the main stream and less dispersive in the direction perpendicular to the flow than large particles

Algorithms for Fault-Tolerant Placement of Stateful Virtualized Network Functions

Traditional network functions (NFs) such as firewalls are implemented in costly dedicated hardware. By decoupling NFs from physical devices, network function virtualization enables virtual network functions (VNF) to run in virtual machines (VMs). However, VNFs are vulnerable to various faults such as software and hardware failures. To enhance VNF fault tolerance, the deployment of backup VNFs in stand-by VM instances is necessary. In case of stateful VNFs, stand-by instances require constant state updates from active instances during its operation. This will guarantee a correct and seamless handover from failed instances to stand-by instances after failures. Nevertheless, such state updates to stand-by instances could consume significant network bandwidth resources and lead to potential admission failures for VNF requests. In this paper, we study the fault-tolerant VNF placement problem with the optimization objective of admitting as many requests as possible. In particular, the VNF placement of active/stand-by instances, the request routing paths to active instances, and state transfer paths to stand-by instances are jointly considered. We devise an efficient heuristic algorithm to solve this problem, and propose a bi-criteria approximation algorithm with performance guarantees for a special case of the problem. Simulations with realistic settings show that our algorithms can significantly improve the request admission rate compared to conventional approaches

In-situ electrochemical modification of pre-intercalated vanadium bronze cathodes for aqueous zinc-ion batteries

Vanadium bronzes have been well-demonstrated as promising cathode materials for aqueous zinc-ion batteries. However, conventional single-ion pre-intercalated V2O5 nearly reached its energy/power ceiling due to the nature of micro/electronic structures and unfavourable phase transition during Zn2+ storage processes. Here, a simple and universal in-situ anodic oxidation method of quasi-layered CaV4O9 in a tailored electrolyte was developed to introduce dual ions (Ca2+ and Zn2+) into bilayer δ-V2O5 frameworks forming crystallographic ultra-thin vanadium bronzes, Ca0.12Zn0.12V2O5·nH2O. The materials deliver transcendental maximum energy and power densities of 366 W h kg−1 (478 mA h g−1 @ 0.2 A g−1) and 6627 W kg−1 (245 mA h g−1 @ 10 A g−1), respectively, and the long cycling stability with a high specific capacity up to 205 mA h g−1 after 3000 cycles at 10 A g−1. The synergistic contributions of dual ions and Ca2+ electrolyte additives on battery performances were systematically investigated by multiple in-/ex-situ characterisations to reveal reversible structural/chemical evolutions and enhanced electrochemical kinetics, highlighting the significance of electrolyte-governed conversion reaction process. Through the computational approach, reinforced “pillar” effects, charge screening effects and regulated electronic structures derived from pre-intercalated dual ions were elucidated for contributing to boosted charge storage properties

Identify the critical regions and switching/failure mechanisms in non-filamentary RRAM (a-VMCO) by RTN and CVS techniques for memory window improvement

Non-filamentary RRAM is a promising technology that features self-rectifying, forming/compliance-free, tight resistance distributions at both high and low resistance states (HRS/LRS). Direct experimental evidence for its physical switching & failure mechanisms, however, is still missing, due to the lack of suitable characterization techniques. In this work, a novel method combining the random-telegraph-noise (RTN), constant-voltagestress (CVS) and time-to-failure Weibull plot is developed to investigate these mechanisms in the non-filamentary RRAM cell based on amorphous-Si/TiO2. For the first time, the following key advances have been achieved: i) Switching mechanism by defect profile modulation in a critical interfacial region has been identified from defect locations extracted by RTN; ii) Defect profile in this region plays a critical role in device failure, leading to different Weibull distributions during negative (LRS) and positive (HRS) CVS; iii) Progressive formation of a conductive percolation path during electrical stress is directly observed due to defect generation in addition to pre-existing defect movement; iv) Optimizing the critical interfacial region significantly improves memory window and failure margin. This provides a useful tool for advancing the non-filamentary RRAM technology

A universal pH range and a highly efficient Mo2C-based electrocatalyst for the hydrogen evolution reaction

Electrochemical water splitting is a promising approach to generate ‘green’ hydrogen. The efficiency of this process relies on the effectiveness of the electrocatalysts used. The electro-kinetics of the hydrogen evolution reaction (HER) is highly pH dependent and conventional catalysts typically are expensive and rare platinum-based materials. The development of low-cost, multi-component electrocatalysts, where each of the components has a synergistic effect, can be an effective approach to improve kinetics. Herein, a series of transition metal (Fe, Mn, Co, and Ni)-modified molybdenum carbides in a nitrogen-doped carbon matrix (TM-Mo2C@NCF) are synthesised to maximise exposed active sites. Among them, Fe-Mo2C@NCF delivers the best-in-class HER performance over a wide range of electrolytes. Tafel slopes of 76, 109 and 110 mV dec−1 and overpotentials of 65, 130 and 129 mV at 10 mA cm−2 were obtained in 1.0 M KOH, 1.0 M phosphate buffer solution (PBS) and 0.5 M H2SO4, respectively. The computational study further indicates that the synergistic electronic modulation co-activated by Fe and N dopants in Fe-Mo2C@NCF can reduce the Gibbs free energy of H adsorption (ΔGH*) and render the Mo–Mo bridge site the most energetically favorable adsorption site for the H* intermediate, which contributes to an increased HER performance