One step synthesis of rGO-Ni3S2 nano-cubes composite for high-performance supercapacitor electrodes

In the last decade, supercapacitors possessing high power density and cyclic stability have attracted great interests in various applications. Graphene-based composite electrodes are known as a promising candidate for supercapacitors due to synergistic effects. For the first time, in this work, we develop a simple one-step hydrothermal synthesis of graphene wrapped Ni₃S₂ nanocubes (rGO-Ni₃S₂) composite for high-performance and low-cost supercapacitor electrodes. The rGO-Ni₃S₂ electrode exhibits an ultrahigh specific capacity of 616 C g^?1 at the current density of 1 A g^?1 with excellent cycling durability of 92.7% after 5000 cycles, which is much better when compared with the counterpart without graphene (pure Ni₃S₂). We attribute the remarkable performance of the rGO-Ni₃S₂ electrode to the synergistic effects of the graphene as the conductive support and Ni₃S₂ cubics as the pseudocapacitive material. This work constitutes a step forward towards the development of low-cost and high-performance supercapacitors for the next generation of portable electronics.     

Adjusted robust mean-value-at-risk model: less conservative robust portfolios

We examine the robust mean-VaR portfolio optimization problem when a parametric approach is used for estimating VaR. A robust optimization formulation is used to accommodate estimation risk, and we obtain an analytic solution when there is a risk-free asset and short-selling is allowed. This renders the model computationally tractable. Further, to avoid the conservatism of robust optimal portfolios, we suggest an adjusted robust optimization approach. Empirically, we evaluate the out-of-sample performance of the new approach, the robustness of obtained solutions and level of conservatism of the resulting portfolios. The empirical results highlight some benefits of our approach.     

Effects of forming media on hydrodynamic deep drawing

Apart from the punch and the die, a pressurized fluid (water or oil) is used in hydroforming. The presence of such pressure media is the main difference between hydroforming and conventional deep drawing. No comprehensive study has yet been conducted on the effect of forming media on the formation of cylindrical cups via hydrodynamic deep drawing assisted by radial pressure. This study investigated the formation of such cups through Finite element (FE) simulation and experiments. First, the process was modeled numerically using ABAQUS FE software. After simulation, copper and St14 sheets were formed with water and oil as the forming media. The effect of these forming media on thickness distribution and maximum punch force was investigated. By examining the thickness distribution curve of the hydroformed cup, a close agreement was found between experimental and numerical results. Using oil as the forming media reduced thinning at the corner radius zone of the punch and increased the maximum punch force. Changing the forming media does not significantly influence the maximum thickening at the cup wall region.

     

A particle swarm–BFGS algorithm for nonlinear programming problems

This article proposes a hybrid optimization algorithm based on a modified BFGS and particle swarm optimization to solve medium scale nonlinear programs. The hybrid algorithm integrates the modified BFGS into particle swarm optimization to solve augmented Lagrangian penalty function. In doing so, the algorithm launches into a global search over the solution space while keeping a detailed exploration into the neighborhoods. To shed light on the merit of the algorithm, we provide a test bed consisting of 30 test problems to compare our algorithm against two of its variations along with two state-of-the-art nonlinear optimization algorithms. The numerical experiments illustrate that the proposed algorithm makes an effective use of hybrid framework when dealing with nonlinear equality constraints although its convergence cannot be guaranteed.     

A novel cost optimization method for mobile cloud computing by dynamic processing of demands based on their power consumption

Mobile cloud computing (MCC) is an emerging technology that is introduced to combat the existing limitations in mobile computing such as constrained energy and storage. MCC enables mobile users to perform their tasks in the operator cloud and benefit from the offered services. On the other hand, operators are required to decrease their costs to stay in the competitive market. In this paper, we propose a method to reduce the cost of power consumption and increase the profit of 4G/5G network operators delivering MCC services. We propose an online method that is based on dynamic processing of mobile users’ demands based on their power consumption in the cloud, called Dyn-PDPC. In this algorithm, the power consumption of demands is estimated based on event counters, and demands are classified and processed accordingly. Unlike the offline methods, the proposed online method can be implemented with the existing information and there is no need for prior knowledge. We also present an extended version of Dyn-SP algorithm, in which we had an unrealistic assumption about the energy consumption of demands. In Dyn-PDPC, by using control parameters, when the electricity price is low, demands with high power consumption are processed, and then the low power-consumption demands are processed. Similarly, when the electricity price is high, demands with low power consumption are processed at first. Simulation results demonstrate that the proposed algorithm has more accuracy, and more reduction in long-term cost compared to other online methods in MCC networks.     

Taguchi design for optimization of structural and mechanical properties of hydroxyapatite-alumina-titanium nanocomposite

The Taguchi methodology was utilized to determine the influence of three factors, namely nanostructured alumina (A) and micro-structured titanium (B) weight percents and sintering temperature (C) on the phase stability, mechanical and structural properties of hydroxyapatite (HA) composites. HA nanosized powder was synthesized via wet precipitation method. According to L9 orthogonal array, different combinations of powder mixtures were cold isostatically pressed and pressure-less sintered in a reducing atmosphere. XRD analysis confirmed the presence of HA phase and metallic Ti after sintering. Analyze of Variance (ANOVA) method was used to specify the percentage contributions of three factors. Addition of 5–10?wt% titanium contributed to increasing the decomposition of HA and the amount of open porosity by 43.07% and 55.40%, respectively and caused a decrease in the strength by 44.67%. Alumina nanoparticles consistently inhibited the grain growth but showed a negligible effect on the decomposition of HA. It also caused enhancements in the strength and toughness by 14.61 and 23.70% contributions. According to ANOVA, sintering temperature illustrated considerable effects on the properties of HA composites. It exhibited more than 56% contribution to the grain growth and decomposition of HA. Structural investigations led to a total optimum condition with a combination of 7?wt % alumina/3?wt % titanium/1150?°C.     

A novel ZrB2-based composite manufactured with Ti3AlC2 additive

A novel ZrB₂–Ti₃AlC₂ composite was densified using spark plasma sintering at 1900 °C under pressure of 30 MPa for 7 min. The effect of Ti₃AlC₂ MAX phase on the densification behavior, microstructural evolutions, phase arrangement, and mechanical properties of the composite were investigated. The phase analysis and microstructural studies revealed the decomposition of the MAX phase at the initial steps of the SPS process. The structural characteristics and surface morphology of the in-situ synthesized reinforcements were verified using X-ray diffraction and scanning electron microscopy, respectively. The formation mechanism of each reinforcement phase was also investigated using thermodynamical assessments. The prepared ZrB₂–Ti₃AlC₂ composite not only possessed a near fully-dense characteristic having an excellent hardness of 31 GPa, but also unexpectedly presented high fracture toughness. The indentation fracture toughness of the composite was calculated as 7.8 MPa m^1/2, which is unprecedented compared with the same class of hard ZrB₂-based composites. Indeed, the superior mechanical properties of the composite achieved in this study was obtained by the homogenous distribution of Al-based reinforcements, formation of hard interfacial ZrC grains, and solid solutions provided by Ti-based phases. The correlations between the phase arrangement, microstructure, and the attained mechanical properties of the composite were comprehensively discussed.     

General bounds for the optimal value of retailers’ reorder point in a two-level inventory control system with and without information sharing

In this study, an inventory system consisting of a single product, one supplier, and multiple identical retailers is considered. Each retailer replenishes inventory from the supplier according to the well known (R,Q) policy. Transit times are constant and retailers face independent Poisson demand. The supplier utilizing the retailers' information in decision making for replenishment policy with a given order size starts with m initial batches (of size Q) and places an order in a batch of size Q to an outside source when a new order is placed. In this inventory system, excess demand is backordered, delayed orders are satisfied on a first-come first-serve basis, and no partial shipment is allowed. By partitioning the cost function of this system, general upper and lower bounds for the optimal value of R are determined. Based on several numerical examples, it is shown that these bounds (especially the lower bound) allow the optimal reorder point to be found more effectively with a shorter solving time.     

Fe3+-Clinoptilolite/graphene oxide and layered MoS2@Nitrogen doped graphene as novel graphene based nanocomposites for DMFC

Fe³⁺ doped in a natural zeolite (Fe³⁺-Clinoptilolite) hybridized with graphene oxide (GO) was used as an electro-catalyst for methanol oxidation in direct methanol fuel cells (DMFC). Furthermore, thin layered molybdenum disulfide (MoS₂) composited with nitrogen doped graphene (NG) was used for oxygen reduction. Successful synthesis of these nanomaterials was confirmed by X-ray diffraction (XRD), X-ray florescence (XRF), Fourier transform infrared (FTIR), energy-dispersive X-ray (EDX), Raman spectroscopy, Field Emission Scanning Electron Microscopy (FESEM) and transmission electron microscopy (TEM) images. In the following, by using the cyclic voltammetry (CV) technique the electrochemical behaviors of the glassy carbon electrodes modified with the mentioned composites were investigated. The results of methanol oxidation and oxygen reduction showed sufficient electro-catalytic effects as well as significant diffusion currents in presence of the non-precious synthetic materials. Obtained exchange currents (i₀) from Tafel plots showed increasment up to 6.02 × 10^?6 and 1.47 × 10^?5 μA for anode and cathode respectively. Also, thermodynamic potential of the DMFC was estimated about 1.1 V in alkaline media that was very close to reported value for theoretical potential in DMFC.