rGO/CuO/PEDOT nanocomposite formation,its characterisation and electrochemical performances for supercapacitors

ABSTRACT

Supercapacitor properties of rGO, CuO, PEDOT and rGO/CuO at [rGO]_o/[CuO]_o?=?1:1; 1:1.5; 1:2 and rGO/CuO/PEDOT nanocomposite at [rGO]_o/[CuO]_o/[EDOT]_o?=?1:1:1; 1:1:3; 1:1:5 were investigated using chemical reduction of GO and in-situ polymerisation process. SEM-EDX, HRTEM, BET surface area analysis confirm the nanocomposite formations. Nanocomposite materials are also analysed through FTIR-ATR, Raman, TGA-DTA, GCD, CV and EIS. The highest specific capacitance of C _sp?=?156.7 F/g at 2?mV/s is determined as rGO/CuO/PEDOT at [rGO]_o/[CuO]_o/[EDOT]_o?=?1:1:5. In addition, two-electrode supercapacitor device for rGO/CuO/PEDOT at [rGO]_o/[CuO]_o/[EDOT]_o?=?1:1:5 are found to provide a maximum specific energy (E?=?14.15 Wh/kg at 20?mA) and specific power (P?=?24730 W/kg at 50?mA), electrical serial resistance (ESR?=?13.33 Ω) with good capacity retention after 3000 cycles. An equivalent circuit model of LR1(CR2)(QR3) is proposed to interpret the EIS data. The supercapacitor performance of the rGO/CuO/PEDOT nanocomposite electrode indicates the synergistic effect of hybrid supercapacitors.     

Assessment of the Axial Load Response of an H Pile Driven in Multilayered Soil

Most of the current design methods for driven piles were developed for closed-ended pipe piles driven in either pure clay or clean sand. These methods are sometimes used for H piles as well, even though the axial load response of H piles is different from that of pipe piles. Furthermore, in reality, soil profiles often consist of multiple layers of soils that may contain sand, clay, silt or a mixture of these three particle sizes. Therefore, accurate prediction of the ultimate bearing capacity of H piles driven in a mixed soil is very challenging. In addition, although results of well documented load tests on pipe piles are available, the literature contains limited information on the design of H piles. Most of the current design methods for driven piles do not provide specific recommendations for H piles. In order to evaluate the static load response of an H pile, fully instrumented axial load tests were performed on an H pile (HP?310×110) driven into a multilayered soil profile consisting of soils composed of various amounts of clay, silt and sand. The base of the H pile was embedded in a very dense nonplastic silt layer overlying a clay layer. This paper presents the results of the laboratory tests performed to characterize the soil profile and of the pile load tests. It also compares the measured pile resistances with those predicted with soil property- and in situ test-based methods.     

Achieving compatibility in blends of low‐density polyethylene/polyamide‐6 with addition of ethylene vinyl acetate

Polymer alloys and blends, whose major advantage is the potential of achieving a range of physical and mechanical properties, have continued to be a subject of interest over recent years. Addition of a block or graft copolymer, with chemically similar segments to those involved in the polymer blend considered, led to a variety of desirable properties. The copolymer added to the blend functioned to promote a homogeneous dispersion of the constituent phases and to enhance their mutual adhesion. Such agents that enable better dispersion in polymer blends are known as compatibilizers. In this study an attempt has been made to improve the compatibility in a polymer blend composed of two normally incompatible constituents, LDPE and PA₆, by addition of a compatibilizer. The compatibilizer agent, ethylene vinyl acetate (EVA), was added to the polymer blend in ratios of 1, 5, and 10% by using a twin‐screw extruder. The effect of EVA on the crystallization of the polymer constituents was observed through DSC examinations. Furthermore, the control sample and all three blends of LDPE/PA₆/EVA were subjected to examinations to obtain their yield and tensile strengths, elasticity modulus, percentage elongation, izod impact strength, hardness, and melt flow index. © 2001 John Wiley & Sons, Inc. J Appl Polym Sci 82: 1748–1754, 2001     

Photovoltaic system assessment for a school building

The installation of photovoltaic panels (PVs) on the roof of residential and commercial buildings is getting widespread as these areas stand normally idle and can be used for another purpose without losing an inhabited space. Considering the solar potential of Turkey, a significant amount of electricity generation is possible using current PV technology. For this reason, a two-story detached school building located in ?zmir, Turkey was taken into consideration and monthly as well as annual coverage ratio of an on-grid PV system for its entire energy requirement (including heating, cooling and lighting) was investigated. The PVs were installed on the south face of the school building roof. A heat pump, with a typical coefficient of performance (COP) value of 2.5, was used for supplying required cooling and heating. The heating, cooling and lighting loads were determined on a monthly basis. The average monthly electrical energy generation of the mounted PVs was calculated using a written code in Energy Equation Solver (EES) software. As a result, the monthly as well as yearly electrical energy demand coverage ratio values for the school using the installed PVs were revealed. Since the school building has a large south faced roof, the installation of PVs is very suitable to meet the cumulative electrical energy need of the heat pump and the lighting load. For Case 1, 180 PVs, which supply the entire yearly demand (with a 110% coverage ratio), were taken into consideration, while for Case 2, 265 PVs, which cover 75% of the roof area, were evaluated. The results showed that between November and March, PV electrical energy generation is not sufficient to meet all energy need of the school for both cases. However, significant coverage ratio values were observed for the rest of the year. In a yearly basis, the PV generation exceeded the building demand by 62% for the Case 2. This conclusion points out that the school can meet its yearly electricity need with the considered PV system and can even have an additional financial profit by selling its surplus PV electricity to the grid. Economic and environmental payback time values as well as simple payback time value were also computed for both investigated cases. The results pointed out a simple payback time of 7.9 years for Case 1 and 7.6 years for Case 2. Energy payback time was determined as 5 years for both systems. The greenhouse gas payback time of 2.7 years and 5.9 years was encountered for coal based and natural gas based calculations.     

Weighting factors design in model predictive direct torque control based on cascaded neural network

An innovative control strategy is introduced in this paper for model predictive direct torque control (MPDTC) of a permanent magnet synchronous motor (PMSM) inverter, which is based on a cascaded neural network for the automatic selection and online tuning of weighting factors. Specifically, the lower network in the proposed two-stage cascaded network is trained by utilizing the weighting factors and the corresponding converter parameters under a specific working condition to establish data substitution models under that working condition and determine the fitness function for obtaining the optimal weighting factors. The upper network of the cascaded network is trained using various working conditions and their corresponding optimal weighting factors calculated by the lower network, with the goal of achieving real-time tuning of the weighting factors under variable working conditions. By employing a data-driven method to design the weighting factors at each working condition offline, this method reduces online tuning to a single calculation in the upper network and minimizes the online calculation burden. This approach enables the weighting factors to be adjusted in real-time according to changes in the working conditions, leading to enhanced accuracy of weighting factor optimization. Experimental results demonstrate that the proposed strategy improves the overall performance of the inverters.     

Power generation expansion planning with adaptive simulated annealing genetic algorithm

In this paper, an adaptive simulated annealing genetic algorithm is proposed to solve generation expansion planning of Turkey's power system. Least‐cost planning is a challenging optimization problem due to its large‐scale, long‐term, nonlinear, and discrete nature of power generation unit size. Genetic algorithms have been successfully applied during the past decade, but they show some limitations in large‐scale problems. In this study, simulated annealing is used instead of mutation operator to improve the genetic algorithm. The improved algorithm is applied to the power generation system with seven types of generating units and a 20‐year planning horizon. The planning horizon is divided into four equal periods. The new algorithm provides approximately 6.6 billion US$ (3.2%) cheaper solution than GA and also shows faster convergence. Copyright © 2006 John Wiley & Sons, Ltd.     

Smart shop floor scheduling using knowledge based simulation

In this paper, the need for knowledge-based simulation technique in shop floor scheduling are addressed. A prototype integrated system in Feed Mill manufacturing utilizing an integrated approach of Artificial Intelligence (AI) and simulation is discussed. The system is designed to support the production planner in scheduling and controlling the shop floor on real-time and on-line basis. System overview with the emphasis on knowledge-based simulation module is described.