Managing the degree of exfoliation and number of graphene layers using probe sonication approach

We have demonstrated a fast, versatile, and scalable approach to synthesize high-quality few layer graphene sheets with low defect ratio and high crystallinity produced from exfoliation of graphite flakes in DMF by using probe sonication. The effect of sonication time on degree of exfoliation and number of graphene layers has been fully investigated. The degree of exfoliation of graphene sheets as a function of sonication time has been successfully analyzed by XRD, UV-Vis spectroscopy, TEM, and BET studies. The morphological changes at different sonication times have also been observed by SEM. A structural and defect characterization of graphene sheets has been discussed in detail by Raman spectroscopic technique. The shift in position of 2D Raman band and its de-convolution provided information about formation of multi to few layer graphene sheets with sonication. Moreover, Raman results are highly consistent with TEM studies as per number of graphene layers is concerned.     

Empirical validation of object-oriented metrics for predicting fault proneness models

Empirical validation of software metrics used to predict software quality attributes is important to ensure their practical relevance in software organizations. The aim of this work is to find the relation of object-oriented (OO) metrics with fault proneness at different severity levels of faults. For this purpose, different prediction models have been developed using regression and machine learning methods. We evaluate and compare the performance of these methods to find which method performs better at different severity levels of faults and empirically validate OO metrics given by Chidamber and Kemerer. The results of the empirical study are based on public domain NASA data set. The performance of the predicted models was evaluated using Receiver Operating Characteristic (ROC) analysis. The results show that the area under the curve (measured from the ROC analysis) of models predicted using high severity faults is low as compared with the area under the curve of the model predicted with respect to medium and low severity faults. However, the number of faults in the classes correctly classified by predicted models with respect to high severity faults is not low. This study also shows that the performance of machine learning methods is better than logistic regression method with respect to all the severities of faults. Based on the results, it is reasonable to claim that models targeted at different severity levels of faults could help for planning and executing testing by focusing resources on fault-prone parts of the design and code that are likely to cause serious failures.     

Layered axial force coupled membrane based metal contact single-pole quad-throw RF MEMS switch: design,RF performance and mechanical modeling

Microsystem Technologies - RF MEMS is a perfect candidate to replace the conventional switches used for microwave frequency. Most of the RF MEMS switches developed generally concentrate on...     

Comparing and evaluating the effectiveness of mobile Web adequacy evaluation tools

Universal Access in the Information Society - The number of Web sites is growing exponentially and so are the people who are accessing them on mobile devices including people with special...     

Exact fuzzy optimal solution of fully fuzzy linear programming problems with unrestricted fuzzy variables

Kumar et al. (Appl. Math. Model. 35:817?C823, 2011) pointed out that there is no method in literature to find the exact fuzzy optimal solution of fully fuzzy linear programming (FFLP) problems and proposed a new method to find the fuzzy optimal solution of FFLP problems with equality constraints having non-negative fuzzy variables and unrestricted fuzzy coefficients. There may exist several FFLP problems with equality constraints in which no restriction can be applied on all or some of the fuzzy variables but due to the limitation of the existing method these types of problems can not be solved by using the existing method. In this paper a new method is proposed to find the exact fuzzy optimal solution of FFLP problems with equality constraints having non-negative fuzzy coefficients and unrestricted fuzzy variables. The proposed method can also be used to solve the FFLP problems with equality constraints having non-negative fuzzy variables and unrestricted fuzzy coefficients. To show the advantage of the proposed method over existing method the results of some FFLP problems with equality constraints, obtained by using the existing and proposed method, are compared. Also, to show the application of proposed method a real life problem is solved by using the proposed method.     

Analysis of the Photonic Crystal Power Splitter Based on the Junction Defect Radius for Optimum Resonance

Nano-photonics is an emerging area of optical materials, which would take the optointegrated circuits towards progress. Photonic crystal (PC) based power splitters are useful constituents for the design of photonic integrated circuits (PICs). They are very important devices for connecting different building blocks on an integrated optical chip. In this paper, a two-dimensional PC Y-junction power splitter (21×15 μm) based on the resonance effect with circular air holes etched on a hexagonal lattice with a period a is proposed. The plane wave expansion (PWE) and finite difference time domain (FDTD) techniques are used for analyzing the structure. The simulation results show that the optimum resonance occurs when the radius of the defect hole is 0.3a, leading to the maximum and equal power distribution.     

Spin valve effect in sputtered FL-MoS2 and ferromagnetic shape memory alloy based magnetic tunnel junction

In the last decade, two-dimensional (2D) transition metal dichalcogenides have been introduced with great significance in the spintronic devices for their extraordinary electrical, optical, and spin-dependent properties. In this work, we have fabricated a few-layer molybdenum disulfide (FL-MoS₂) (~6 nm) as a non-magnetic spacer layer in Ni–Mn–In/FL-MoS₂/Ni–Mn–In magnetic tunnel junction (MTJ) using DC magnetron sputtering. FL-MoS₂ thin film sandwiched between two ferromagnetic shape memory alloy based electrodes exhibit semiconducting behavior, confirmed by current-voltage (I–V) characteristics and temperature dependent resistance measurement. The fabricated MTJ shows spin valve effect in the presence of an external magnetic field. The tunneling magnetoresistance (TMR) has been recorded in 10 K–300 K temperature range. The highest TMR ratio of 0.51% was obtained at a low temperature ~10 K, corresponding to the spin polarization of ~5%. This TMR ratio reduces to a value of 0.032% as the temperature of the device increases up to 300 K, displaying a finite TMR at room temperature. A detailed study of thickness and temperature-dependent magnetization versus magnetic field (M ? H) hysteresis loops of Ni–Mn–In thin films has been performed to understand the complex TMR behavior. The present study paves the way for the use of sputtered FL-MoS₂ and ferromagnetic shape memory alloy in ultrafast spintronics for advanced magnetic devices application.     

Enhancing linearity in I–V characteristics by B/N doping in graphene for communication devices

To explore communication applications, a study towards achieving linearity in the I–V characteristics through increasing concentrations of Boron (B) / Nitrogen (N) doping on pristine graphene sheet is investigated. Individual B/N doping of 6.25, 12.50, 18.75 and 25% has been done in the same sub lattice using Density Functional Theory (DFT) along with Non Equilibrium Greens Function (NEGF) calculations. The modification in the electronic and transport properties of graphene sheet are also investigated. In comparison to the variation of band gap from 0.35 to 1.183 eV and 0.36 to 1.149 eV for B and N respectively, an insignificant variation in effective mass is reported. Apart from linearity, variation in conductance in doped structures is seen. B doping increases conductivity and yields ON current of 610 µA while N doping gives ON current of 310 µA for maximum doping concentrations. In this work, the sustained carrier mobility and high gain linear characteristics of doped graphene obtained will help to utilise a graphene channel for different communication device applications.