H2SO4 as a passivating medium on the localised corrosion resistance of surgical 316L SS metallic implant and its effect on hydroxyapatite coatings

The localised corrosion resistance of 316L SS metallic implant due to H₂SO₄ treatment is being studied through electrochemical studies involving cyclic polarisation experiments and impedance studies. The efficiency of hydroxyapatite (HAP) coatings on H₂SO₄ treated 316L SS is also been investigated through electrochemical studies and the dissolution characteristics of the coatings. The study reveal that 15% H₂SO₄ treatment was found to be efficient in the corrosion resistance of 316L SS and dissolution of alloy is considerably reduced in the hydroxyapatite coatings on 15% H₂SO₄ treated 316L SS.     

Improving decision tree performance by exception handling

This paper focuses on improving decision tree induction algorithms when a kind of tie appears during the rule generation procedure for specific training datasets. The tie occurs when there are equal proportions of the target class outcome in the leaf node's records that leads to a situation where majority voting cannot be applied. To solve the above mentioned exception, we propose to base the prediction of the result on the naive Bayes(NB)estimate, k-nearest neighbour(k-NN)and association rule mining(ARM). The other features used for splitting the parent nodes are also taken into consideration.     

Influence of Threshold Voltage Performance Analysis on Dual Halo Gate Stacked Triple Material Dual Gate TFET for Ultra Low Power Applications

Silicon - In this article, a two dimensional (2-D) threshold voltage modeling based gate and channel engineering are developed analytically for Dual Halo Gate Stacked Triple Material Dual Gate...     

Air Jet Erosion Studies on Mg/SiC Composite

Magnesium with 10% SiC is identified to be a suitable composition for wear resistance application. To improve the utilization of this composite for various industrial applications, erosion study has been conducted by using air jet erosion tester with varied machining conditions. The composite is prepared by a conventional stir casting process. Alumina is taken as an erodent particle. Impact angle, erosion velocity, and discharge rate are taken as the governing parameters of erosion rate. Lower impact angle and high erodent velocity yield to have a high erosion rate of 0.022 g/min with the least surface finish of 1.48 μm. Erosion velocity is found to have a significant effect of 59% over the other considered parameters. Further, the analysis of the surface profile parameters likely; Ssk, Sku, Sp, Sv, and Sa on the machined surface reveals the mechanism of the material removal and also, the surface defects are analyzed by using SEM image.     

Influence of Germanium Source Dual Halo Dual Dielectric Triple Material Surrounding Gate Tunnel FET for Improved Analog/RF Performance

Silicon - This paper investigates the RF Stability performance of the Germanium Source Dual Halo Dual Dielectric Triple Material Surrounding Gate Tunnel FET Ge(SRC)-DH-DD-TM-SG-TFET using 3D -...     

Development of calcium phosphate based apatite from hen’s eggshell

Stoichiometric hydroxyapatite with Ca/P molar ratio, 1.67, was synthesized using hen’s eggshell as calcium source and phosphoric acid by precipitation method. Conventional EDTA titration and gravimetric methods were adopted to estimate the amount of calcium and phosphorous, respectively. Fourier-transform infrared (FT-IR) and X-ray diffraction (XRD) techniques were employed to investigate the formation of the HAP phase. Thermal analysis (TG-DTA) was carried out to investigate the thermal stability of HAP powder. FT-IR spectra show the characteristic peaks for phosphate and hydroxyl groups. XRD results reveal that the major characteristic peaks of HAP appear in the region of approximately 26°, 28°, 29°, 30–35°, 39°, 46°, 49° and 50° (2θ) and also indicate that there are no occurrences of secondary phases during HAP formation. TG-DTA result depicts that the synthesized HAP was stable up to 1300°C.     

Joint Equalization and Coding for On-Chip Bus Communication

In this paper, we propose using joint equalization and coding to improve on-chip communication speeds by signaling at rates beyond the rate governed by resistance-capacitance (RC) delay of the interconnect. Operating beyond the RC limit introduces inter-symbol interference (ISI). We mitigate the effects of ISI by employing equalization. The proposed equalizer employs a variable threshold inverter whose switching threshold is modified as a function of past output of the bus. We demonstrate even higher speedups by combining equalization with crosstalk avoidance coding. Specifically, simulation results for a 10-mm 32-bit bus in 0.13-mum CMOS technology show that 1.28 speedup is achievable by equalization alone and 2.30 speedup is achievable by joint equalization and coding.     

ANN–GA approach for predictive modeling and optimization of NOx emission in a tangentially fired boiler

An artificial neural network (ANN) and genetic algorithm (GA) approach to predict NOx emission of a 210 MW capacity pulverized coal-fired boiler and combustion parameter optimization to reduce NOx emission in flue gas, is proposed. The effects of oxygen concentration in flue gas, coal properties, coal flow, boiler load, air distribution scheme, flue gas outlet temperature, and nozzle tilt were studied. The data collected from parametric field experiments was used to build a feed-forward back-propagation neural net. The coal combustion parameters were used as inputs and NOx emission as outputs of the model. The ANN model was developed for full load conditions and its predicted values were verified with the actual values. The algebraic equation containing weights and biases of the trained net was used as fitness function in GA. The genetic search was used to find the optimum level of input operating conditions corresponding to low NOx emission. The results proved that the proposed approach could be used for generating feasible operating conditions.     

Quantum mechanical compact modeling of symmetric double-gate MOSFETs using variational approach

A physics-based analytical model for symmetrically biased double-gate (DG) MOSFETs considering quantum mechanical effects is proposed. Schrödinger's and Poisson's equations are solved simultaneously using a variational approach. Solving the Poisson and Schrödinger equations simultaneously reveals quantum mechanical effects (QME) that influence the performance of DG MOSFETs. The inversion charge and electrical potential distributions perpendicular to the channel are expressed in closed forms. We systematically evaluated and analyzed the potentials and inversion charges, taking QME into consideration, in Si based double gate devices. The effect of silicon thickness variation in inversion-layer charge and potentials are quantitatively defined. The analytical solutions provide good physical insight into the quantization caused by quantum confinement under various gate biases.