Effect of different thermomechanical processing on structure and mechanical properties of electron beam melted niobium

Among the refractory metals and alloys, niobium and niobium alloys are used in variety of high temperature applications ranging from light bulbs to rocket engines because of its high melting and boiling point, lower density, good ductility at room temperature and high corrosion resistance. In this paper the effects of different thermomechanical processing on structure and mechanical properties of electron beam melted niobium ingot was investigated. The correlation among the different processing conditions and microstructure as well as mechanical properties have been investigated using optical microscope, SEM, UTM and microhardness testing. The results show that the cold forging response of EB melted ingot was very poor, where as oxidation resistant coated ingot and ingot sealed in evacuated stainless steel jacket were successfully forged at 900 °C. The cast and hot forged EBM niobium ingot was cold rolled without any intermediate annealing. The hot forged, cold rolled and annealed niobium sheets exhibit better strength as compared to cold rolled and annealed niobium sheets. The mechanical properties of all the niobium sheets processed by using different processing conditions are superior to the properties specified by ASTM standard.     

In situ high-temperature powder diffraction studies of solid oxide electrolyte direct carbon fuel cell materials in the presence of brown coal

Direct carbon fuel cells are an attractive alternative for conventional power generation; however, there is almost no information on the stability of conventional fuel cell materials in direct carbon fuel cell environments, in particular when exposed to realistic fuels and the contaminants contained within these fuels. Similarly, there is little information on the structure and phase assemblage of solid fuels exposed to typical environments found in direct carbon fuel cells. In this paper, we use in situ high-resolution synchrotron powder diffraction on conventional high-temperature fuel cell materials and untreated brown coal to assess the stability and reactivity of these materials at various temperatures up to 850 °C. Materials investigated include nickel metal (Ni), gadolinium-doped ceria (GDC) and yttria-stabilised zirconia (YSZ). The phase stability, crystallite size, lattice parameters and associated linear coefficient of thermal expansion were determined. The phase stability of all fuel cell materials was found to be good with no additional phase formation noted either during heating or after prolonged periods at temperature. An increase in the crystallite size was observed for both GDC and Ni. Non-linear thermal expansion observed in these materials was related to partial reduction of cerium ions (GDC) and due to a Curie point transition (Ni). A wide range of mineral phases were observed in the coal samples and these phases were found to change significantly with temperature. Mineral phases consistent with the ash composition and existing literature on Victorian brown coal were assigned to phases observed.     

B-spline FIR filters

This paper presents an efficient procedure for the design of interpolated FIR (IFIR) filters with linear phase. The algorithm uses the uniform B-spline function as an interpolator and solves the optimal Chebyshev approximation problem on the optimal subinterval. The technique can be used for the design of general lowpass, highpass and bandpass filters. While the number of multiplications of the IFIR filter is dependent on the bandwidth and the center frequency of the desired filter, it provides the minimum number of multiplications achievable and nearly always provides a substantial reduction when compared to Parks-McClellan designs.     

Optical, thermal and phase transition studies in Sn1-x Ge x Te

The optical and thermal properties of the mixed semiconducting alloy, Sn_1-xGe_xTe, is studied by photo acoustics, for various Ge concentrations and phase transition for a particular concentration is also studied by the same method. The results are compared with the available literature values and discussed.     

Hydrothermal synthesis of Mg-Al hydrotalcites by urea hydrolysis

We report a simple method to prepare hydrotalcites involving both urea hydrolysis and hydrothermal synthetic conditions. Out of a series of Mg/Al ratios tried, pure hydrotalcite like phase was obtained for Mg/Al ratios of 1:1 and 2:1. Unlike in conventional co-precipitation method we succeeded in preparing Mg/Al ratio of 1:1 by this route. The high temperature (180 °C) applied and pressure developed in the autoclave during the synthesis might have altered the topochemical transformation. The materials were characterized by X-ray diffraction, X-ray photoelectron spectroscopy, Fourier transform infrared, thermo gravimetric and differential thermal analysis and transmission electron microscopy.     

Prediction of quality characteristics of laser drilled holes using artificial intelligence techniques

Micro-drilling using lasers finds widespread industrial applications in aerospace, automobile, and bio-medical sectors for obtaining holes of precise geometric quality with crack-free surfaces. In order to achieve holes of desired quality on hard-to-machine materials in an economical manner, computational intelligence approaches are being used for accurate prediction of performance measures in drilling process. In the present study, pulsed millisecond Nd:YAG laser is used for micro drilling of titanium alloy and stainless steel under identical machining conditions by varying the process parameters such as current, pulse width, pulse frequency, and gas pressure at different levels. Artificial intelligence techniques such as adaptive neuro-fuzzy inference system (ANFIS) and multi gene genetic programming (MGGP) are used to predict the performance measures, e.g. circularity at entry and exit, heat affected zone, spatter area and taper. Seventy percent of the experimental data constitutes the training set whereas remaining thirty percent data is used as testing set. The results indicate that root mean square error (RMSE) for testing data set lies in the range of 8.17–24.17% and 4.04–18.34% for ANFIS model MGGP model, respectively, when drilling is carried out on titanium alloy work piece. Similarly, RMSE for testing data set lies in the range of 13.08–20.45% and 6.35–10.74% for ANFIS and MGGP model, respectively, for stainless steel work piece. Comparative analysis of both ANFIS and MGGP models suggests that MGGP predicts the performance measures in a superior manner in laser drilling operation and can be potentially applied for accurate prediction of machining output.

     

Prediction and optimization of performance measures in electrical discharge machining using rapid prototyping tool electrodes

In this work, the performance of rapid prototyping (RP) based rapid tool is investigated during electrical discharge machining (EDM) of titanium as work piece using EDM 30 oil as dielectric medium. Selective laser sintering, a RP technique, is used to produce the tool electrode made of AlSi10Mg. The performance of rapid tool is compared with conventional solid copper and graphite tool electrodes. The machining performance measures considered in this study are material removal rate, tool wear rate and surface integrity of the machined surface measured in terms of average surface roughness (Ra), white layer thickness, surface crack density and micro-hardness on white layer. Since the machining process is a complex one, potentiality of application of a predictive tool such as least square support vector machine has been explored to provide guidelines for the practitioners to predict various machining performance measures before actual machining. The predictive model is said to be robust one as root mean square error in the range of 0.11–0.34 is obtained for various performance measures. A hybrid optimization technique known as desirability based grey relational analysis in combination with firefly algorithm is adopted for simultaneously optimizing the performance measures. It is observed that peak current and tool type are the significant parameters influencing all the performance measures.

     

Mathematical modeling insight of hetero gate dielectric-dual material gate-GAA-tunnel FET for VLSI/analog applications

This paper presents a mathematical modeling insight for the novel heterogate dielectric-dual material gate-GAA TFET (HD-DMG-GAA-TFET) and validating the results with TCAD simulation. By using the appropriate boundary conditions and continuity equations, the Poisson’s equation is solved to obtain the potential profile. The developed model is used to study the analog performance parameters such as subthreshold swing (SS), threshold voltage (V_th), transconductance (g_m), drain conductance (g_d), device efficiency (g_m/I_ds), intrinsic gain (g_m/g_d), channel resistance (R_ch) and output resistance (R_o). Further, to optimize the effect of metal work function on analog performance, three different combinations of DMG configurations has been studied. The results demonstrated that for a difference of 0.4 eV, the analog performance of the device is optimized. Low off current and high value of on current resulting into a higher I_ON/I_OFF ratio has been obtained, which is appropriate for sub-nanometre devices and low standby power applications. The analytical results obtained from the proposed model shows good agreement with the simulated results obtained with the ATLAS device simulator.

     

Performance investigation of heterogeneous gate dielectric-gate metal engineered–gate all around-tunnel FET for RF applications

In this work, the effect of gate metal work function engineering (GME), gate bias and drain bias on the bias dependent parasitic capacitances has been studied. Further, RF Figure of merits (FOMs) such as power gains, cut-off frequency (f _T), maximum oscillation frequency (f _Max) and intrinsic delay of hetero-dielectric gate-metal-engineered gate-all-around tunnel FET (HD-GME-GAA-TFET) are studied and compared with HD-GAA-TFET. Simulation results show an appreciable improvement in RF FOMs with the application of GME architecture on GAA TFET. Further, it has been observed that GME exhibits 3.76 times enhancement and 0.017 times reduction in cut-off frequency and intrinsic delay respectively as we increase the work function difference, which makes it a promising candidate for low power switching applications. Moreover, the small signal Y-parameters have also been studied which indicates that HD-GME-GAA-TFET is a promising candidate for RF/microwave applications. All the simulations have been done using ATLAS device simulator.

     

Power quality analysis using Discrete Orthogonal S-transform (DOST)

Power quality is one of the major issues in the modern electrical power world. The widespread usage of power electronic devices and non-linear loads make the power system more vulnerable to the power quality disturbances. As the power grids are expanding more and more because of the renewable sources, it necessitates responsive detection and accurate classification of power quality disturbances for corrective measures. This paper presents a new approach for power quality analysis using an orthogonal time–frequency representation of S-transform called Discrete Orthogonal S-transform (DOST). These power quality disturbances are generated on EHV transmission line under different fault and load condition. Different power quality disturbances have been analyzed using the short time Fourier transform (STFT), discrete wavelet transform (DWT), S-transform (ST) and DOST. Different case studies validate the superiority of DOST over other transforms in a more efficient way to monitor the power quality disturbances.