Studies of multiple ionization in the RF spark and vacuum vibrator arc ion sources

Relative abundance distributions of multiply-charged ionic species have been measured for the RF spark and vacuum vibrator are ion sources, for a number of elements. An attempt has been made to explain the observed charge state distribution on the basis of models for the arc and spark plasma. The difficulties in the way of explaining the observed charge state distributions, using the LTE model with Saha distribution as well as the corona model, are pointed out. The distribution can be explained by a diffusion-dominated plasma model with known or calculated values for ionization cross-sections, the single impact model being suitable for the RF spark and the multiple impact model for the vibrator arc.

CAE-based prediction of projectile residual velocity for impact on single and multi-layered metallic armour plates

The present, paper deals with the CAE-based study Of impact of jacketed projectiles on single- and multi-layered metal armour plates using LS-DYNA. The validation of finite element modelling procedure is mainly based on the mesh convergence study using both shell and solid elements for representing single-layered mild steel target plates. It, is shown that the proper choice of mesh density and the strain rate-dependent material properties are essential for all accurate prediction of projectile residual velocity. The modelling requirements are initially arrived at by correlating against test residual velocities for single-layered mild steel plates of different depths at impact velocities in the ran.-c of approximately 800-870 m/s. The efficacy of correlation is adjudged, in terms of a 'correlation index', defined in the paper: for which values close to unity are desirable. The experience gained for single-layered plates is next; used in simulating projectile impacts on multi-layered mild steel target plates and once again a high degree of correlation with experimental residual velocities is observed. The study is repeated for single- and multi-layered aluminium target plates with a similar level of success in test residual velocity prediction. TO the authors' best knowledge, the present comprehensive study shows in particular for the first time that, with a. proper modelling approach, LS-DYNA can be used with a great degree of confidence in designing perforation-resistant single and multi-layered metallic armour plates.

Impact of energy quantisation in single electron transistor island on hybrid complementary metal oxide semiconductor-single electron transistor integrated circuits

For the first time, the impact of energy quantisation in single electron transistor (SET) island on the performance of hybrid complementary metal oxide semiconductor (CMOS)-SET transistor circuits has been studied. It has been shown through simple analytical models that energy quantisation primarily increases the Coulomb Blockade area and Coulomb Blockade oscillation periodicity of the SET device and thus influences the performance of hybrid CMOS-SET circuits. A novel computer aided design (CAD) framework has been developed for hybrid CMOS-SET co-simulation, which uses Monte Carlo (MC) simulator for SET devices along with conventional SPICE for metal oxide semiconductor devices. Using this co-simulation framework, the effects of energy quantisation have been studied for some hybrid circuits, namely, SETMOS, multiband voltage filter and multiple valued logic circuits. Although energy quantisation immensely deteriorates the performance of the hybrid circuits, it has been shown that the performance degradation because of energy quantisation can be compensated by properly tuning the bias current of the current-biased SET devices within the hybrid CMOS-SET circuits. Although this study is primarily done by exhaustive MC simulation, effort has also been put to develop first-order compact model for SET that includes energy quantisation effects. Finally, it has been demonstrated that one can predict the SET behaviour under energy quantisation with reasonable accuracy by slightly modifying the existing SET compact models that are valid for metallic devices having continuous energy states.

Impact of Energy Quantization on the Performance of Current-Biased SET Circuits

The current-biased single electron transistor (SET) (CBS) is an integral part of almost all hybrid CMOS SET circuits. In this paper, for the first time, the effects of energy quantization on the performance of CBS-based circuits are studied through analytical modeling and Monte Carlo simulations. It is demonstrated that energy quantization has no impact on the gain of the CBS characteristics, although it changes the output voltage levels and oscillation periodicity. The effects of energy quantization are further studied for two circuits: negative differential resistance (NDR) and neuron cell, which use the CBS. A new model for the conductance of NDR characteristics is also formulated that includes the energy quantization term.

Climate change impact assessment: Uncertainty modeling with imprecise probability

Hydrologic impacts of climate change are usually assessed by downscaling the General Circulation Model (GCM) output of large-scale climate variables to local-scale hydrologic variables. Such an assessment is characterized by uncertainty resulting from the ensembles of projections generated with multiple GCMs, which is known as intermodel or GCM uncertainty. Ensemble averaging with the assignment of weights to GCMs based on model evaluation is one of the methods to address such uncertainty and is used in the present study for regional-scale impact assessment. GCM outputs of large-scale climate variables are downscaled to subdivisional-scale monsoon rainfall. Weights are assigned to the GCMs on the basis of model performance and model convergence, which are evaluated with the Cumulative Distribution Functions (CDFs) generated from the downscaled GCM output (for both 20th Century [20C3M] and future scenarios) and observed data. Ensemble averaging approach, with the assignment of weights to GCMs, is characterized by the uncertainty caused by partial ignorance, which stems from nonavailability of the outputs of some of the GCMs for a few scenarios (in Intergovernmental Panel on Climate Change [IPCC] data distribution center for Assessment Report 4 [AR4]). This uncertainty is modeled with imprecise probability, i.e., the probability being represented as an interval gray number. Furthermore, the CDF generated with one GCM is entirely different from that with another and therefore the use of multiple GCMs results in a band of CDFs. Representing this band of CDFs with a single valued weighted mean CDF may be misleading. Such a band of CDFs can only be represented with an envelope that contains all the CDFs generated with a number of GCMs. Imprecise CDF represents such an envelope, which not only contains the CDFs generated with all the available GCMs but also to an extent accounts for the uncertainty resulting from the missing GCM output. This concept of imprecise probability is also validated in the present study. The imprecise CDFs of monsoon rainfall are derived for three 30-year time slices, 2020s, 2050s and 2080s, with A1B, A2 and B1 scenarios. The model is demonstrated with the prediction of monsoon rainfall in Orissa meteorological subdivision, which shows a possible decreasing trend in the future.

A conditional random field-based downscaling method for assessment of climate change impact on multisite daily precipitation in the Mahanadi basin

Downscaling to station-scale hydrologic variables from large-scale atmospheric variables simulated by general circulation models (GCMs) is usually necessary to assess the hydrologic impact of climate change. This work presents CRF-downscaling, a new probabilistic downscaling method that represents the daily precipitation sequence as a conditional random field (CRF). The conditional distribution of the precipitation sequence at a site, given the daily atmospheric (large-scale) variable sequence, is modeled as a linear chain CRF. CRFs do not make assumptions on independence of observations, which gives them flexibility in using high-dimensional feature vectors. Maximum likelihood parameter estimation for the model is performed using limited memory Broyden-Fletcher-Goldfarb-Shanno (L-BFGS) optimization. Maximum a posteriori estimation is used to determine the most likely precipitation sequence for a given set of atmospheric input variables using the Viterbi algorithm. Direct classification of dry/wet days as well as precipitation amount is achieved within a single modeling framework. The model is used to project the future cumulative distribution function of precipitation. Uncertainty in precipitation prediction is addressed through a modified Viterbi algorithm that predicts the n most likely sequences. The model is applied for downscaling monsoon (June-September) daily precipitation at eight sites in the Mahanadi basin in Orissa, India, using the MIROC3.2 medium-resolution GCM. The predicted distributions at all sites show an increase in the number of wet days, and also an increase in wet day precipitation amounts. A comparison of current and future predicted probability density functions for daily precipitation shows a change in shape of the density function with decreasing probability of lower precipitation and increasing probability of higher precipitation.

Impact of substrate nitridation on the photoluminescence and photovoltaic characteristics of GaN grown on p-Si (100) by molecular beam epitaxy

This report focuses on the structural and optical properties of the GaN films grown on p-Si (100) substrates along with photovoltaic characteristics of GaN/p-Si heterojunctions fabricated with substrate nitridation and in absence of substrate nitridation. The high resolution X-ray diffraction (HRXRD), atomic force microscopy (AFM), Raman and photoluminescence (PL) spectroscopic studies reveal that the significant enhancement in the structural as well as in the optical properties of GaN epifilms grown with silicon nitride buffer layer when compared with the sample grown without silicon nitride buffer layer. The low temperature PL shows a free excitonic (FX) emission peak at 3.51 eV at the temperature of 5 K with a very narrow line width of 35 meV. Temperature dependent PL spectra follow the Varshni equation well and peak energy blue shifts by similar to 63 meV from 300 to 5 K. Raman data confirms the strain free nature and reasonably good crystallinity of the films. The GaN/p-Si heterojunctions fabricated without substrate nitridation show a superior photovoltaic performance compared to the devices fabricated in presence of substrate nitridation. The discussions have been carried out on the junction properties. Such single junction devices exhibit a promising fill factor and conversion efficiency of 23.36 and 0.12 %, respectively, under concentrated AM1.5 illumination.

Mixture of Fuels Approach for the Synthesis of SrFeO3-delta Nanocatalyst and Its Impact on the Catalytic Reduction of Nitrobenzene

A modified solution combustion approach was applied in the synthesis of nanosize SrFeO3-delta (SFO) using single as well as mixture of citric acid, oxalic acid, and glycine as fuels with corresponding metal nitrates as precursors. The synthesized and calcined powders were characterized by Fourier transform infrared spectroscopy (FT-IR), X-ray diffraction (XRD), thermogravimetric analysis and derivative thermogravimetric analysis (TG-DTG), scanning electron microscopy, transmission electron microscopy, N-2 physisorption methods, and acidic strength by n-butyl amine titration methods. The FT-IR spectra show the lower-frequency band at 599 cm(-1) corresponds to metal-oxygen bond (possible Fe-O stretching frequencies) vibrations for the perovskite-structure compound. TG-DTG confirms the formation temperature of SFO ranging between 850-900 degrees C. XRD results reveal that the use of mixture of fuels in the preparation has effect on the crystallite size of the resultant compound. The average particle size of the samples prepared from single fuels as determined from XRD was similar to 50-35 nm, whereas for samples obtained from mixture of fuels, particles with a size of 30-25 nm were obtained. Specifically, the combination of mixture of fuels for the synthesis of SFO catalysts prevents agglomeration of the particles, which in turn leads to decrease in crystallite size and increase in the surface area of the catalysts. It was also observed that the present approach also impacted the catalytic activity of the SFO in the catalytic reduction of nitrobenzene to azoxybenzene.

Impact of glycosylation on stability, structure and unfolding of soybean agglutinin (SBA): an insight from thermal perturbation molecular dynamics simulations

Glycosylation has been recognized as one of the most prevalent and complex post-translational modifications of proteins involving numerous enzymes and substrates. Its effect on the protein conformational transitions is not clearly understood yet. In this study, we have examined the effect of glycosylation on protein stability using molecular dynamics simulation of legume lectin soybean agglutinin (SBA). Its glycosylated moiety consists of high mannose type N-linked glycan (Man(9)GlcNAc(2)). To unveil the structural perturbations during thermal unfolding of these two forms, we have studied and compared them to the experimental results. From the perspective of dynamics, our simulations revealed that the nonglycosylated monomeric form is less stable than corresponding glycosylated form at normal and elevated temperatures. Moreover, at elevated temperature thermal destabilization is more prominent in solvent exposed loops, turns and ends of distinct beta sheets. SBA maintains it folded structure due to some important saltbridges, hydrogen bonds and hydrophobic interactions within the protein. The reducing terminal GlcNAc residues interact with the protein residues VAL161, PRO182 and SER225 via hydrophobic and via hydrogen bonding with ASN 9 and ASN 75. Our simulations also revealed that single glycosylation (ASN75) has no significant effect on corresponding cis peptide angle orientation. This atomistic description might have important implications for understanding the functionality and stability of Soybean agglutinin.