Modeling and analysis of energy quantization effects on single electron inverter performance

In this paper, for the first time, the effects of energy quantization on single electron transistor (SET) inverter performance are analyzed through analytical modeling and Monte Carlo simulations. It is shown that energy quantization mainly changes the Coulomb blockade region and drain current of SET devices and thus affects the noise margin, power dissipation, and the propagation delay of SET inverter. A new analytical model for the noise margin of SET inverter is proposed which includes the energy quantization effects. Using the noise margin as a metric, the robustness of SET inverter is studied against the effects of energy quantization. A compact expression is developed for a novel parameter quantization threshold which is introduced for the first time in this paper. Quantization threshold explicitly defines the maximum energy quantization that an SET inverter logic circuit can withstand before its noise margin falls below a specified tolerance level. It is found that SET inverter designed with CT:CG=1/3 (where CT and CG are tunnel junction and gate capacitances, respectively) offers maximum robustness against energy quantization.

Properties of the gold related acceptor level in silicon

The apparent thermal activation energy of 0.56 eV and the electron thermal capture cross section of 2.0 × 10-16 cm2 are measured for the gold related acceptor level in p+ nn+ silicon diodes by isothermal current transient and DLTS techniques. Using the emission and capture rate data and a degeneracy ratio of 2, the energy separation of the trap level from the conduction band is calculated and found to have the same temperature dependence as the band gap indicating that the acceptor level is pinned with respect to the valence band a t Ev + 0.637 eV.

On the determination of energy eigenvalues and coupling strengths using duality

The Shifman-Vainshtein-Zakharov method of determining the eigenvalues and coupling strengths, from the operator product expansion, for the current correlation functions is studied in the nonrelativistic context, using the semiclassical expansion. The relationship between the low-lying eigenvalues, and the leading corrections to the imaginary-time Green function is elucidated by comparing systems which have almost identical spectra. In the case of an anharmonic oscillator it is found that with the procedure stated in the paper, that inclusion of more terms to the asymptotic expansion does not show any simple trend towards convergence to the exact values. Generalization to higher partial waves is given. In particular for the P-level of the oscillator, the procedure gives poorer results than for the S-level, although the ratio of the two comes out much better.

Energy use in Indian household sector - An actor-oriented approach

Over the years, significant changes have taken place with regard to the type as well the quantity of energy used in Indian households. Many factors have contributed in bringing these changes. These include availability of energy, security of supplies, efficiency of use, cost of device, price of energy carriers, ease of use, and external factors like technological development, introduction of subsidies, and environmental considerations. The present paper presents the pattern of energy consumption in the household sector and analyses the causalities underlying the present usage patterns. It identifies specific (groups of) actors, study their specific situations, analyse the constraints and discusses opportunities for improvement. This can be referred to ``actor-oriented'' analysis in which we understand how various actors of the energy system are making the system work, and what incentives and constraints each of these actors is experiencing. It analyses actor linkages and their impact on the fuel choice mechanism. The study shows that the role of actors in household fuel choice is significant and depends on the level of factors - micro, meso and macro. It is recommended that the development interventions should include actor-oriented tools in energy planning, implementation, monitoring and evaluation. The analysis is based on the data from the national sample survey (NSS), India. This approach provides a spatial viewpoint which permits a clear assessment of the energy carrier choice by the households and the influence of various actors. The scope of the paper is motivated and limited by suggesting and formulating a powerful analytical technique to analyse the problem involving the role of actors in the Indian household sector.

Implications of high level pseudogene transcription in Mycobacterium leprae

Background: The Mycobacterium leprae genome has less than 50% coding capacity and 1,133 pseudogenes. Preliminary evidence suggests that some pseudogenes are expressed. Therefore, defining pseudogene transcriptional and translational potentials of this genome should increase our understanding of their impact on M. leprae physiology. Results: Gene expression analysis identified transcripts from 49% of all M. leprae genes including 57% of all ORFs and 43% of all pseudogenes in the genome. Transcribed pseudogenes were randomly distributed throughout the chromosome. Factors resulting in pseudogene transcription included: 1) co-orientation of transcribed pseudogenes with transcribed ORFs within or exclusive of operon-like structures; 2) the paucity of intrinsic stem-loop transcriptional terminators between transcribed ORFs and downstream pseudogenes; and 3) predicted pseudogene promoters. Mechanisms for translational ``silencing'' of pseudogene transcripts included the lack of both translational start codons and strong Shine-Dalgarno (SD) sequences. Transcribed pseudogenes also contained multiple ``in-frame'' stop codons and high Ka/Ks ratios, compared to that of homologs in M. tuberculosis and ORFs in M. leprae. A pseudogene transcript containing an active promoter, strong SD site, a start codon, but containing two in frame stop codons yielded a protein product when expressed in E. coli. Conclusion: Approximately half of M. leprae's transcriptome consists of inactive gene products consuming energy and resources without potential benefit to M. leprae. Presently it is unclear what additional detrimental affect(s) this large number of inactive mRNAs has on the functional capability of this organism. Translation of these pseudogenes may play an important role in overall energy consumption and resultant pathophysiological characteristics of M. leprae. However, this study also demonstrated that multiple translational ``silencing'' mechanisms are present, reducing additional energy and resource expenditure required for protein production from the vast majority of these transcripts.

Allostery and conformational free energy changes in human tryptophanyl-tRNA synthetase from essential dynamics and structure networks

The interdependence of the concept of allostery and enzymatic catalysis, and they being guided by conformational mobility is gaining increased prominence. However, to gain a molecular level understanding of llostery and hence of enzymatic catalysis, it is of utter importance that the networks of amino acids participating in allostery be deciphered. Our lab has been exploring the methods of network analysis combined with molecular dynamics simulations to understand allostery at molecular level. Earlier we had outlined methods to obtain communication paths and then to map the rigid/flexible regions of proteins through network parameters like the shortest correlated paths, cliques, and communities. In this article, we advance the methodology to estimate the conformational populations in terms of cliques/communities formed by interactions including the side-chains and then to compute the ligand-induced population shift. Finally, we obtain the free-energy landscape of the protein in equilibrium, characterizing the free-energy minima accessed by the protein complexes. We have chosen human tryptophanyl-tRNA synthetase (hTrpRS), a protein esponsible for charging tryptophan to its cognate tRNA during protein biosynthesis for this investigation. This is a multidomain protein exhibiting excellent allosteric communication. Our approach has provided valuable structural as well as functional insights into the protein. The methodology adopted here is highly generalized to illuminate the linkage between protein structure networks and conformational mobility involved in the allosteric mechanism in any protein with known structure.

Correlation between conductivity or diffusivity and activation energy in amorphous solids

There exist many investigations of ionic transport in a variety of glasses. These studies exhibit strong correlation between ionic conductivity and activation energy: Typically, it is found that higher conductivity is associated with lower activation energies and vice versa. Although there are explanations for this at a phenomenological level, there is no consistent physical picture to explain the correlation between conductivity and activation energy. We have carried out molecular dynamics simulation as a function of the size of the impurity atom or diffusant (both neutral and charged) in a host amorphous matrix. We find that there is a maximum in self-diffusivity as a function of the size of the impurity atom suggesting that there is an appropriate size for which the diffusivity is maximum. The activation energy is found to be the lowest for this size of the impurity. A similar maximum has been previously found in other condensed phases, such as confined fluids and dense liquids, and has its origin in the levitation effect. The implications of this result for understanding ionic conductivity in glasses are discussed. Our results suggest that there is a relation between microscopic structure of the amorphous solid, diffusivity or conductivity, and activation energy. The nature of this relationship is discussed in terms of the levitation parameter showing that diffusivity is maximum when the size of the neck or doorway radius is comparable with the size of the diffusant. Our computational results here are in excellent agreement with independent experimental results of Nascimento et al. [Braz. J. Phys. 35, 626 (2005)] that structural features of the glass are important in determining the ionic conductivity.

Analysis of Energy Quantization Effects on Single-Electron Transistor Circuits

In this paper, the effects of energy quantization on different single-electron transistor (SET) circuits (logic inverter, current-biased circuits, and hybrid MOS-SET circuits) are analyzed through analytical modeling and Monte Carlo simulations. It is shown that energy quantizationmainly increases the Coulomb blockade area and Coulomb blockade oscillation periodicity, and thus, affects the SET circuit performance. A new model for the noise margin of the SET inverter is proposed, which includes the energy quantization effects. Using the noise margin as a metric, the robustness of the SET inverter is studied against the effects of energy quantization. An analytical expression is developed, which explicitly defines the maximum energy quantization (termed as ``quantization threshold'') that an SET inverter can withstand before its noise margin falls below a specified tolerance level. The effects of energy quantization are further studiedfor the current-biased negative differential resistance (NDR) circuitand hybrid SETMOS circuit. A new model for the conductance of NDR characteristics is also formulated that explains the energy quantization effects.

Multiple contour extraction from graylevel images using an artificial neural network

For active contour modeling (ACM), we propose a novel self-organizing map (SOM)-based approach, called the batch-SOM (BSOM), that attempts to integrate the advantages of SOM- and snake-based ACMs in order to extract the desired contours from images. We employ feature points, in the form of ail edge-map (as obtained from a standard edge-detection operation), to guide the contour (as in the case of SOM-based ACMs) along with the gradient and intensity variations in a local region to ensure that the contour does not "leak" into the object boundary in case of faulty feature points (weak or broken edges). In contrast with the snake-based ACMs, however, we do not use an explicit energy functional (based on gradient or intensity) for controlling the contour movement. We extend the BSOM to handle extraction of contours of multiple objects, by splitting a single contour into as many subcontours as the objects in the image. The BSOM and its extended version are tested on synthetic binary and gray-level images with both single and multiple objects. We also demonstrate the efficacy of the BSOM on images of objects having both convex and nonconvex boundaries. The results demonstrate the superiority of the BSOM over others. Finally, we analyze the limitations of the BSOM.

Elucidation of the conformational free energy landscape in H.pylori LuxS and its implications to catalysis

Background: One of the major challenges in understanding enzyme catalysis is to identify the different conformations and their populations at detailed molecular level in response to ligand binding/environment. A detail description of the ligand induced conformational changes provides meaningful insights into the mechanism of action of enzymes and thus its function. Results: In this study, we have explored the ligand induced conformational changes in H. pylori LuxS and the associated mechanistic features. LuxS, a dimeric protein, produces the precursor (4,5-dihydroxy-2,3-pentanedione) for autoinducer-2 production which is a signalling molecule for bacterial quorum sensing. We have performed molecular dynamics simulations on H. pylori LuxS in its various ligand bound forms and analyzed the simulation trajectories using various techniques including the structure network analysis, free energy evaluation and water dynamics at the active site. The results bring out the mechanistic details such as co operativity and asymmetry between the two subunits, subtle changes in the conformation as a response to the binding of active and inactive forms of ligands and the population distribution of different conformations in equilibrium. These investigations have enabled us to probe the free energy landscape and identify the corresponding conformations in terms of network parameters. In addition, we have also elucidated the variations in the dynamics of water co-ordination to the Zn2+ ion in LuxS and its relation to the rigidity at the active sites. Conclusions: In this article, we provide details of a novel method for the identification of conformational changes in the different ligand bound states of the protein, evaluation of ligand-induced free energy changes and the biological relevance of our results in the context of LuxS structure-function. The methodology outlined here is highly generalized to illuminate the linkage between structure and function in any protein of known structure.

Control of barrier height of MIS tunnel diodes using deep level impurities

The barrier height of MIS tunnel diodes is studied considering the effect of deep impurities. It is shown that the barrier height of a given MIS-system can be controlled by changing the density and the activation energy of the defect level. The study leads to the conclusion that deep impurities of character opposite to shallow impurities enhance the barrier height. On the other hand, the barrier height is lowered when the type of the deep impurities is the same as that of shallow impurities.

In-Network Computation in Random Wireless Networks: A PAC Approach to Constant Refresh Rates with Lower Energy Costs

We propose a method to compute a probably approximately correct (PAC) normalized histogram of observations with a refresh rate of Theta(1) time units per histogram sample on a random geometric graph with noise-free links. The delay in computation is Theta(root n) time units. We further extend our approach to a network with noisy links. While the refresh rate remains Theta(1) time units per sample, the delay increases to Theta(root n log n). The number of transmissions in both cases is Theta(n) per histogram sample. The achieved Theta(1) refresh rate for PAC histogram computation is a significant improvement over the refresh rate of Theta(1/log n) for histogram computation in noiseless networks. We achieve this by operating in the supercritical thermodynamic regime where large pathways for communication build up, but the network may have more than one component. The largest component however will have an arbitrarily large fraction of nodes in order to enable approximate computation of the histogram to the desired level of accuracy. Operation in the supercritical thermodynamic regime also reduces energy consumption. A key step in the proof of our achievability result is the construction of a connected component having bounded degree and any desired fraction of nodes. This construction may also prove useful in other communication settings on the random geometric graph.

Single‐gate deep level transient spectroscopy technique

A new deep level transient spectroscopy technique is suggested which allows the deep level parameters to be obtained from a single temperature scan. Using large ratio t2/t1 of the measurement gate positions t1 and t2 and analyzing the steep high‐temperature side of the peak, it is demonstrated that the deep level activation energy can be determined with high accuracy.

Energy-Efficient Fault Tolerance in Chip Multiprocessors Using Critical Value Forwarding

Relentless CMOS scaling coupled with lower design tolerances is making ICs increasingly susceptible to wear-out related permanent faults and transient faults, necessitating on-chip fault tolerance in future chip microprocessors (CMPs). In this paper we introduce a new energy-efficient fault-tolerant CMP architecture known as Redundant Execution using Critical Value Forwarding (RECVF). RECVF is based on two observations: (i) forwarding critical instruction results from the leading to the trailing core enables the latter to execute faster, and (ii) this speedup can be exploited to reduce energy consumption by operating the trailing core at a lower voltage-frequency level. Our evaluation shows that RECVF consumes 37% less energy than conventional dual modular redundant (DMR) execution of a program. It consumes only 1.26 times the energy of a non-fault-tolerant baseline and has a performance overhead of just 1.2%.