A statistical-based material and process guidelines for design of carbon nanotube field-effect transistors in gigascale integrated circuits

Carbon nanotube field-effect transistors (CNFETs) show great promise as building blocks of future integrated circuits. However, synthesizing single-walled carbon nanotubes (CNTs) with accurate chirality and exact positioning control has been widely acknowledged as an exceedingly complex task. Indeed, density and chirality variations in CNT growth can compromise the reliability of CNFET-based circuits. In this paper, we present a novel statistical compact model to estimate the failure probability of CNFETs to provide some material and process guidelines for the design of CNFETs in gigascale integrated circuits. We use measured CNT spacing distributions within the framework of detailed failure analysis to demonstrate that both the CNT density and the ratio of metallic to semiconducting CNTs play dominant roles in defining the failure probability of CNFETs. Besides, it is argued that the large-scale integration of these devices within an integrated circuit will be feasible only if a specific range of CNT density with an acceptable ratio of semiconducting to metallic CNTs can be adjusted in a typical synthesis process.     

Measurement of Urbach edge and midgap states in amorphous silicon p-i-n devices

Urbach energy of valence band tails and mid-gap defect densities are important parameters for determining the performance of amorphous silicon (a-Si:H) devices. In this paper, we examine a technique which allows one to determine these parameters in device structures, as opposed to in films. The technique consists of measuring sub-gap quantum efficiency as a function of reverse bias and photon wavelength. We show that there is a distinction between the response of tail states and mid-gap states to the application of reverse bias, and that by analyzing these differences, one can locate the energies of the mid-gap states in the device. The technique gives an accurate measurement of Urbach edge of tail states, even on textured substrates, but only estimates mid-gap states within a factor of 2.     

In-process regressions and adaptive multicriteria neural networks for monitoring and supervising machining operations

The authors develop a monitoring and supervising system for machining operations using in-process regressions (for monitoring) and adaptive feedforward artificial neural networks (for supervising). The system is designed for: (1) in-process tool life measurement and prediction; (2) supervision of machining operations in terms of the best machining setup; and (3) catastrophic tool failure monitoring. The monitoring system predicts tool life by using different sensors for gathering information based on a regression model that allows for the variations between tools and different machine setups. The regression model makes its prediction by using the history of other tools and combining it with the information obtained about the tool under consideration. The supervision system identifies the best parameters for the machine setup problem within the framework of multiple criteria decision making. The decision maker (operator) considers several criteria, such as cutting quality, production rate and tool life. To make the optimal decision with several criteria, an adaptive feedforward artificial neural network is used to assess the decision maker's preferences. The authors' neural network approach learns from the decision maker's complex behavior and hence, in automatic mode, can make decisions for the decision maker. The approach is not computationally demanding, and experiments demonstrate that its predictions are accurate.     

Manipulations of germ-cell populations in the gonad of the fowl

Prehistoric populations suffered the rigors of everyday survival as hunter-gatherers, and some of the individuals had osseous manifestations as a result both of these stresses and of aging. Paleomedical scientists usually seek out osseous abnormalities found in skeletal remains, thus stressing the morbidity of a population [4]. In so doing, they portray those populations as less healthy than their own. This may not necessarily be the case. Specimens without signs of injury should be considered as evidence of the population's vitality; bones with evidence of injury that has healed during life should be considered as evidence of debility; and bones with evidence of conditions that are occupational in origin should be considered as evidence of social, economic, and ecological environmental conditions [4]. This is more useful than singling out specimens with abnormalities as signs of the population's morbidity [4]. This is confirmed by the majority of bones appearing osteologically healthy, except for the characteristic findings of biomechanical wear and tear arising from acquiring food and from combat (osteoarthritis, fractures). Although a number of children may have been infected by the treponematoses, which were manifested by cutaneous lesions, only a small percentage of children actually experienced osseous infection. Also, bone metastases were extremely rare.     

A Method of Examining in Detail Electric Arc Furnace Performance

A method of data acquisition and analysis is described that has been developed to assess in detail the performance of electric arc furnaces. The method has been implemented on a small single user minicomputer (a PDP 11/40) and on a large mainframe (an IBM 3033). The method was specifically developed in order to determine reliable statistical parameters that can be used to characterize arc furnace performance. The method is outlined, and its use is illustrated using data recorded on magnetic tape at the new Iron and Steel Company of Trinidad and Tobago (ISCOTT) plant. Results are presented that illustrate the operation of the ISCOTT furnace for scrap and pellet feed.     

Melt‐blowing thermoplastic polyurethane and polyether‐block‐amide elastomers: Effect of processing conditions and crystallization on web properties

Melt‐blown webs from ester and ether thermoplastic polyurethanes and polyether‐block‐amide (PEBA) elastomers were produced at different die‐to‐collector distances (DCD) to study the correlation between the polymer type and hardness, melt‐blowing process conditions, and web properties. An experimental set up was built to measure the air temperature and velocity profiles below and across the melt‐blowing die to correlate the fiber formation process and polymer crystallization behavior to process conditions and web properties. It was shown that air temperature and velocity profiles follow similar trends with increasing distance below the melt‐blowing die: both drop rapidly until reaching a plateau region approximately 5–6 cm below the die. Thereafter, they remain relatively constant with further increasing distance. It was found that crystallization onset and peak temperatures of all block copolymers in this study fall within this region of rapid velocity and temperature drop. This suggests that the polymers have already started to crystallize and solidify before reaching the collector, the extent of which depends on the crystallization kinetics of the polymer. The strong influence of the crystallization kinetics on web strength was clearly demonstrated in the PEBA series. In particular, the hardest grade produced the lowest web strength mainly because of its high crystallization rate and crystallization onset temperature. It is concluded that the melt‐blown web strength is strongly dependent on the degree of fiber‐to‐fiber adhesion within the web, which is determined by the amount of fiber solidification that occurs prior to the collector. The crystallization kinetics of the polymer and the distances traveled between the die and collector or the exposure time of the polymer melt to process and ambient air were shown to be critical in the amount of fiber solidification attained. POLYM. ENG. SCI., 2009. © 2009 Society of Plastics Engineers     

Quantum Entanglement and Cryptography for Automation and Control of Dynamic Systems

This paper addresses the application of quantum entanglement and cryptography for automation and control of dynamic systems.A dynamic system is a system where t...     

Experimental investigation into Fe3O4/SiO2 nanoparticle performance and comparison with other nanofluids in enhanced oil recovery

Nanofluids because of their surface characteristics improve the oil production from reservoirs by enabling different enhanced recovery mechanisms such as wettability alteration, interfacial tension (IFT) reduction, oil viscosity reduction, formation and stabilization of colloidal systems and the decrease in the asphaltene precipitation. To the best of the authors’ knowledge, the synthesis of a new nanocomposite has been studied in this paper for the first time. It consists of nanoparticles of both SiO₂ and Fe₃O₄. Each nanoparticle has its individual surface property and has its distinct effect on the oil production of reservoirs. According to the previous studies, Fe₃O₄ has been used in the prevention or reduction of asphaltene precipitation and SiO₂ has been considered for wettability alteration and/or reducing IFTs in enhanced oil recovery. According to the experimental results, the novel synthesized nanoparticles have increased the oil recovery by the synergistic effects of the formed particles markedly by activating the various mechanisms relative to the use of each of the nanoparticles in the micromodel individually. According to the results obtained for the use of this nanocomposite, understanding reservoir conditions plays an important role in the ultimate goal of enhancing oil recovery and the formation of stable emulsions plays an important role in oil recovery using this method.     

Introducing four different branch structures in PET by reactive processing––A rheological investigation

Chain extension/branching by reactive processing is a well-known method to enhance the rheological properties of polymers. In this study, pyromellitic dianhydride, poly(glycolic acid), triglycidyl isocyanurate, and bisphenol A diglycidyl ether were used as chain extender/branching agents to produce branched Polyethylene terephthalate (PETs) with four different molecular structures. According to the linear rheological characterizations, the storage modulus and complex viscosity of modified PET samples enhanced significantly after branching. The shear viscosities of modified PET show a pronounced shear-thinning behavior and a remarkable increase at low frequencies, which can be an indication of the existence of long-chain branches (LCBs) in the molecular structure of polymer and broadening the molecular weight distribution. Fourier transform infrared (FTIR) and differential scanning calorimetry (DSC) analysis were used to investigate the effect of branching agents on the chemical structure and thermal properties of PET, respectively. DSC results show that higher amounts of LCBs lead to lower melting and crystallization temperatures.