An accurate analytical I-V model for sub-90-nm MOSFETs and its application to read static noise margin modeling

We propose an accurate model to describe the I-V characteristics of a sub-90-nm metal-oxide-semiconductor field-effect transistor(MOSFET) in the linear and saturation regions for fast analytical calculation of the current.The model is based on the BSIM3v3 model.Instead of using constant threshold voltage and early voltage,as is assumed in the BSIM3v3 model,we define these voltages as functions of the gate-source voltage.The accuracy of the model is verified by comparison with HSPICE for the 90-,65-,45-,and 32-nm CMOS technologies.The model shows better accuracy than the nth-power and BSIM3v3 models.Then,we use the proposed I-V model to calculate the read static noise margin(SNM) of nano-scale conventional 6T static random-access memory(SRAM) cells with high accuracy.We calculate the read SNM by approximating the inverter transfer voltage characteristic of the cell in the regions where vertices of the maximum square of the butterfly curves are placed.The results for the SNM are also in excellent agreement with those of the HSPICE simulation for 90-,65-,45-,and 32-nm technologies.Verification in the presence of process variations and negative bias temperature instability(NBTI) shows that the model can accurately predict the minimum supply voltage required for a target yield.     

PTC effect in HDPE filled with carbon blacks modified by Ni and Au metallic particles

Several types of positive temperature coefficient (PTC) composites are prepared by using Ni and Au modified carbon black. The major aim of this work was the lowering of the room temperature resistivity of the composites by enhancement of electrical conduction of the CB particles by incorporating metallic particles. Investigations showed that the metal particles fill the cavities and surface defects of the CB and thus surface free area reduces after modification. Metallic particles also change the nature of the CB particles after modification. Several types of PTC composites were prepared by using modified and unmodified CB by several loading level of filler. Measuring electrical properties of the PTC samples showed that the Ni modified CB reduce room temperature resistivity to lower than that of PTC composites prepared by unmodified CB. PTC composites prepared by Au modified CBs showed very different properties compared to PTC composites prepared by Ni modified CB. Their resistivities were quite higher than the others showing a poor compatibility between the matrix and Au modified CB. The effect of thermal annealing also investigated on the electrical properties of the prepared composites. Room temperature resistivities reduced for most of the samples while PTC intensities increased after annealing. Theoretical bases are employed to discuss the room temperature resistivity and PTC behavior of the composites before and after annealing. © 2007 Wiley Periodicals, Inc. J Appl Polym Sci 2007     

Preparation of ABS/montmorillonite nanocomposite using a solvent/non-solvent method

Polymer layered silicate nanocomposites have been studied for many years and due to their distinguished properties and applications, it is still the subject of many research programs. There are different methods of preparation, with the melt intercalation method as the mostly used method. Due to the thermal destructive effects of melt mixing on the polymer chains there are currently efforts to develop some new methods of preparation. A solvent/non-solvent method has been developed in this study for the preparation of ABS/clay nanocomposites. ABS nanocomposite is precipitated after addition of ethanol (non-solvent) containing organic modified montmorillonite from a THF solution while it is stirring. A kind of mixing system known as homogenizer has been used in this work. The final product has been determined having an intercalated structure with a uniform interlayer spacing of the silicate layers. The ABS nanocomposites prepared in this work has been studied by X-ray diffraction, FTIR, transmission electron microscope and thermogravimetric analysis. The effect of using homogenizer on the characteristics of the nanocomposites also has been investigated and discussed in several parts of the present work.     

Weighted and constrained possibilistic C-means clustering for online fault detection and isolation

In this paper, a new weighted and constrained possibilistic C-means clustering algorithm is proposed for process fault detection and diagnosis (FDI) in offline and online modes for both already known and novel faults. A possibilistic clustering based approach is utilized here to address some of the deficiencies of the fuzzy C-means (FCM) algorithm leading to more consistent results in the context of the FDI tasks by relaxing the probabilistic condition in FCM cost function. The proposed algorithm clusters the historical data set into C different dense regions without having precise knowledge about the number of the faults in the data set. The algorithm incorporates simultaneously possibilistic algorithm and local attribute weighting for time-series segmentation. This allows different weights to be allocated to different features responsible for the distinguished process faults which is an essential characteristic of proper FDI operations. A set of comparative studies have been carried out on the large-scale Tennessee Eastman industrial challenge problem and the DAMADICS actuator benchmark to demonstrate the superiority of the proposed algorithm in process FDI applications with respect to some available alternative approaches.     

Fabrication of a novel electrochemiluminescence glucose biosensor using Au nanoparticles decorated multiwalled carbon nanotubes

Au nanoparticles (nanoAu) with an average diameter of 60 nm were decorated on the surface of multiwalled carbon nanotubes to prepare MWCNTs-nanoAu nano-hybrids. The MWCNTs-nanoAu nano-hybrids were cast on the surface of a glassy carbon electrode and were then further modified with a layer comprising glucose oxidase and chitosan to fabricate a novel electrochemiluminescence (ECL) glucose biosensor. The biosensor showed a remarkably improved electrocatalytic activity towards luminol oxidation and significant improvement in its ECL response. The proposed ECL biosensor exhibited excellent performance for glucose detection with a wide linear range (1-1000 μM), low detection limit (0.5 μM), excellent reproducibility (0.5%) and satisfactory selectivity.     

Model interoperability via Model Driven Development

Among the factors that contribute to the inherent complexity of the software development process is the gap between the design and the formal analysis domains. Software design is often considered a human oriented task while the analysis phase draws on formal representation and mathematical foundations. An example of this dichotomy is the use of UML for the software design phase and Petri Nets for the analysis; a separation of concerns that leads to the creation of heterogeneous models. Although UML is widely accepted as a language that can be used to model the structural and behavioural aspects of a system, its lack of mathematical foundations is seen as a serious impediment to rigorous analysis. Petri Nets on the other hand have a strong mathematical basis that are well suited for formal analysis; they lack however the appeal and the ease-of-use of UML. A pressing concern for software developers is how to bridge the gap between these domains and allow for model interoperability and the integration of different toolsets across them, and thus reduce the complexity of the software development process. The aim of this paper is to present a Model Driven Development (MDD) model transformation which supports a seamless transition between UML and Petri Nets. This is achieved by model interoperability from UML Sequence Diagrams to Petri Nets and supported by tool integration. The model transformation framework allows a software system to be designed in terms of UML Sequence Diagrams and subjected to formal analysis by taking advantage of the strong mathematical framework of Petri Nets. The behaviour of a Personal Area Network will be used to illustrate the proposed approach and to highlight model interoperability and tool integration through the design, the transformation and the analysis phases.     

Design and Implementation of an Inverse Dynamics Controller for Uncertain Nonholonomic Robotic Systems

This paper addresses the trajectory tracking control problem of nonholonomic robotic systems in the presence of modeling uncertainties. A tracking controller is proposed such that it combines the inverse dynamics control technique and an adaptive robust PID control strategy to preserve robustness to both parametric and nonparametric uncertainties. A SPR-Lypunov stability analysis demonstrates that tracking errors are uniformly ultimately bounded (UUB) and exponentially converge to a small ball containing the origin. The proposed inverse dynamics tracking controller is successfully applied to a nonholonomic wheeled mobile robot (WMR) and experimental results are presented to validate the effectiveness of the proposed controller.     

ZnO nanoparticles and polyaniline blend as an active layer for bulk heterojunction solar cell applications

In this work, a facile and straightforward procedure was introduced to prepare a blend as an active layer for hybrid solar cell applications. The active layer consisting of a blend of ZnO nanoparticles (NPs) and polyaniline (PANI) dispersions was deposited by spin coating on ITO covered glasses. The current density–voltage characteristics were studied under AM1.5G standard illumination, without any encapsulation process. Also, the samples were studied using UV–Vis spectroscopy, energy dispersive X-ray spectroscopy (EDS) and field emission-scanning electron microscopy. The investigation is limited just to the active layer, so the cells were fabricated without any interlayer. The effect of various volume ratios of ZnO–NPs:PANI solutions, thickness and the annealing temperature of the active layer on the open circuit voltage and the short circuit current density of the cells were investigated. Moreover, the blending time of ZnO–NPs:PANI dispersions as a significant factor for achieving the optimum results were studied.     

Optical and Structure Properties of Nanocrystalline Titania Powders with Cu Dopant

TiO₂ nanopowders doped by Cu were prepared by the sol–gel method. The effects of Cu doping on the structural, optical, and photo-catalytic properties of titania nanopowders have been studied by X-ray diffraction (XRD), scanning electron microscopy (SEM), transmission electron microscopy (TEM), and UV–Vis absorption spectroscopy. XRD results suggest that adding impurities has a significant effect on anatase phase stability, crystallinity, and particle size of TiO₂. Titania rutile phase formation in the system (Ti–Cu) was promoted by Cu²⁺ doped TiO₂. The photo-catalytic activity was evaluated by photo-catalytic degradation kinetics of aqueous methylene orange (MO) under visible radiation. The results show that the photo-catalytic activity of the 5 %Cu doped TiO₂ nanopowders has a larger degradation efficiency than pure TiO ₂ under visible light. Also, the minimum band gap was estimated to be ～ 1.9–2 eV from UV–Vis spectra.     

The effect of graphene oxide on UV curing kinetics and properties of SU8 nanocomposites

In the present study SU8 nanocomposites were prepared by incorporating graphene oxide (GO ), and its effect on the UV curing kinetics, morphology, electrical, hardness and thermal properties of the nanocomposites were investigated at different loading levels of GO (0.1 ? 3 wt%). Studying the reaction kinetics of the UV curing process by means of real‐time infrared spectroscopy showed that the polymerization rate and the final conversion of epoxy groups was related to the loading level of GO in the nanocomposites. An autocatalytic kinetics model of the curing reaction confirmed the effect of GO nanoparticles on the curing rate constant (k ), the order of the initiation reaction (m ) and the ultimate conversion of the UV ‐cured nanocomposites. Appropriate experimental observations indicated that dispersion of GO within the resin plays a critical role on the cure kinetics and final conversion. The results of the kinetics modeling and morphological observations showed that the curing rate constant of the nanocomposites is highly dependent on the GO content and its dispersion state, indicating that GO prevents epoxy resin crosslinking by photoinitator deactivation. Moreover, oxygen functionalities, such as hydroxyl and carboxyl groups, on the surface of GO facilitate interfacial interactions between epoxy groups from the matrix and GO . Electrical conductivity measurements demonstrated that the UV ‐induced photo‐cured GO filled resins are conductive SU8 nanocomposites. It was observed that the thermal stability of the nanocomposites is enhanced due to the dispersion of GO in the matrix. Moreover, the microhardness analysis showed that addition of GO to neat SU8 increases the mechanical hardness of the nanocomposite. © 2016 Society of Chemical Industry