Home Automation Using Augmented Reality (HAAR)

Wireless Personal Communications - The development of Smart Home Controllers has seen rapid growth in recent years, especially for smart devices, that can utilize the Internet of Things (IoT)....     

On the Growth of Thin-Film AlGaN/GaN Epitaxial Heterostructures on Hybrid Substrates Containing Layers of Silicon Carbide and Porous Silicon

Semiconductors - Abstract—In our work, we carry out a structural-spectroscopic study of AlGaN/GaN epitaxial layers grown by molecular-beam epitaxy with nitrogen-plasma activation on a hybrid...     

Long Duration Persistent Photocurrent in 3 nm Thin Doped Indium Oxide for Integrated Light Sensing and In-Sensor Neuromorphic Computation

Miniaturization and energy consumption by computational systems remain major challenges to address. Optoelectronics based synaptic and light sensing provide an exciting platform for neuromorphic processing and vision applications offering several advantages. It is highly desirable to achieve single-element image sensors that allow reception of information and execution of in-memory computing processes while maintaining memory for much longer durations without the need for frequent electrical or optical rehearsals. In this work, ultra-thin (<3 nm) doped indium oxide (In₂O₃) layers are engineered to demonstrate a monolithic two-terminal ultraviolet (UV) sensing and processing system with long optical state retention operating at 50 mV. This endows features of several conductance states within the persistent photocurrent window that are harnessed to show learning capabilities and significantly reduce the number of rehearsals. The atomically thin sheets are implemented as a focal plane array (FPA) for UV spectrum based proof-of-concept vision system capable of pattern recognition and memorization required for imaging and detection applications. This integrated light sensing and memory system is deployed to illustrate capabilities for real-time, in-sensor memorization, and recognition tasks. This study provides an important template to engineer miniaturized and low operating voltage neuromorphic platforms across the light spectrum based on application demand.     

An Approach for Enhancement of Saturation Magnetization in Cobalt Ferrite Nanoparticles by Incorporation of Terbium Cation

Cobalt ferrite nanoparticles were synthesized by a reverse micelle process. The optimum processing conditions required to fabricate nanocrystalline cobalt ferrite using a reverse micelle technique, especially the effect of water-to-surfactant molar ratios including w = 8, 10, 12, and 14, pH values in the range of 8 to 11, and annealing temperatures in the range of 400°C to 800°C, were evaluated. x-Ray diffraction (XRD), field-emission scanning electron microscopy (FE-SEM), vibrating-sample magnetometry, and superconducting quantum interference device analysis were employed to evaluate the structural and magnetic properties of synthesized nanoparticles. XRD analysis confirms that the nanoparticles have a single-phase cubic spinel structure. The average particle size increases with increasing pH value and annealing temperature. Magnetization study reveals that the cobalt ferrite nanoparticles exhibit a superparamagnetic trend. The zero-field-cooled magnetization curves of cobalt ferrite nanoparticles indicated that, with an increase in pH value, the blocking temperature increases. Based on the obtained optimum parameters, terbium-substituted cobalt ferrite nanoparticles with composition CoFe_2?x Tb _x O₄ (x = 0.1 to 0.5) were prepared by a reverse micelle process. XRD and field-emission scanning electron microscopy evaluation demonstrated that single-phase spinel ferrites with narrow size distribution were obtained. Mössbauer spectroscopy was used to determine the site preference of terbium cation. The results confirm that terbium cations were distributed at tetrahedral and octahedral sites, but with a preference for the former. It was observed that, with an increase in terbium content, the saturation magnetization increases.     

Characterization of High-k Gate Dielectric with Amorphous Nanostructure

In the present study, Zr _x La_1?x O _y amorphous nanostructures were prepared by the sol–gel method such that the Zr atomic fraction (x) ranged from 0% to 70%. An analytical model is described for the dielectric constant (k) of Zr _x La_1?x O _y nanostructures in a metal–oxide–semiconductor (MOS) device. The structure and morphology of Zr _x La_1?x O _y film was studied using x-ray diffraction, scanning electron microscopy, atomic force microscopy, and transmission electron microscopy. Elemental qualitative analysis was performed using energy-dispersive x-ray spectra and a map that confirmed the findings. Preliminary information on the influence of thermal annealing on the morphological control of Zr _x La_1?x O _y amorphous nanostructures is presented. The dielectric constant of the crystalline Zr_0.5La_0.5O _y thin film is about 36. Electrical property characterization was performed using a metal–dielectric–semiconductor structure via capacitance–voltage and current density–voltage measurements.     

A new simple method for analysing of thermal noise in switched-capacitor filters

Thermal noise is one of the most important challenges in analogue integrated circuits design. This problem is more crucial in switched-capacitor (SC) filters due to the aliasing effect of wide-band thermal noise. In this article, a new simple method is proposed for estimating the power spectrum density of output thermal noise in SC filters, which have acceptable accuracy and short running time. In the proposed method, first using HSPICE simulator, accurate value of accumulated sampled noise on sampler capacitors in each clock state is achieved. Next, using difference equations of the SC filter, frequency response of the SC filter is shaped by time domain analysis. Based on the proposed method, a SC low-pass filter and a second-order SC band-pass filter are analysed. The results are validated by comparing to the previously measured data.     

The preparation of an amino acid-based surfactant and its potential application as an EOR agent

Most of the synthetic surfactants investigated with the aim of enhanced chemically oil recovery in the literature have environmental drawbacks. In this work, application of an environmentally-friendly synthetic surfactant as an enhanced oil recovery agent is introduced by measuring interfacial tension of water–kerosene systems and wettability alteration of carbonate pellets. For this purpose, an amino acid-based surfactant was initially synthesized using a new synthetic approach which was subsequently confirmed by spectra of Fourier transform infrared and Proton nuclear magnetic resonance. Results showed a value of critical micelle concentration in the range of 9000–9100 ppm for this surfactant. Results also demonstrated a decrease of 38.53% in water–kerosene system interfacial tension and a 17.76% reduction in oil-wetness of the carbonate pellets.     

Kinetic modeling of pyrolysis of three Iranian waste oils in a micro-fluidized bed

Different approaches have been used to convert the waste materials into a clean syngas or other chemicals such as methanol. Among them, pyrolysis is a good candidate to produce the synthesis gas and volatile matters for industrial and refinery applications. In this work, we studied the kinetic and chemical behavior of three Iranian waste oils through a kinetic model and an experimental study. The experiments carried out in a micro-FB reactor, which is a good option for low emissions. Results showed that the reaction temperature and reaction rate are two of the most important factors for maximum conversion level of fuel. Results also showed an optimum value for reaction rate. The modeling results validated against the experimental measurements and found to be in good agreements.     

Prediction of asphaltene precipitation during gas injection

Maintaining the flow of multiphase fluid from the reservoir to the surface has been an important issue with wide economic importance for the petroleum industry. Asphaltene precipitation due to change in temperature, pressure, and composition of oil can adversely affect the oil flow to the surface by reducing the available diameter of the tubing. In this study, the precipitation of asphaltene from an Iranian crude oil was investigated. To do our study, through information about asphaltene instability in the live oil during both natural depletion and gas injection conditions about oil sample from Iranian oil field was gathered. Then, the solid model and scaling model were utilized to predict the weight percent of precipitated asphaltene at a wide range of the pressure and temperature. Results of the work revealed that both models predict the increase in weight percent of precipitated asphaltene when lean gas injected to the live oil at the maximum point of asphaltene instability. In addition, the study showed that both models are capable of predicting the experimental data of asphaltene precipitation; while scaling modeling is more reliable when the gas is injected to the oil.