Encapsulation of cellulose chain into carbon nanotubes and boron nitride nanotubes

Encapsulation of cellulose chain into carbon nanotubes and boron nitride nanotubes was investigated to find out the possibility of band gap engineering in these nanotubes. The structural stability and the electronic properties of the zigzag carbon nanotubes and boron nitride nanotubes filled with cellulose chain were studied using density functional theory. It was found that encapsulation of cellulose chain into nanotubes was an exothermic process. The metallic properties of the carbon nanotubes did not change by cellulose encapsulation. The semiconductor and insulator nanotubes filled with cellulose were shown semiconducting properties. The energy band gap of these tubes was decreased by cellulose encapsulation. The results demonstrated the ability of band gap engineering through the encapsulation of cellulose chain into carbon nanotubes and boron nitride nanotubes.     

Secure decentralized peer-to-peer training of deep neural networks based on distributed ledger technology

The accuracy and performance of deep neural network models become important issues as the applications of deep learning increase. For example, the navigation system of autonomous self-driving vehicles requires very accurate deep learning models. If a self-driving car fails to detect a pedestrian in bad weather, the result can be devastating. If we can increase the model accuracy by increasing the training data, the probability of avoiding such scenarios increases significantly. However, the problem of privacy for consumers and lack of enthusiasm for sharing their personal data, e.g., the recordings of their self-driving car, is an obstacle for using this valuable data. In Blockchain technology, many entities which cannot trust each other in normal conditions can join together to achieve a mutual goal. In this paper, a secure decentralized peer-to-peer framework for training the deep neural network models based on the distributed ledger technology in Blockchain ecosystem is proposed. The proposed framework anonymizes the identity of data providers and therefore can be used as an incentive for consumers to share their private data for training deep learning models. The proposed framework uses the Stellar Blockchain infrastructure for secure decentralized training of the deep models. A deep learning coin is proposed for Blockchain compensation.

     

Aerial tracking of elongated objects in rural environments

In this paper, a new approach to finding and tracking various land cover boundaries such as rivers, agricultural fields, channels and roads for use in visual navigation system of an unmanned aerial vehicle is presented. We use a combination of statistical estimation and optimization techniques for extraction of dominant boundaries in noisy aerial images. A set of perceptual grouping restrictions is used to connect the acquired piecewise boundaries and to find the heading direction of the main boundary. The results are further refined by applying a set of texture and colour cues and eliminating any false hypothesis. To reduce the computation requirements, another approach based on sampled colour values of different land covers is also investigated. Colour characteristics of a set of manually selected windows are compared to select the best attributes needed for discrimination between different land covers in various (natural) lighting conditions. Each frame is then partially scanned and desired environmental features are extracted and classified. The results show that the proposed technique meets the minimum speed and accuracy requirement of aforementioned application and outperforms single-feature object tracking algorithms.

First Principle Study of Electronic and Optical Properties of Full-Fluorinated SnC Nanosheets

Silicon - We have investigated the electronic structures and optical properties of pristine and full-fluorinated SnC nanosheets using the full potential linearized augmented plane wave [FP-LAPW]...     

A Cu-Cr alloy with nano and microscale Cr particles produced in a water-cooled copper mold

Microstructures have profound effects on the hardness and strength of Cu-Cr alloys. The microstructures of a Cu-Cr alloy cast in a water-cooled copper mold were studied in the present work. The scanning electron microscopy (SEM) results show that there are the copper matrix saturated with chromium, spherical precipitates of chromium separated from liquid phase during cooling before the initiation of so- lidification, and a eutectic phase in grain boundary areas. To investigate the effect of age-hardening tr...     

Electrodeposition of CdSe coatings on ZnO nanowire arrays for extremely thin absorber solar cells

We report on electrodeposition of CdSe coatings onto ZnO nanowire arrays and determine the effect of processing conditions on material properties such as morphology and microstructure. CdSe-coated ZnO nanowire arrays have potential use in extremely thin absorber (ETA) solar cells, where CdSe absorbs visible light and injects photoexcited electrons into the ZnO nanowires. We show that room-temperature electrodeposition enables growth of CdSe coatings that are highly crystalline, uniform, and conformal with precise control over thickness and microstructure. X-ray diffraction and transmission electron microscopy show nanocrystalline CdSe in both hexagonal and cubic phases with grain size ∼5 nm. Coating morphology depends on electrodeposition current density. Uniform and conformal coatings were achieved using moderate current densities of ∼2 mA cm⁻² for nanowires with roughness factor of ∼10, while lower current densities resulted in sparse nucleation and growth of larger, isolated islands. Electrodeposition charge density controls the thickness of the CdSe coating, which was exploited to investigate the evolution of the morphology at early stages of nucleation and growth. UV–vis transmission spectroscopy and photoelectrochemical solar cell measurements demonstrate that CdSe effectively sensitizes ZnO nanowires to visible light.     

Emulsifier‐free miniemulsion polymerization of styrene using a cationic initiator

Polystyrene latex particles were synthesized using a method based on emulsifier‐free miniemulsion polymerization under ultrasonic irradiation in the presence of 2,2′ azobis (2‐amidinopropane) dihydrochloride (V‐50) as a cationic ionizable water‐soluble initiator and cetyl alcohol as costabilizer. The optimized conditions were obtained by using various parameters, such as the amounts of monomer and initiator, and the time and power of ultrasonic irradiation. In optimal conditions, the latex particles appeared to be about 250 nm in diameter through scanning electron microscopy (SEM). The SEM and gel permeation chromatography (GPC) analyses and monomer conversions of emulsifier‐free miniemulsion polymerization were compared with those of conventional emulsifier‐free emulsion polymerization using V‐50 as initiator in both cases. The results showed that in the miniemulsion polymerization, the rate of polymerization (Rp) was significantly higher, and latex particles were significantly smaller than those in the conventional emulsion polymerization. © 2007 Wiley Periodicals, Inc. J Appl Polym Sci, 2007     

Pulsatile flow of viscous and viscoelastic fluids in constricted tubes

The unsteady flow of blood through stenosed artery, driven by an oscillatory pressure gradient, is studied. An appropriate shape of the time-dependent stenoses which are overlapped in the realm of the formation of arterial narrowing is constructed mathematically. A msathematical model is developed by treating blood as a non-Newtonian fluid characterized by the Oldroyd-B and Cross models. A numerical scheme has been used to solve the unsteady nonlinear Navier-stokes equations in cylindrical coordinate system governing flow, assuming axial symmetry under laminar flow condition so that the problem effectively becomes two-dimensional. Finite difference technique was used to investigate the effects of parameters such as pulsatility, non-Newtonian properties and the flow time on the velocity components, the rate of flow, and the wall shear stress through their graphical representations quantitatively at the end of the paper in order to validate the applicability of the present improved mathematical model under consideration.     

Fragile high capacity data hiding in digital images using integer-to-integer DWT and lattice vector quantization

Multimedia Tools and Applications - Data hiding in digital multimedia has been extensively used for sensitive data transmission and data authentication. An important property of data hiding which...