A strong controllable absorber using graphene-metal nanostructure

In this paper, a strong absorption is obtained by a graphene-metal nanostructure at near-infrared wavelengths. The proposed absorber consists of a single graphene layer on a metal film array with semicircle and L-shaped grooves. There are two absorption peaks of 0.48 and 0.86 at 1488?nm and 1538?nm wavelengths, respectively, in the absorption spectrum of the structure without the graphene layer. The absorption is enhanced to 0.89 at 1498?nm wavelength and the full-width at half-maximum (FWHM) is increased as the graphene layer is used. Also, the absorption value of 0.99 can be attained as three graphene layers are utilized and the FWHM can be enhanced to 173?nm when four graphene layers are on the structure. Moreover, the effects of geometrical parameters of the structure and graphene chemical potential on the absorption spectrum are studied to tune the absorption value and wavelength. By tuning the geometrical parameters, a three-band absorber is proposed.     

Synthesis and properties of novel biodegradable poly(ε‐caprolactone)/ poly(ethylene glycol)‐based polyurethane elastomers

Elastomeric polyurethanes with tunable biodegradation properties and suitable for numerous biomedical applications were synthesized via reaction of epoxy‐terminated polyurethanes (EUPs) with 1,6‐hexamethylenediamine as curing agent. The EUPs themselves were prepared from glycidol and isocyanate‐terminated polyurethanes made from poly(ε‐caprolactone) (PCL) or poly(ethylene glycol) (PEG) and 1,6‐hexamethylene diisocyanate. All the polymers were characterized by conventional methods, and their physical, mechanical, thermal, and degradation properties were studied. The results showed that the degradation rate and mechanical properties of the final products can be controlled by the amount of PEG or PCL present in the EUP. Increasing the PEG content causes an increase of hydrolytic degradation rate, and increasing the PCL content improves the mechanical properties of the final products. Evaluation of cytotoxcicity showed nontoxic behavior of the prepared samples, but the cytocompatibility of these polymers needs to be improved. Copyright © 2006 Society of Chemical Industry     

FORCE TRANSDUCER MODELING OF RECTANGULAR,V–SHAPED,AND DAGGER CANTILEVER PROBES BASED ON ATOMIC FORCE MICROSCOPY

Real-time monitoring of the nano-particle manipulation process by atomic force microscope (AFM) is almost impossible since the manipulator of the AFM is used as either the imaging or manipulation tool at a given instant. As one approach to this problem, researchers scan the area where the target particle exists, before and after the nano-manipulation. Thus, by using some fixed reference features, the new relative position of the particle is obtained from the images. However, this imaging is offline, and unexpected problems during nano-manipulation process cannot be detected. In this article, force transducer of the AFM rectangular, V-shaped, and dagger cantilevers, which convert the three-dimensional deflections measured by the detection system to corresponding three-dimensional force, are modeled and compared. So there would be a feedback from the real-time force system during nano-manipulation process, which can be utilized for better understanding and reliable handling of nano-particles. Furthermore, the manipulation forces are affected directly by spring constants of cantilever. Hence, the cantilever is the most significant and sensitive component of the AFM. Therefore, variations of the lateral, longitudinal, and normal spring constants of the mentioned cantilever for different geometrical parameters are analyzed and discussed.     

Ti alkoxide-based catalyst system in selective ethylene dimerization: High performance through modifying by alkylsilanes

Butene-1 production through a selective ethylene dimerization is one of the largest industrial processes, which is catalyzed by homogeneous catalyst system. The common industrial catalyst system is comprised of Ti alkoxide-based catalysts in combination with AlEt₃ as an activator. In this study, the alkylsilanes were used as novel improving agents in the catalyst system for highly selective ethylene dimerization to butene-1. The nature and concentration of alkylsilanes on the dimerization rate, catalyst yield, by-product production, and selectivity to butene-1 were investigated in detail. It was found that alkylsilanes improved the productivity and selectivity of the catalyst. Moreover, the content of the solid by-product considerably decreased. The performance of the modified catalyst system was noticeably higher than that of the nonmodified one. Totally, it was proved that alkylsilanes could play a modifying role in the selective ethylene catalytic dimerization process.     

Optimal Water Allocation from Subsurface Dams: A Risk-Based Optimization Approach

Subsurface dams, strongly advocated in the 1992 United Nations Agenda-21, have been widely studied to increase groundwater storage capacity. However, an optimal allocation of augmented water with the construction of the subsurface dams to compensate for the water shortage during dry periods has not so far been investigated. This study, therefore, presents a risk-based simulation–optimization framework to determine optimal water allocation with subsurface dams, which minimizes the risk of water shortage in different climatic conditions. The developed framework was evaluated in Al-Aswad falaj, an ancient water supply system in which a gently sloping underground channel was dug to convey water from an aquifer via the gravity force to the surface for irrigation of downstream agricultural zones. The groundwater dynamics were modeled using MODFLOW UnStructured-Grid. The data of boreholes were used to generate a three-dimensional stratigraphic model, which was used to define materials and elevations of five-layer grid cells. The validated groundwater model was employed to assess the effects of the subsurface dam on the discharge of the falaj. A Conditional Value-at-Risk optimization model was also developed to minimize the risk of water shortage for the augmented discharge on downstream agricultural zones. Results show that discharge of the falaj is significantly augmented with a long-term average increase of 46.51%. Moreover, it was found that the developed framework decreases the water shortage percentage in 5% of the worst cases from 87%, 75%, and 32% to 53%, 32%, and 0% under the current and augmented discharge in dry, normal, and wet periods, respectively.

     

A novel legitimacy preserving data hiding scheme based on LAS compressed code of VQ index tables

Data hiding is a technique for secret and secure data storing and transmission that embeds data into a media such as an image, audio, video and so on, with minimal quality degradation of the media. Some developed data hiding schemes are reversible. Reversibility property allows the media to be recovered completely after extraction of the embedded data. Vector Quantization (VQ)-based image data hiding is one of the most popular study areas in the literature. However, most VQ-based reversible data hiding schemes generate non-legitimate codes as output. In other words output codes generated by such schemes could not be decoded by the conventional VQ or VQ based decoders and may arouse the attention of interceptors. On the other hand, the existing VQ based reversible data hiding schemes that generate legitimate VQ codes as output, suffer from low capacity and poor quality of stego-image. In this paper a novel reversible data hiding scheme for VQ-compressed images based on locally adaptive data compression scheme (LAS) is proposed. Unlike other schemes, the proposed scheme doesn’t change the VQ indices; data is embedded by choosing one of the possible ways to encode each index. As a result, in comparison with the schemes that embed data by index replacement, in the proposed scheme no extra distortion is made by data embedding and the outputted codes are compatible with the conventional LAS decoder. These properties help to hide the existence of secret data and make the scheme suitable for steganography. Moreover, a framework to combine the proposed scheme with some other schemes to improve their capacity and embedding side information is proposed. Since LAS is a general data compression scheme, the proposed scheme could be used to embed data into any data formats. All existing LAS based data hiding schemes produce non-legitimate codes as their outputs and the proposed scheme is the first and only one that produces legitimate codes as output. Experimental results show that the proposed scheme outperforms the existing LAS based schemes and some other VQ based data hiding schemes. On average, the proposed scheme embeds 2.14 bits per index with almost the same bit-rate as the bit-rate of the VQ index table.     

Motion estimation using learning automata

Block-matching algorithms (BMAs) are widely employed for motion estimation. BMAs divide input frames into several blocks and minimize an error function for each block to calculate motion vectors. Afterward, each motion vector is applicable for all of the pixels within the block. Since computing the error functions is resource intensive, many fast-search motion estimation algorithms have been suggested to reduce the computational cost. These fast algorithms provide a significant reduction in computation but often converge to a local minimum. A learning automaton is an adaptive decision-making unit that learns the optimal action through repeated interactions with its environment. Learning automata (LA) have been applied successfully to a wide range of applications including pattern recognition, dynamic channel assignment, and social network analysis. In this paper, we apply LA to motion estimation problem, which is one of the basic problems in computer vision. We compare the accuracy and performance of the suggested algorithms with other well-known BMAs. Interestingly, the obtained results indicate high efficiency and accuracy of the proposed methods. The results suggest that simplicity, efficiency, parallel nature, and accuracy of LA-based methods make them a good candidate to solve computer vision problems.     

Numerical Investigation on the Impact of DBD Plasma Actuators on Temperature Enhancement in the Channel Flow

The present study indicates the impact of different arrangements of dielectric barrier discharge (DBD) plasma actuators on temperature field in a channel flow. The modified lumped circuit element electro‐static model was used to calculate induced Lorentz body force and plasma dissipation of the actuators. Different distributions of temperature in the modeled channel flow for each arrangement of actuators (one, two, and three attached actuators) are discussed. According to the numerical simulation, DBD plasma actuators are beneficial devices for increasing temperature in the channel flow, especially near the location of the actuators that can be considered for related applications. The actuators are modeled under an incompressible flow regime with low Reynolds number of 335, and the configurations of the actuators are set to be 3 KV for the peak voltage amplitude, 10,000 Hz for the voltage frequency, and Kapton as the dielectric.     

Optimization of the Thermal Efficiency of a Two-Phase Closed Thermosyphon using Active Learning on the Human Algorithm Interaction

Here, pristine and functionalized multi-walled carbon nanotubes with silver/water nanofluids were first synthesized. To investigate thermal performance of two-phase closed thermosyphon, thermal efficiency was experimentally obtained as a key parameter. To obtain optimal points in operational condition, the active learning method was employed in concentration ranges of 0–1 wt% as well as input power of 30–150 W which cannot be accessed. The active learning method is based on the fuzzy logic rules; here query synthesis and the measure human algorithm interaction (HAI) were used for learning. As the primary data obtained from experiments is small, this method was used to suggest the most optimal conditions. First, primary data obtained from experiments are given to the algorithm and then algorithm proposed some suggestions based on the maximum uncertainty. Subsequently, thermal efficiency is estimated based on fuzzy inference. Here, two mechanisms are employed as combined ones. The mentioned suggestions will be tested in the offered operational conditions. If the accuracy of the suggestions was confirmed by the obtained data, these data would be added to the primary ones. In fact, the used method can be considered in the area of HAI performing with the aid of experienced human simultaneously with intelligent algorithms. Meanwhile, the best working concentration to obtain the most optimum thermal efficiency obtained in the range 0.90 to 0.95 for both nanofluids.     

Synthesis and Characterization of New Zinc(II) Coordination Polymer with a Flexible Hetro-coordination Ligand via In Situ Reaction as a New Precursor for Zinc(II) Oxide Nano-sphere Particles

A new coordination polymer, [Zn₃(tza)₃(H₂O)₃] _n (1) which H₂tza?=?1H-tetrazolate-5-acetic acid has been synthesized and characterized by IR spectroscopy, elemental analysis X-ray crystallography. The single-crystal X-ray data of compound 1 show existence of three different ZnII ion with different coordination spheres, hexagonal, pyramidal and pentagonal. This coordination polymer used as a precursor for preparation of zinc(II) oxide nano-particles. Nano-particles were characterized by powder X-ray powder diffraction and the its morphology characterized by scanning electron microscope.