• Advances in nano research
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• v.10 no.1
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• pp.91-99
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• 2021

Silicene is an emerging two-dimensional (2D) semiconductor material which has been envisaged to be compatible with conventional silicon technology. This paper presents a theoretical study of uniformly doped silicene with aluminium (AlSi3) Field-Effect Transistor (FET) along with the benchmark of device performance metrics with other 2D materials. The simulations are carried out by employing nearest neighbour tight-binding approach and top-of-the-barrier ballistic nanotransistor model. Further investigations on the effects of the operating temperature and oxide thickness to the device performance metrics of AlSi3 FET are also discussed. The simulation results demonstrate that the proposed AlSi3 FET can achieve on-to-off current ratio up to the order of seven and subthreshold swing of 67.6 mV/dec within the ballistic performance limit at room temperature. The simulation results of AlSi3 FET are benchmarked with FETs based on other competitive 2D materials such as silicene, graphene, phosphorene and molybdenum disulphide.

• Current Optics and Photonics
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• v.5 no.6
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• pp.699-710
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• 2021

In this study, we propose a biomimetic optical structure design methodology for investigating micro-optical mechanisms associated with the compound eyes of insects. With these compound eyes, insects can respond fast while maintaining a wide field of view. Also, considerable research attention has been focused on the insect compound eyes to utilize these benefits. However, their nano micro-structures are complex and challenging to demonstrate in real applications. An effectively integrated design methodology is required considering the manufacturing difficulty. We show that photorealistic ray-traced visualization is an effective method for designing the biomimetic of a micro-compound eye of an insect. We analyze the image formation mechanism and create a three-dimensional computer-aided design model. Then, a ray-trace visualization is applied to observe the optical image formation. Finally, the segmented images are stitched together to generate an image with a wide-angle; the image is assessed for quality. The high structural similarity index (SSIM) value (approximately 0.84 to 0.89) of the stitched image proves that the proposed MATLAB-based image stitching algorithm performs effectively and comparably to the commercial software. The results may be employed for the understanding, researching, and design of advanced optical systems based on biological eyes and for other industrial applications.

• Advances in nano research
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• v.10 no.5
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• pp.423-435
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• 2021

This paper examines the thermal post-buckling behaviors of graphene-reinforced metal matrix composite (GRMMC) laminated cylindrical panels which possess in-plane negative Poisson's ratio (NPR) and rest on an elastic foundation. A panel consists of GRMMC layers of piece-wise varying graphene volume fractions to obtain functionally graded (FG) patterns. Based on the MD simulation results, the GRMMCs exhibit in-plane NPR as well as temperature-dependent material properties. The governing equations for the thermal post-buckling of panels are based on the Reddy's third order shear deformation shell theory. The von Karman nonlinear strain-displacement relationship and the elastic foundation are also included. The nonlinear partial differential equations for GRMMC laminated cylindrical panels are solved by means of a singular perturbation technique in associate with a two-step perturbation approach and in the solution process the boundary layer effect is considered. The results of numerical investigations reveal that the thermal post-buckling strength for (0/90)_5T GRMMC laminated cylindrical panels can be enhanced with an FG-X pattern. The thermal post-buckling load-deflection curve of 6-layer (0/90/0)_S and (0/90)_3T panels of FG-X pattern are higher than those of 10-layer (0/90/0/90/0)_S and (0/90)_5T panels of FG-X pattern.

• Advances in nano research
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• v.11 no.6
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• pp.657-665
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• 2021

The present work aimed to explore green approach via aqueous leaves extract of Murraya koenigii (ALEMk) for the synthesis of silver nanoparticles (AgNPsMk) in single step. The synthesis process was visualized with a color change and monitored by employing UV/Visible spectroscopy and a clear peak attained at 420 nm confirming the synthesis of AgNPsMk. The possible functional groups present in the extract which participated in the synthesis of AgNPsMk were identified with the help of FTIR spectroscopy. Further characterization using TEM images revealed the spherical shape of AgNPsMk with average particle size of 20 nm displaying well dispersion throughout the solution. Pronounced antioxidant activities of AgNPsMk at increased concentrations observed which evidencing strong radical scavenging ability. Moreover, AgNPsMk exhibited strong antibacterial behavior when tested against bacterial strains of Escherichia coli and Bacillus subtilis. Moving ahead, in vitro cytotoxicity work revealed potent cell viability loss appearing in AU565 and HeLa cancer cell lines on exposure to AgNPsMk at increased concentration. Finally, in vivo assessment carried out inside male Wistar rats indicated non toxic effect on examined liver tissues besides biochemical analysis including bilirubin, alkaline phosphtase (ALP) and serum glutamate pyruvate transaminase (SGPT) which found within the normal range when compared with control. The prior research work profoundly apprises the potential of green synthesized AgNPsMk to play a significant role in biomedical applications and formulations.

• Advances in nano research
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• v.11 no.6
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• pp.607-620
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• 2021

In this paper, the vibrations of boron nitride nanotubes (BNNTs) are investigated by considering the electric field. To consider the size effect at nanoscale dimensions, the surface elasticity theory is exploited. The equations of motion of the BNNTs are obtained by applying Hamilton's principle, and the clamped-guided boundary conditions are also considered. The governing equations and boundary conditions are discretized using the differential quadrature method (DQM), and the natural frequency is obtained by using the eigenvalue problem solution. The results are compared with the molecular dynamic simulation in order to validate the accurate values of the surface effects. In the molecular dynamics (MD) simulation, the potential between boron and nitride atoms is considered as the Tersoff type. The Timoshenko beam model is adopted to model BNNT. The vibrations of two types of zigzag and armchair BNNTs are considered. In the result section, the effects of chirality, surface elasticity modulus, surface residual tension, surface density, electric field, length, and thickness of BNNT on natural frequency are investigated. According to the results, it should be noted that, as an efficient non-classical continuum mechanic approach, the surface elasticity theory can be used in scrutinizing the dynamic behavior of BNNTs.

• Advances in nano research
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• v.13 no.6
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• pp.587-597
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• 2022

In the present study, a novel optimization method in formation control of multi -system vehicles based on the trajectory of the nearest neighbor trajectory is presented. In this regard, the state equations of each vehicle and multisystem is derived and the optimization scheme based on minimizing the differences between actual positions and desired positions of the vehicles are conducted. This formation control is a position-based decentralized model. The trajectory of the nearest neighbor are optimized based on the current position and state of the vehicle. This approach aids the whole multi-agent system to be optimized on their trajectory. Furthermore, to overcome the cumulative errors and maintain stability in the network a semi-centralized scheme is designed for the purpose of checking vehicle position to its predefined trajectory. The model is implemented in Matlab software and the results for different initial state and different trajectory definition are presented. In addition, to avoid collision avoidance and maintain the distances between vehicles agents at a predefined desired distances. In this regard, a neural fuzzy network is defined to be utilized in conjunction with the control system to avoid collision between vehicles. The outcome reveals that the model has acceptable stability and accuracy.

• Advances in nano research
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• v.12 no.2
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• pp.223-239
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• 2022

Object detection has always been to pursue objects with particular properties or representations and to predict details on objects including the positions, sizes and angle of rotation in the current picture. This was a very important subject of computer vision science. While vision-based object tracking strategies for the analysis of competitive videos have been developed, it is still difficult to accurately identify and position a speedy small ball. In this study, deep learning (DP) network was developed to face these obstacles in the study of tennis motion tracking from a complex perspective to understand the performance of athletes. This research has used CNN-VGG 16 to tracking the tennis ball from broadcasting videos while their images are distorted, thin and often invisible not only to identify the image of the ball from a single frame, but also to learn patterns from consecutive frames, then VGG 16 takes images with 640 to 360 sizes to locate the ball and obtain high accuracy in public videos. VGG 16 tests 99.6%, 96.63%, and 99.5%, respectively, of accuracy. In order to avoid overfitting, 9 additional videos and a subset of the previous dataset are partly labelled for the 10-fold cross-validation. The results show that CNN-VGG 16 outperforms the standard approach by a wide margin and provides excellent ball tracking performance.

• Advances in nano research
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• v.15 no.2
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• pp.113-128
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• 2023

The advancement of theoretical research has numerous challenges, particularly with regard to the modeling of structures, in contrast to experimental investigation of the mechanical behavior of complex systems. The main objective of this investigation is to provide an analytical analysis of the static problem of a new generation of composite structure, namely, functionally graded FG graphene reinforced composite GRC coated plates/shells. A complex power law function is used to define the material's graduation. Investigations are conducted on Hardcore and Softcore coated FG plates/shells. The virtual work approach is used to perform the equilibrium equations, which are then solved using the Galerkin technique to account for various boundary conditions. With reliable published articles, the presented solution is validated. The effects of hardcore and softcore distributions, gradation indexes, and boundary conditions on the buckling, bending deflection and stresses of FG GRC-coated shells are presented in detail. Obtained results and the developed procedure are supportive for design and manufacturing of FG-GRC coated plates/shells in several fields and industries e.g., aerospace, automotive, marine, and biomedical implants.

• Journal of the Korean institute of surface engineering
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• v.56 no.2
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• pp.115-124
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• 2023

Anodization is an electrochemical process that electrochemically converts a metal surface into an oxide layer, resulting in enhanced corrosion resistance, wear resistance, and improved aesthetic appearance. Local anodization, also known as selective anodization, is a modified process that enables specific regions or patterns on the metal surface to undergo anodization instead of the entire surface. Several methods have been attempted to produce oxide layers via localized anodic oxidation, such as using a mask or pre-patterned substrate. However, these methods are often intricate, time-consuming, and costly. Conversely, the direct writing or patterning approach is a more straightforward and efficient way to fabricate the oxide layers. This review paper intends to enhance our comprehension of local anodization and its potential applications in various fields, including the development of nanotechnologies. The application of anodization is promising in surface engineering, where the anodic oxide layer serves as a protective coating for metals or modifies the surface properties of materials. Furthermore, anodic oxidation can create micro- and nano-scale patterns on metal surfaces. Overall, the development of efficient and cost-effective anodic oxidation methods is essential for the advancement of various industries and technologies.

• Advances in nano research
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• v.12 no.3
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• pp.231-251
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• 2022

Dynamic behavior of temperature-dependent Reddy functionally graded (RFG) nanobeam subjected to thermomagnetic effects under the action of moving point load is carried out in the present work. Both symmetric and sigmoid functionally graded material distributions throughout the beam thickness are considered. To consider the significance of strain-stress gradient field, a material length scale parameter (LSP) is introduced while the significance of nonlocal elastic stress field is considered by introducing a nonlocal parameter (NP). In the framework of the nonlocal strain gradient theory (NSGT), the dynamic equations of motion are derived through Hamilton's principle. Navier approach is employed to solve the resulting equations of motion of the functionally graded (FG) nanoscale beam. The developed model is verified and compared with the available previous results and good agreement is observed. Effects of through-thickness variation of FG material distribution, beam aspect ratio, temperature variation, and magnetic field as well as the size-dependent parameters on the dynamic behavior are investigated. Introduction of the magnetic effect creates a hardening effect; therefore, higher values of natural frequencies are obtained while smaller values of the transverse deflections are produced. The obtained results can be useful as reference solutions for future dynamic and control analysis of FG nanobeams reinforced nanocomposites under thermomagnetic effects.