Impact of adhesive ingredients on adhesion between rubber and brass-plated steel wire in tire

Proficiency on underlying mechanism of rubber-metal adhesion has been increased significantly in the last few decades. Researchers have investigated the effect of various ingredients, such as hexamethoxymethyl melamine, resorcinol, cobalt stearate, and silica, on rubber-metal interface. The role of each ingredient on rubber-metal interfacial adhesion is still a subject of scrutiny. In this article, a typical belt skim compound of truck radial tire is selected and the effect of each adhesive ingredient on adhesion strength is explored. Out of these ingredients, the effect of cobalt stearate is found noteworthy. It has improved adhesion strength by 12% (without aging) and by 11% (humid-aged), respectively, over control compound. For detailed understanding of the effect of cobalt stearate on adhesion, scanning electron microscopy and energy dispersive spectroscopy are utilized to ascertain the rubber coverage and distribution of elements. X-ray photoelectron spectroscopy results helped us to understand the impact of Cu_XS layer depth on rubber-metal adhesion. The depth profile of the Cu_XS layer was found to be one of the dominant factors of rubber-metal adhesion retention. Thus, this study has made an attempt to find the impact of different adhesive ingredients on the formation of Cu_XS layer depth at rubber-metal interface and establish a correlation with adhesion strength simultaneously.     

Analysis of D.C Parameters of Short-Channel Heterostructure Double Gate Junction-Less MOSFET Circuits Considering Quantum Mechanical Effects

Silicon - In this article, the electrical behavior of short channel SiGe Heterostructure Junction-Less DG-MOSFET have been studied by incorporating the quantum mechanical effect and short channel...     

Chemical toughening of epoxies. I. Structural modification of epoxy resins by reaction with hydroxy-terminated poly(butadiene-co-acrylonitrile)

In an attempt to toughen the epoxy resin matrix for fiber-reinforced composite applications, a chemical modification procedure of a commercially available bisphenol-A-based epoxy resin using reactive liquid rubber HTBN [hydroxy-terminated poly(butadiene-co-acrylonitrile)] and TDI (tolylene diisocyanate) is described. The progress of the reaction and the structural changes during modification process are studied using IR spectroscopy, viscosity data, and chemical analysis (epoxy value determination). The studies support the proposition that TDI acts as a coupling agent between the epoxy and HTBN, forming a urethane linkage with the former and an oxazolidone ring with the latter. The chemical reactions that possibly take place during the modification are discussed.     

Multi-focus image fusion using a morphology-based focus measure in a quad-tree structure

Finite depth-of-field poses a problem in light optical imaging systems since the objects present outside the range of depth-of-field appear blurry in the recorded image. Effective depth-of-field of a sensor can be enhanced considerably without compromising the quality of the image by combining multi-focus images of a scene. This paper presents a block-based algorithm for multi-focus image fusion. In general, finding a suitable block-size is a problem in block-based methods. A large block is more likely to contain portions from both focused and defocused regions. This may lead to selection of considerable amount of defocused regions. On the other hand, small blocks do not vary much in relative contrast and hence difficult to choose from. Moreover, small blocks are more affected by mis-registration problems. In this work, we present a block-based algorithm which do not use a fixed block-size and rather makes use of a quad-tree structure to obtain an optimal subdivision of blocks. Though the algorithm starts with blocks, it ultimately identifies sharply focused regions in input images. The algorithm is simple, computationally efficient and gives good results. A new focus-measure called energy of morphologic gradients is introduced and is used in the algorithm. It is comparable with other focus measures viz.energy of gradients, variance, Tenengrad, energy of Laplacian and sum modified Laplacian. The algorithm is robust since it works with any of the above focus measures. It is also robust against pixel mis-registration. Performance of the algorithm has been evaluated by using two different quantitative measures.     

Development,optimization, and characterization of a novel tea tree oil nanogel using response surface methodology

Purpose: To develop and optimize nanoemulsion (NE)-based emulgel (EG) formulation as a potential vehicle for topical delivery of tea tree oil (TTO).

Methodology: Central composite design was adopted for optimizing the processing conditions for NE preparation by high energy emulsification method viz. surfactant concentration, co-surfactant concentration, and stirring speed. The optimized NE was developed into emulgel (EG) using pH sensitive polymer Carbopol 940 and triethanolamine as alkalizer. The prepared EG was evaluated for its pH, viscosity, and texture parameters, ex vivo permeation at 37?°C and stability. Antimicrobial evaluation of EG in comparison to conventional gel and pure TTO was also carried out against selected microbial strains.

Results and discussion: Optimized NE had particle size and zeta potential of 16.23?±?0.411?nm and 36.11?±?1.234?mV, respectively. TEM analysis revealed the spherical shape of droplets. The pH of EG (5.57?±?0.05?) was found to be in accordance with the range of human skin pH. EG also illustrated efficient permeation (79.58?μL/cm²) and flux value (J_SS) of 7.96?μL cm²/h through skin in 10?h. Viscosity and texture parameters, firmness (9.3?±?0.08?g), spreadability (2.26?±?0.06?mJ), extrudability (61.6?±?0.05?mJ), and adhesiveness (8.66?±?0.08?g) depict its suitability for topical application. Antimicrobial evaluation of EG with same amount of TTO as conventional gel revealed broader zones of growth inhibitions against all the selected microbial strains. Moreover, EG was also found to be nonirritant (PII 0.0833). These parameters were consistent over 90 d.

Conclusion: TTO EG turned out to be a promising vehicle for the topical delivery of TTO with enhanced therapeutic efficacy.     

Multi-item inventory model of breakable items with stock-dependent demand under stock and time dependent breakability rate

Items made of glass, ceramic, etc. are normally stored in stacks and get damaged during the storage due to the accumulated stress of heaped stock. These items are known as breakable items. Here a multi-item inventory model of breakable items is developed, where demands of the items are stock dependent, breakability rates increase linearly with stock and nonlinearly with time. Due to non-linearity and complexity of the problem, the model is solved numerically and final decisions are made using Genetic Algorithm (GA). In a particular case, model is solved analytically as well as numerically and results are compared. Models are developed with both crisp and uncertain inventory costs. For uncertain inventory costs both fuzzy and stochastic parameters are considered. A chance constrained approach is followed to deal with simultaneous presence of stochastic and fuzzy parameters. Different numerical examples are used to illustrate the problem for different cases.     

A particle swarm approach for multi-objective optimization of electrical discharge machining process

This paper proposes an experimental investigation and optimization of various machining parameters for the die-sinking electrical discharge machining (EDM) process using a multi-objective particle swarm (MOPSO) algorithm. A Box–Behnken design of response surface methodology has been adopted to estimate the effect of machining parameters on the responses. The responses used in the analysis are material removal rate, electrode wear ratio, surface roughness and radial overcut. The machining parameters considered in the study are open circuit voltage, discharge current, pulse-on-time, duty factor, flushing pressure and tool material. Fifty four experimental runs are conducted using Inconel 718 super alloy as work piece material and the influence of parameters on each response is analysed. It is observed that tool material, discharge current and pulse-on-time have significant effect on machinability characteristics of Inconel 718. Finally, a novel MOPSO algorithm has been proposed for simultaneous optimization of multiple responses. Mutation operator, predominantly used in genetic algorithm, has been introduced in the MOPSO algorithm to avoid premature convergence. The Pareto-optimal solutions obtained through MOPSO have been ranked by the composite scores obtained through maximum deviation theory to avoid subjectiveness and impreciseness in the decision making. The analysis offers useful information for controlling the machining parameters to improve the accuracy of the EDMed components.     

33.7 MHz heavy-ion radio frequency quadrupole linac at VECC Kolkata

A 33.7 MHz heavy-ion radio frequency quadrupole (RFQ) linear accelerator has been designed, built, and tested. It is a four-rod-type RFQ designed for acceleration of 1.38 keVu, qA> or =116 ions to about 29 keVu. Transmission efficiencies of about 85% and 80% have been measured for the unanalyzed and analyzed beams, respectively, of oxygen ((16)O(2+), (16)O(3+), (16)O(4+)), nitrogen ((14)N(3+), (14)N(4+)), and argon ((40)Ar(4+)). The system design and measurements along with results of beam acceleration test will be presented.     

Electrical conductivity of a novel cast 6351 Al–Al4SiC4 in situ composite

In this research work, electrical conductivity of a novel cast 6351 Al–Al₄SiC₄ composite has been studied for varying Al₄SiC₄ particle content (2–7 vol%). Analytical models were developed on the basis of free electron theory and local resistance approach in order to predict electrical conductivity of metal matrix composites. The electrical conductivity of cast 6351 Al–Al₄SiC₄ composite was found to decrease with increasing Al₄SiC₄ content. Overprediction of results and more % deviation of the predicted electrical conductivity from experimental value were observed for local-resistance-approach-based model. However, the model developed on the basis of electron theory considering scattering of electrons at particle–matrix interface accurately predicted the experimental electrical conductivity data.