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.     

Finite sample properties of estimators of spatial autoregressive models with autoregressive disturbances

The article investigates the finite sample properties of estimators for spatial autoregressive models where the disturbance terms may follow a spatial autoregressive process. In particular we investigate the finite sample behavior of the feasible generalized spatial two-stage least squares (FGS2SLS) estimator introduced by Kelejian and Prucha (1998), the maximum likelihood (ML) estimator, as well as that of several other estimators. We find that the FGS2SLS estimator is virtually as efficient as the ML estimator. This is important because the ML estimator is computationally burdensome, and may even be forbidding in large samples, while the FGS2SLS estimator remains computationally feasible in large samples. Received: 20 January 2001 / Accepted: 31 August 2001     

Evaluation of improvement of physical and mechanical properties of bamboo fibers due to alkali treatment

Bamboo strips treated with caustic solutions of different concentrations, e.g., 5%, 10%, 15%, 20%, 25%, and 50%, were subjected to mechanical testing giving stresses on tensile strength, percent elongation at break, flexural strength, flexural modulus, and toughness. The change in average density was ?15%, and the weight loss value shows a maximum of 21.94% at 50% alkali treatment. The mechanical properties of bamboo strips increase steadily with increasing concentration of caustic soda, showing a comparable increased value at 15 and 20%, and then exhibiting a gradual fall. The percent elongation at break corroborates these observations showing a continuous decreasing trend. The properties under investigation exhibit a clear transition in between 15 and 20% alkali concentration. The morphology of strips was studied by scanning electron microscope and polarizing light microscope. The crystal structure of both untreated and treated strips was compared by XRD analysis. In both cases, the breakdown of the crystal structures of the cellulose fibers and the recrystallization or reorientation of the degraded chains that are devoid of hemicellulose are quite apparent. However, at a very high concentration (to the extent of 25%) the breakdown of structure predominates much more over the reorientation or recrystallization. © 2007 Wiley Periodicals, Inc. J Appl Polym Sci, 2008     

Chitosan-based magnetic molecularly imprinted polymer: synthesis and application in selective recognition of tricyclazole from rice and water samples

A tricyclazole selective chitosan/Fe₃O₄ magnetic molecularly imprinted polymer (MMIP) was synthesized using non-covalent binding polymerization involving methacrylic acid (MAA) as functional monomer, divinylbenzene (DVB-80) as crosslinker, 2,2'-azobisisobutyronitrile as initiator, acetonitrile/toluene (75:25, v/v) as porogenic solvent and tricyclazole as template. Surface morphology and magnetic characterization of the prepared imprinted and non-imprinted polymers were done using scanning electron microscopy, transmission electron microscopy, Fourier transform infrared spectrometry and vibrating sample magnetometry, respectively. The adsorption kinetic data fitted best in pseudo-second-order model. The adsorption equilibrium was achieved in 30 min and the maximum binding capacity was 4579.9 µg/g. The Freundlich isotherm model was found suitable for explaining the binding isotherm data (R² > 0.99). Negative values of thermodynamic parameters ∆G (Gibb’s free energy), ∆H (enthalpy), and ∆S (entropy) revealed exothermic and spontaneous nature of adsorption processes. It also revealed decreased randomness at the solid–liquid interface during sorption. The scatchard plot analysis suggested heterogeneity of binding sites on MMIPs. The molecular recognition selectivity of MMIPs towards tricyclazole was much higher, as compared to its structural analogues, tebuconazole (α = 28.58) and hexaconazole (α = 37.16). The MMIPs were successfully applied to separate and enrich tricyclazole from fortified samples of rice and water, with a recovery percentage of 89.4% and 90.9%, respectively. These reusable imprinted polymers possessing high selectivity and specificity can be utilized as an adsorbent for solid-phase extraction in sample preparation for tricyclazole residue analysis in complex environmental matrices.

     

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...     

Studies on engineering properties of PVC–PMMA semi‐interpenetrating polymer networks

Semi1 and semi2 interpenetrating polymer networks (IPNs) of PVC and in situ formed PMMA have been synthesized using diallyl phthalate and ethylene glycol dimethacrylate as the crosslinkers of PVC and PMMA, respectively. These two types of IPNs have been compared w.r.t their physical, mechanical, and thermal properties and an endeavor has been made to find a correlation of these properties with the morphology generated in these systems. The semi1 IPNs displayed a decrease in their mechanical parameters and the physical properties as well, while in contrast, the semi2 IPNs exhibited a marginal increase in the corresponding values after an initial drop upto about 15% of crosslinked PMMA incorporation when compared to the crosslinked PVC in the case of semi1 IPN and linear PVC in the case of semi2 IPN. The various samples of semi1 and semi2 IPNs showed a two‐stage degradation typical of PVC, while confirming the increased stability with the samples having higher percentages of PMMA. The influence of crosslinking of the major matrix in semi1 IPN was almost counterbalanced by the influence of crosslinking in the dispersed PMMA phase in the case of semi2 IPN. The softening characteristics as detected by the extent of penetration of the probe, as has been detected by thermomechanical analysis, are in conformity with their mechanicals. © 2005 Wiley Periodicals, Inc. J Appl Polym Sci 97: 1725–1735, 2005     

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.     

Impact of network effects and diffusion channels on home computer adoption

Researchers have identified network effects as one of the major drivers for the adoption and diffusion of household technologies. However, the mechanisms and social contexts through which network effects induce technology adoption are unclear. In this paper, we investigate the adoption of household computers using the dataset from the 1989-2003 Computer and Internet Supplement to the Current Population Surveys (CPS). We argue that social influence and learning play a dominant role in inducing the adoption of home computers, and workplaces and schools are important channels through which network effects take place. We find that recent adopters have a stronger impact than distant adopters on future computer adoptions. When the adoption rate is low, channels play a more important role, but their effects diminish as the adoption rate grows. We also find that diffusion channels are more effective for first-time adoption than for repeat purchases. Overall, our study provides important theoretical, policy, and managerial implications.