Frictional behaviour of bonded solid film lubricants

The friction-reducing action of bonded solid lubricants is explained on the basis of deformation of the layered film. The plane strain problem of an elastic cylinder indenting on an elastic layer bonded to an elastic half-space is used to explain the frictional behaviour of dry film lubricants.     

Synergistic effect of graphene with graphene oxide,nanoclay, and nanosilica in enhancing the mechanical and barrier properties of bromobutyl rubber/epoxidized natural rubber composites

The present work aims to investigate the effect of hybrid nanofillers in bromobutyl rubber/epoxidized natural rubber (ENR 50) composites for developing highly air-impermeable nanocomposites. The nanocomposites with hybrid nanofillers were prepared by a simple melt mixing method, and the morphology of the developed nanocomposites was studied using X-Ray diffraction, transmission electron microscopy, and atomic force microscopy. Improvement in the mechanical, barrier and dynamic properties can be observed for hybrid nanocomposites compared to the composites filled with individual graphene nanoplatelets (GNPs). The strong interfacial attraction between GNP monolayers enhance its aggregation in nanocomposites. While, in the current study the results are showing that the addition of graphene oxide, nanoclay, and nanosilica enhances the dispersion of GNP in the composites. The homogeneous dispersion of GNP nanofillers will develop a tortuous pathway in the composites, which are responsible for their air barrier properties. Bound rubber content and dynamic strain measurements (Payne effect) show a maximum value for binary nanocomposites.     

Nano-phases of NaBH4 and KBH4

Phase stability and chemical bonding of beta-NaBH4 and beta-KBH4 derived nano-structures and possible low energy surfaces of them from thin film geometry have been investigated using ab initio projected augmented plane wave method. Structural optimizations based on total energy calculations predicted that, for beta-NaBH4 and beta-KBH4 phases, the (011) and (101) surfaces are more stable among the possible low energy surfaces. The predicted critical size of the nano-cluster for beta-NaBH4 and beta-KBH4 is 1.35 and 1.8 nm, respectively. The corresponding critical diameter for the nano-whisker is 2.6 and 2.8 nm respectively for beta-NaBH4 and beta-KBH4. Structural optimization based on total energy calculations show that the bond distances in the surfaces of nano-whisker are found to be higher than that in the bulk material and the calculated H site energies and bond overlap population analysis suggesting that it is considerably easier to remove hydrogen from the surface of the clusters and nano-whiskers than that from the bulk crystals.     

Breadfruit (Artocarpus communis) meal: Nutrient composition and feeding value for broilers

Breadfruit (Artocarpus communis) meal was found to contain (g kg dry matter) 59 crude protein, 14 crude fat, 59 crude fibre, 34 ash and 834 available carbohydrates. The amino acid composition of breadfruit meal (BFM) compared closely with that of maize. The nitrogen-corrected apparent metabolisable energy value of BFM was determined to be 13.89 MJ kg^?1 dry matter. Two trials were conducted to evaluate the feeding value of BFM in broiler diets. In trial 1. BFM was included in broiler starter and finisher diets at 0, 125 and 250 g kg^?1 replacing maize. In trial 2, BFM was incorporated in broiler starter diets at 0, 200 and 400 g kg^?1 replacing maize. The results indicate that BFM supported broiler performance as efficiently as maize at all dietary levels tested.     

Magnetic susceptibility and specific heat of Pr2?xCexCuO4?y

We report here the measurements of magnetic susceptibility of Pr_2–xCe_xCuO_4–y (x=0, 0.05 and 0.15) from 2K to 300K and the specific heat of Pr_1.85Ce_0.15CuO₄ between 6K and 60K. Fitting of the magnetic susceptibility data to a Curie-Weiss law gave effective magnetic moment (p_eff) values close to the free ion value of 3.58_B for Pr³⁺. p_eff was found to decrease with increase in cerium concentration. The site symmetry of Pr³⁺ in Pr_2–xCe_xCuO_4–y (PCCO) host is D_4h and a crystal field (CF) Hamiltonian appropriate to tetragonal symmetry was used to analyze the magnetic susceptibility data. J-mixing of all the thirteen multiplets of Pr³⁺ and intermediate coupled wave functions have been included. A best set of CF parameters obtained not only explains the magnetic susceptibility but also the inelastic neutron scattering spectra (INS) reasonably well. The Schottky component together with Debye and Einstein contributions successfully accounts for the measured specific heat.     

Fragility analysis of continuous pipelines subjected to transverse permanent ground deformation

The structural integrity of buried continuous pipelines can be jeopardized by transverse permanent ground deformation (PGD) induced by landslides. A probabilistic analysis can facilitate understanding the likelihood of damage to pipelines in landslide regions, further minimizing the risk. However, empirical fragility curves for the landslide-pipeline interaction problem are not available due to the lack of field data. The problem can be addressed by numerical approaches. In this study, a simplified two-dimensional numerical model is developed. It characterizes the pipes as beam-type structures and the surrounding soil as Winkler springs. It is compared here against three-dimensional continuum-based analyses, which could save extensively on computational efforts. All input parameters were sampled randomly and paired with the displacement demands to form a limited set of statistically significant, yet nominally identical, pipeline samples, and the demand models for the maximum tensile strain were evaluated. A supervised machine learning technique, called Lasso regression, was then used to establish a predictive relation between the input and the output using the limited dataset, based on which a large dataset (one million) was calculated for the fragility analysis. The use of a Winkler-based analysis and the supervised machine learning technique makes it possible to generate fragility curves for pipelines subjected to transverse PGD for the first time.