Prediction of Mechanical Properties of Graphene Oxide Reinforced Aluminum Composites

Estimating the effect of graphene oxide (GO) reinforcement on overall properties of aluminum (Al) matrix composites experimentally is time-consuming and involves high manufacturing costs and sophisticated characterizations. An attempt was made in this paper to predict the mechanical properties of GO/Al composites by using a micromechanical finite element approach. The materials used for prediction included monolayer and multilayer GO layers distributed uniformly on the spherical Al matrix particles. The estimation was done by assuming that a representative volumetric element (RVE) represents the composite structure, and reinforcement and matrix were modeled as continuum. The load transfer between the GO reinforcement and Al was modeled using joint elements that connect the two materials. The numerical results from the finite element model were compared with Voigt model and experimental results from the GO/Al composites produced at optimized process parameters. A good agreement of numerical results with the theoretical models was noted. The load-bearing capacity of the Al matrix increased with the addition of GO layers, however, Young’s modulus of the GO/Al composites decreased with an increase in the number of layers from monolayer to 5 layers. The numerical results presented in this paper have demonstrated the applicability of the current approach for predicting the overall properties of composites

EVALUATION OF MEDHOVIKAS, A HERBAL FORMULATION FOR ANTIDEPRESSANT ACTIVITY

Objective: The present study was conducted to evaluate the antidepressant activity of Medhovikas and its activity is compared with that of Imipramine and Mentat. The MAO-A and MAO-B levels were estimated by the Biochemical Method.Methods: There are several methods available to evaluate the antidepressant activity. In the present study the antidepressant activity is assessed using behavioural despair method such as Forced swim test (FST) in mice. Imipramine is used as a positive control in doses of 10mg/kg and 20mg/kg, Similar activity was also observed with Medhovikas in doses of 200 and 400mg/kg. Biochemical method in rats to estimate the levels of MAO-A and MAO-B, the biogenic amine 5-HT is oxidized by MAO to 5-hydrixy indole acetic acid (5-HIAA) as a major metabolite and is excreted in urine. Hence the reduction in the urinary 5-HIAA level from normal after treatment with the test compound was taken as a measure of it's MAO inhibitory action.Results : The antidepressant activity of 200 and 400mg/kg of Medhovikas was equivalent to that of 10 and 20mg/kg of imipramine respectively. It significantly reduced the duration of immobility indicating antidepressant activity. Significant decrease in brain MAO-A and MAO-B levels were observed which was determined by the Biochemical method.Conclusion: Antidepressant activity was probably shown by inhibiting MAO-A and MAO-B, There are several methods to detect the monoamine oxidaise inhibitor activity of substances. These methods are based on biochemical estimation of biogenic amines and /or their pharmacological responses. This shows that Medhovikas is a potential antidepressant and the probable mechanism of action is in interest for further investigation.Keywords: Antidepressant, Forced swim test, Imipramine,MAO-A & B, Medhovika and Menta

PHARMACEUTICAL PROCESSING AND ANALYTICAL STUDY OF TRIVANGA BHASMA

Background: Rasashastra is a branch of Ayurvedic pharmaceutics, which deals with the conversion of metals & minerals into potent medicines. In Rasashastra, the metals like gold, silver, copper, iron, lead, tin, zinc etc. are converted in to Bhasma and are applied in therapeutics. Validity of this branch of science totally depends on the successful completion of the practical aspects with careful observations, and it becomes necessary to perform analytical studies to check the quality of the finished products. Hence, the present study was carried out to understand the pharmaceutical processing and to analyze the Trivanga Bhasma with the aid of classical tests and modern analytical tools.Materials & Methods: Trivanga Bhasma was prepared by subjecting the Vanga, Naga & Yashada to Samanya & Vishesha Shodhana, Jarana and Marana processes as per the classical references. Final product was then subjected to all the classical Bhasmaparikshas and also analyzed by adopting modern analytical techniques.Results & Conclusion: Yellow coloured Trivanga Bhasma which passed all the Bhasmaparikshas was obtained after seventeen Laghuputas. Percentile of tin, lead & zinc were noted

Graphene and derivatives – Synthesis techniques, properties and their energy applications

2D nanomaterials with exceptional electrical, mechanical and thermal properties are promising reinforcing materials for fabricating high-performance composite materials. Rapid developments in nanotechnology in recent years have facilitated the development of advanced materials for functional devices. In particular, this review is focussed on the application of graphene nanoparticle-based composites (GNP's) and graphene derivatives in the fields of energy storage and conversion devices. This review focuses on these recent developments including the synthesis of graphene-based materials and its derivative, as well as the related achieved electrical, mechanical and thermal properties

Parametric study for graphene reinforced aluminum matrix composites production using Box Behnken design

The production of graphene reinforced aluminum matrix composite through powder metallurgical route requires optimization of process parameters to obtain better performance characteristics. One of the advanced method available for statistical analysis of parameters is Response Surface Methodology (RSM). The statistical analysis was carried out with three parameters, weight percentage of graphene reinforcement Wg (0.05%, 0.1% and 0.2%), stirring time ST(1h, 2h and 3h) and compaction pressure Pc(16T, 17T and 19T) while sintering temperature T kept constant. The performance of the Box Behnken design was analyzed and optimized using Design Expert software for the effective production of composites. From the results obtained from the analysis, the best set of parameters were considered for the future production of composites

Mechanical properties of graphene oxide reinforced aluminium matrix composites

In this paper, the properties of powder metallurgy produced samples of GO reinforced aluminium composites were examined. Discs of 20 mm diameter and 0.5 mm thickness were made from pure Al powder of 35 μm particle size and with GO reinforcement at different GO wt% (0.05, 0.1 and 0.2). The mixture of Al/GO powders prepared through liquid infiltration were cold compacted and then sintered. The GO reinforced Al matrix composites were characterised using the scanning e lectron microscope with energy dispersion spectroscopy (SEM/ EDX ) for investigation of the homogeneous dispersion of GO into the matrix. X - ray diffraction (XRD) analysis for crystallographic phase and micro - Raman spectroscopy w as used to identify the phases inside the composite matrix after the sintering process. Micro hardness and the strength values from the produced Al/GO composites were recorded. It is evident from the results obtained that where uniform mixing is achieved, GO reinforced Al composites ca n be produced with similar hardness values as for those produced from rGO reinforced Al composites

Observation of sub-Poisson photon statistics in the cavity-QED microlaser

We have measured the second-order correlation function of the cavity-QED microlaser output and observed a transition from photon bunching to antibunching with increasing average number of intracavity atoms. The observed correlation times and the transition from super- to sub-Poisson photon statistics can be well described by gain-loss feedback or enhanced/reduced restoring action against fluctuations in photon number in the context of a quantum microlaser theory and a photon rate equation picture. However, the theory predicts a degree of antibunching several times larger than that observed, which may indicate the inadequacy of its treatment of atomic velocity distributions.Comment: 4 pages, 4 figure

Theoretically Efficient Parallel Graph Algorithms Can Be Fast and Scalable

There has been significant recent interest in parallel graph processing due to the need to quickly analyze the large graphs available today. Many graph codes have been designed for distributed memory or external memory. However, today even the largest publicly-available real-world graph (the Hyperlink Web graph with over 3.5 billion vertices and 128 billion edges) can fit in the memory of a single commodity multicore server. Nevertheless, most experimental work in the literature report results on much smaller graphs, and the ones for the Hyperlink graph use distributed or external memory. Therefore, it is natural to ask whether we can efficiently solve a broad class of graph problems on this graph in memory. This paper shows that theoretically-efficient parallel graph algorithms can scale to the largest publicly-available graphs using a single machine with a terabyte of RAM, processing them in minutes. We give implementations of theoretically-efficient parallel algorithms for 20 important graph problems. We also present the optimizations and techniques that we used in our implementations, which were crucial in enabling us to process these large graphs quickly. We show that the running times of our implementations outperform existing state-of-the-art implementations on the largest real-world graphs. For many of the problems that we consider, this is the first time they have been solved on graphs at this scale. We have made the implementations developed in this work publicly-available as the Graph-Based Benchmark Suite (GBBS).Comment: This is the full version of the paper appearing in the ACM Symposium on Parallelism in Algorithms and Architectures (SPAA), 201