Islamic Azad University

About: Islamic Azad University is a education organization based out in Tehran, Iran. It is known for research contribution in the topics: Population & Catalysis. The organization has 83635 authors who have published 113437 publications receiving 1275049 citations. The organization is also known as: Azad University.

Enhanced tensile properties of aluminium matrix composites reinforced with graphene encapsulated SiC nanoparticles

Abstract: Due to a high propensity of nano-particles to agglomerate, making aluminium matrix composites with a uniform dispersion of the nano-particles using liquid routes is an exceptionally difficult task. In this study, an innovative approach was utilised to prevent agglomeration of nano-particle by encapsulating SiC nano-particles using graphene sheets during ball milling. Subsequently, the milled mixture was incorporated into A356 molten alloy using non-contact ultrasonic vibration method. Two different shapes for graphene sheets were characterised using HRTEM, including onion-like shells encapsulating SiC particles and disk-shaped graphene nanosheets. This resulted in 45% and 84% improvement in yield strength and tensile ductility, respectively. The former was ascribed to the Orowan strengthening mechanism, while the latter is due primarily to the fiber pull-out mechanism, brought about by the alteration of the solidification mechanism from particle pushing to particle engulfment during solidification as a consequence of high thermal conductive graphene sheets encapsulating SiC particles.

Thermal conductivity modeling of MgO/EG nanofluids using experimental data and artificial neural network

Abstract: The application of nanofluids in energy systems is developing day by day. Before using a nanofluid in an energy system, it is necessary to measure the properties of nanofluids. In this paper, first the results of experiments on the thermal conductivity of MgO/ethylene glycol (EG) nanofluids in a temperature range of 25–55 °C and volume concentrations up to 5 % are presented. Different sizes of MgO nanoparticles are selected to disperse in EG, including 20, 40, 50, and 60 nm. Based on the results, an empirical correlation is presented as a function of temperature, volume fraction, and nanoparticle size. Next, the model of thermal conductivity enhancement in terms of volume fraction, particle size, and temperature was developed via neural network based on the measured data. It is observed that neural network can be used as a powerful tool to predict the thermal conductivity of nanofluids.

When pandemics impact economies and climate change: Exploring the impacts of COVID-19 on oil and electricity demand in China

Abstract: Despite all the scientific and technological developments in the past one hundred years, biologic issues such as pandemics are a constant threat to society. While one of the aspects of a pandemic is the loss of human life, the outbreak has multi-dimensional impacts across regional and global societies. In this paper, a comparative regressive and neural network model is developed to analyze the impacts of COVID-19 (coronavirus) on the electricity and petroleum demand in China. The environmental analysis shows that the epidemic severeness significantly affects the electricity and the petroleum demand, both directly and indirectly. The outputs of the model stated that the elasticity of petroleum and electricity demand toward the population of the infected people is -0.1% and -0.65%, respectively. The mentioned results show that pandemic status has a significant impact on energy demand, and also its impacts can be tracked into every corner of human society.