Nanopore structure of deep-burial coals explored by AFM

The use of AFM in quantitative analysis of pore characteristics in coal and coal-bearing shale

Quality by design in pharmaceutical manufacturing: A systematic review of current status, challenges and future perspectives.

Optimization on cleaner intensification of ozone production using Artificial Neural Network and Response Surface Methodology: Parametric and comparative study

Nanoparticles (NPs) can promote the column flotation process in mining industry. Nanoparticles’ effects on column flotation process (copper recovery, grade and flotation rate constant) are assessed in Sarcheshmeh Copper Complex, Iran, through response surface methodology (RSM) optimization technique. The γ-Al2O3, α-Fe2O3, SiO2, and TiO2 nanoparticles are selected for these experiments. A flotation rate constant is chosen as a response to assess the effect of nanoparticles on flotation in its kinetic sense. The process pH and nanoparticle dosage are selected as the influential parameters. Results obtained from RSM indicated that the maximum percentage of Cu recovery and grade is obtained at pH of 12 and nanoparticle dosage of 6 kg/t, through α-Fe2O3 and γ-Al2O3 nanoparticles, respectively. Applying nanoparticles in particular γ-Al2O3 and α-Fe2O3 increases the Cu recovery by 8–10% together with the grade by 3–6% in a significant manner. It is revealed that nanoparticles could effectively be applied in enhancing the flotation performance.

Assessment of pH-responsive nanoparticles performance on laboratory column flotation cell applying a real ore feed

Coal is the world’s most abundant energy source because of its abundance and relatively low cost. Due to the scarcity in the supply of high-grade coal, it is necessary to use low-grade coal for fulfilling energy demands of modern civilization. However, due to its high ash and moisture content, low-grade coal exerts the substantial impact on their consumption like pyrolysis, liquefaction, gasification and combustion process. The present research aimed to develop the efficient technique for the production of clean coal by optimizing the operating parameters with the help of response surface methodology. The effect of three independent variables such as hydrofluoric acid (HF) concentration (10–20% by volume), temperature (60–100 °C), and time (90–180 min), for ash reduction from the low-grade coal was investigated. A quadratic model was proposed to correlate the independent variables for maximum ash reduction at the optimum process condition by using central composite design (CCD) method. The study reveals that HF concentration was the most effective parameter for ash reduction in comparison with time and temperature. It may be due to the higher F-statistics value for HF concentration, which effects to large extent of ash reduction. The characterization of coal was evaluated by Fourier transform infrared spectroscopy (FTIR) analysis and Field-emission scanning electron microscopy with energy-dispersive X-ray (FESEM-EDX) analysis for confirmation of the ash reduction.

Application of response surface methodology (RSM) for optimization of leaching parameters for ash reduction from low-grade coal

Abstract: This study aims to check the Vertical Axis Wind Turbines blades and their different types and their feasibility. Increase in energy demand results in need of clean energy like wind energy. This project is done to design and construct the vertical axis wind turbine blade for small scale usage. The vertical axis wind turbine is having axis of rotation vertically and that’s why yaw motor is eliminated. The demand of renwable energy sources is increasing day by day as the fossil fuel is limited and will end one day as well as it has adverse effect in environment and which leads to green house effect, etc

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Himanshu Meena

Papers

Application of response surface methodology (RSM) for optimization of leaching parameters for ash reduction from low-grade coal

Design and Construction of Vertical Axis Wind Turbine Blades