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Hydrometallurgical Extraction of Molybdenum and Rhenium from Sarcheshmeh Molybdenite Concentrates by Acidic Pressure Leaching

Khoshnevisan, Amin | 2011

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  1. Type of Document: Ph.D. Dissertation
  2. Language: Farsi
  3. Document No: 42057 (07)
  4. University: Sharif University of Technology
  5. Department: Materials Science and Engineering
  6. Advisor(s): Yoozbashizadeh, Hossein
  7. Abstract:
  8. The current study was carried out to investigate the pressure oxidative leaching of the molybdenite concentrate in nitric acid to produce molybdic oxide (technical grade) and liquor containing entire rhenium of the concentrate and molybdenum. In the first step The Taguchi method was established to design and minimize the number of experiments. By using Taguchi orthogonal (L25) array, five parameters (time, temperature, oxygen pressure, pulp density and acid concentration) in 5 levels were selected for 25 experiments. Experiments were designed and carried out in a high pressure reactor in the presence of nitric acid as solvent and oxidizing agent for the molybdenite concentrate and its ReS2 content. The optimum conditions for pressure leaching of molybdenite were obtained through using Signal to Noise analysis and modified by using Minitab software prediction tool. Furthermore, the optimum condition for an economical pressure leaching of rhenium sulfide (ReS2) was achieved with the same process. Analysis of variance (ANOVA) showed that the pulp density is of paramount importance in this process. In the second step, the effects of oxygen pressure, stirring speed, pulp density, acid concentration and temperature on the leaching rate of the molybdenum were studied. It was found that about 85% of molybdenite was oxidized to molybdic oxide precipitate with remaining molybdenum dissolved in the leaching liquor. Analysis of experimental data showed that the reaction is chemically controlled with activation energy of 68.8kJ/mol. Furthermore SEM images showed no significant boundary diffusion layer and it was noted that the molybdic oxide precipitates were of fibrous shape. In the third step, a three-layer feed-forward artificial neural network was applied to model the effect of above-mentioned parameters on the leaching ability. The leaching efficiency was considered as a target value for modeling. The quantified leaching efficiencies obtained by applying different parameters demonstrated a good agreement with neural network predictions
  9. Keywords:
  10. Rhenium ; Neural Network ; Taguchi Method ; Pressure Leaching ; Molybdenite Concentrates ; Nitric Acid

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