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作 者:Onyedika Gerald Ugwu Priscilla Ogwuegbu Martin Ejike Emmanuel Nwoye Chukwuka Jiann-Yang Hwang
机构地区:[1]Department of Metallurgical and Materials Engineering, Nnamdi Azikiwe University, Awka, Nigeria [2]Materials Science and Engineering, Michigan Technological University, 1400 Townsend Dr., Houghton, Michigan, U.S.A. [3]Mineral Processing Unit, Department of Chemistry, Federal University of Technology, P.M.B. 1526, Owerri, Nigeria
出 处:《Journal of Minerals and Materials Characterization and Engineering》2012年第7期730-734,共5页矿物质和材料特性和工程(英文)
摘 要:Model for prediction of the concentration of tin extracted during potassium hydroxide leaching of cassiterite has been derived. The model: A = Nt1.53, indicates that the concentration tin extracted is dependent on the residence time. It was found that the validity of the model is rooted in the expression Log A = Log (Nt1.53). Tin extraction per unit time as obtained from experiment and derived model are 2.6666 and 2.6268 mg/min respectively. The maximum deviation of the model-predicted concentration of dissolved tin from the corresponding concentration obtained from the experiment was found to be less than 8%, which is quite within the acceptable deviation limit of experimental results and hence, impacting about 92% confidence coefficient on the model.Model for prediction of the concentration of tin extracted during potassium hydroxide leaching of cassiterite has been derived. The model: A = Nt1.53, indicates that the concentration tin extracted is dependent on the residence time. It was found that the validity of the model is rooted in the expression Log A = Log (Nt1.53). Tin extraction per unit time as obtained from experiment and derived model are 2.6666 and 2.6268 mg/min respectively. The maximum deviation of the model-predicted concentration of dissolved tin from the corresponding concentration obtained from the experiment was found to be less than 8%, which is quite within the acceptable deviation limit of experimental results and hence, impacting about 92% confidence coefficient on the model.
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