Kinetic modelling of a solid-liquid reaction using matlab- oxidation of metallic iron to iron sulphate from FeTiN composite

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Date
2016-06
Authors
Wan Kin Choong
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The leaching of FeTiN was investigated to find out the optimum condition to achieve the highest iron extraction within the range of studies in this project. In this project, the sample is produced by reduction of rutile, carbon and iron oxide in hydrogen-nitrogen gas mixture atmosphere at temperature of 1250°C for 3 hours. Carbon to reducible oxygen of rutile molar ratio of 2:1 was selected to enhance the reduction process. Then leaching of the FeTiN was carried out with three different factors, which are leaching temperature, leaching time and concentration of sulfuric acid. Data analysis was carried out by using 2k factorial design with variation of parameters to define the optimum parameters in percentage of iron extracted and titanium extracted. A shrinking core model were employed for the kinetic modeling process in order to predict the percentage of iron extracted. The models were developed from independently measured physical and thermodynamic properties of the reaction system and verified by experimental results. From DOE analysis, the leaching temperature has shown as most significant parameter in the percentage of iron and titanium extraction compared to others parameters. The highest iron and titanium extraction are obtain from the same parameter which is from the highest levels for leaching temperature, leaching time and concentration of sulfuric acid. This was achieved by using leaching time at 95°C for 3 hour with 12wt% of sulfuric acid. The highest percentage of iron extracted and the percentage of titanium extracted in this project was 97.09% and 35.16% respectively. From the results of kinetic modelling, the similarity of trend between predicted model and experimental results indicate that the prediction is close to the experimental results. Therefore, the theory and experiment results are indicate close correlation between them and are explaining the correctness of the models reasonably.
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