Doctoral Degrees (Chemical Engineering)
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Browsing Doctoral Degrees (Chemical Engineering) by Author "Biley, Chris"
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- ItemThermodynamic and kinetic modelling of iron (III) reduction with sulfur dioxide gas(Stellenbosch : Stellenbosch University, 2015-03) Biley, Chris; Steyl, J. D. T.; Bradshaw, S. M.; Stellenbosch University. Faculty of Engineering. Dept. of Process Engineering.ENGLISH ABSTRACT: Recent developments in the atmospheric treatment of low-grade nickel laterite ores at Anglo American plc has culminated in the conceptual iron-focused laterite (ARFe) process. In addition to the recovery of nickel and cobalt from laterite ore, this process uniquely aims to recover iron as a saleable by-product. The reduction of soluble iron(III) (Fe(III)) by sulfur dioxide gas (SO2) is central to the ARFe concept and represents a complex, multiphase system involving simultaneous gas-liquid mass transfer, thermodynamic speciation and chemical reaction. The chemistry of iron-containing systems is generally poorly understood and accurately predicting their behaviour is challenging, especially under aggressive hydrometallurgical conditions. The primary objective of this work is the development of an engineering model capable of describing the rate and extent of ferric reduction with SO2 under conditions typical of the ARFe process. Thermodynamic considerations provide a rigorous framework for the interpretation of chemical reactions, however little experimental data are openly available for the associated solution species in acidic iron sulfate systems. A key contribution of this work, and critical for the development of the overall model, is the direct measurement of speciation in iron sulfate solutions. Raman and UV-vis spectroscopy were utilised to make direct speciation measurements in the various subsystems of the Fe2(SO4)3-FeSO4-H2SO4-H2O system that were previously unavailable in the open literature. The FeSO+4 and Fe(SO4)– 2 species were explicitly identified and measurements were supported and rationalised by static computational quantum mechanical calculations and ultimately permit the calibration of a robust, ion-interaction solution model with the explicit recognition of the important solution species up to 1.6 mol/kg Fe2(SO4)3, 0.8 mol/kg H2SO4 over 25 – 90 C. Batch and continuous Fe(III) reduction kinetics were measured and the effects of initial Fe2(SO4)3 and H2SO4 concentrations, temperature and in-situ neutralisation quantified. The retardation effect of sulfuric acid was observed to be the most significant factor influencing the initial reaction rate and the achievable extent of reduction at fixed residence time, which varied between about 20 and 80 % after 180 minutes of reaction. A reaction mechanism that is limited by the slow ligand-to-metal electron transfer in the FeIIISO+3 solution species’ decomposition is proposed and spectroscopic measurements and computational quantum mechanical calculations are used to support this mechanism. A kinetic model, comprising a system of differential mass-balance equations, is incorporated into the thermodynamic framework. This reaction model permits the prediction of kinetic profiles over the full range of experimental conditions and can be incorporated into more elaborate simulation models of the ARFe circuit. The specific original contributions of this work are • The direct measurement of aqueous speciation in the Fe2(SO4)3-H2SO4-H2O system by Raman and UV-vis spectroscopy • The development of a modelling framework to characterise speciation, activity coefficients and solubility in the mixed Fe2(SO4)3-FeSO4-H2SO4-H2O system. • The measurement of Fe(III) reduction kinetics using SO2 in concentrated sulfate solutions as a function of initial composition and temperature. • The development of a solution reaction model of Fe(III) reduction with SO2 that accurately predicts the solution speciation and reaction rate with time as a function of composition and temperature. Lastly, the vast complexity of industrial systems will nearly always result in a lack of specific experimental data that are required for the development of phenomenological models. This work emphasises the crucial role that engineering studies hold in the generation of such data to derive maximum practical value for industrial process development and optimisation.