Predictive modelling of Fe(III) precipitation in iron removal process for bioleaching circuits.

In this study, the applicability of three modelling approaches was determined in an effort to describe complex relationships between process parameters and to predict the performance of an integrated process, which consisted of a fluidized bed bioreactor for Fe(3+) regeneration and a gravity settler for precipitative iron removal. Self-organizing maps were used to visually evaluate the associations between variables prior to the comparison of two different modelling methods, the multiple regression modelling and artificial neural network (ANN) modelling, for predicting Fe(III) precipitation. With the ANN model, an excellent match between the predicted and measured data was obtained (R (2) = 0.97). The best-fitting regression model also gave a good fit (R (2) = 0.87). This study demonstrates that ANNs and regression models are robust tools for predicting iron precipitation in the integrated process and can thus be used in the management of such systems.

Oxidation of elemental sulfur, tetrathionate and ferrous iron by the psychrotolerant Acidithiobacillus strain SS3.

Mesophilic iron and sulfur-oxidizing acidophiles are readily found in acid mine drainage sites and bioleaching operations, but relatively little is known about their activities at suboptimal temperatures and in cold environments. The purpose of this work was to characterize the oxidation of elemental sulfur (S(0)), tetrathionate (S4O6(2-)) and ferrous iron (Fe2+) by the psychrotolerant Acidithiobacillus strain SS3. The rates of elemental sulfur and tetrathionate oxidation had temperature optima of 20 degrees and 25 degrees C, respectively, determined using a temperature gradient incubator that involved narrow (1.1 degrees C) incremental increases from 5 degrees to 30 degrees C. Activation energies calculated from the Arrhenius plots were 61 and 89 kJ mol(-1) for tetrathionate and 110 kJ mol(-1) for S(0) oxidation. The oxidation of elemental sulfur produced sulfuric acid at 5 degrees C and decreased the pH to approximately 1. The low pH inhibited further oxidation of the substrate. In media with both S(0) and Fe2+, oxidation of elemental sulfur did not commence until all available ferrous iron was oxidized. These data on sequential oxidation of the two substrates are in keeping with upregulation and downregulation of several proteins previously noted in the literature. Ferric iron was reduced to Fe2+ in parallel with elemental sulfur oxidation, indicating the presence of a sulfur:ferric iron reductase system in this bacterium.

Biologically Fe2+ oxidizing fluidized bed reactor performance and controlling of Fe3+ recycle during heap bioleaching: an artificial neural network-based model.

The performance of a biological Fe(2+) oxidizing fluidized bed reactor (FBR) was modeled by a popular neural network-back-propagation algorithm over a period of 220 days at 37 degrees C under different operational conditions. A method is proposed for modeling Fe(3+) production in FBR and thereby managing the regeneration of Fe(3+) for heap leaching application, based on an artificial neural network-back-propagation algorithm. Depending on output value, relevant control strategies and actions are activated, and Fe(3+) production in FBR was considered as a critical output parameter. The modeling of effluent Fe(3+) concentration was very successful, and an excellent match was obtained between the measured and the predicted concentrations.

Kinetics of iron oxidation by Leptospirillum ferriphilum dominated culture at pH below one.

The kinetics of ferrous iron oxidation by Leptospirillum ferriphilum (L. ferriphilum) dominated culture was studied in the concentration range of 0.1-20 g Fe(2+)/L and the effect of ferric iron (0-60 g Fe(3+)/L) on Fe(2+) oxidation was investigated at pH below one. Denaturing gradient gel electrophoresis of PCR amplified 16S rRNA genes followed by partial sequencing confirmed that the bacterial community was dominated by L. ferriphilum. In batch assays, Fe(2+) oxidation started without lag phase and the oxidation was completed within 1 to 60 h depending on the initial Fe(2+) concentration. The specific Fe(2+) oxidation rates increased up to around 4 g/L and started to decrease at above 4 g/L. This implies substrate inhibition of Fe(2+) oxidation at higher concentrations. Haldane equation fitted the experimental data reasonably well (R(2) = 0.90). The maximum specific oxidation rate (q(m)) was 2.4 mg/mg VS . h, and the values of the half saturation (K(s)) and self inhibition constants (K(i)) were 413 and 8,650 mg/L, respectively. Fe(2+) oxidation was competitively inhibited by Fe(3+) and the competitive inhibition constant (K(ii)) was 830 mg/L. The time required to reach threshold Fe(2+) concentration was around 1 day and 2.3 days with initial Fe(3+) concentration of 5 and 60 g/L, respectively. The threshold Fe(2+) concentration, below which no further Fe(2+) oxidation occurred, linearly increased with increasing initial Fe(2+) and Fe(3+) concentrations. Fe(2+) oxidation proceeds by L. ferriphilum dominated culture at pH below 1 even in the presence of 60 g Fe(3+)/L. This indicates potential of using and biologically regenerating concentrated Fe(3+) sulfate solutions required, for example, in indirect tank leaching of ore concentrates.