Dynamic modelling of competitive elution of activated carbon in columns using neural networks

Abstract In previous papers the mechanism and dynamics of the elution of gold cyanide from activated carbon have been investigated in detail. Sub processes such as the pre-soaking step, the degradation of cyanide, the elution of the spectator cations, the associated shift in the equilibrium of adsorption or desorption as a result of the removal of cations, the reactivation of the carbon surface, and the elution of gold cyanide have been explained quantitatively to some extent, although further work is evidently required Previous work has also shown that equilibrium conditions may be' assumed when adsorption is weak, hence when aggressive pre-soaking conditions have been used. However, these studies have not taken the competitive effect of base metals into account, although this is known to have an adverse effect on the efficiency of gold elution. The present study has shown quantitatively that copper has a significant effect on the recovery of gold. Nickel and silver also have a detrimental effect, but only if they are present as high loadings. In contrast, the elution of the base metals is to a large degree unaffected by the elution of gold. It is shown in this paper that the multi-component equilibrium relationship between the spectator cations and the various metal cyanides can be very complex, and perhaps ill-defined. In such circumstances it is preferable to use a non-parametric technique such as a back-propagation neural network to represent such an equilibrium relationship. Owing to the difficulty of estimating the final conditions of the pre-soaking step, it is not always possible to predict the exact level of equilibrium. Therefore, it could be necessary in practice to adjust the equilibrium predicted by a neural net by a factor which is dependent on the conditions of pre-soaking.