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a b s t r a c tTo evaluate the performance of an automated sorter typically requires testing of the material to be separated on a full-scale device. In many cases limitations on the quantity of material available for testing, and the costs of the test programme, may limit the range of operating conditions examined. In this paper we propose a method for prediction of automated sorter performance, based on material and machine characteristics, which can be used to evaluate how changes to these characteristics affect performance.The distribution of particles at the point of identification is a key parameter in determining sorter efficiency. A Monte Carlo simulation was used to predict the position of particles on a feed conveyor used to deliver particles to the identification zone. The results produced show that this technique can be used to simulate the particle distribution achieved by an operating automated sorter (TiTech Combisense).Sorter efficiency depends on firstly accurate identification of the target product (typically deflected) and secondly the precision of selective deflection, using compressed air jets or mechanical actuators. A reduction of deflection efficiency is generally caused by the co-deflection of ''non-target'' particles resulting from their close proximity to particles being deflected. In order to fine tune the sorter model data from automated sorting experiments were analysed to provide information on deflection efficiency over a wide range of operating conditions. The sorter model developed for the À10 + 6 mm size fraction was shown to provide a realistic prediction for coarser (À15 + 10 mm) particles.The sorter model was used to demonstrate that sorter performance could be significantly improved by improved particle feed distribution. When a high separation efficiency is required for a sorting application a 3 stage process was predicted to have a higher separation efficiency than a single stage process using the same number of sorters.

a b s t r a c tThe efficiency of sensor-based automated sorting depends on both correct identification and separation of different types of particles. It is known that the distribution of particles fed to the sorter will affect both of these. When different particles are in close proximity, they can be ''agglomerated'' or seen as a single particle during identification and also have an increased probability of being unintentionally co-ejected. Both factors will have a negative effect on separation efficiency.The aim of this work was to model the air ejection manifold of a sensor-based automated sorter and to investigate the relationship between particle proximity and unintentional co-ejections. The airflow from a single air ejection valve of a sorter was modelled using computational fluid dynamics (CFD) software and calibrated against a Tomra Sorting Solutions optical sorter. It was found that the air ejection manifold could be accurately represented in CFD code. Particles were modelled using the discrete element method (DEM) software and the effect of particle position, relative to an air ejection valve, on accurate ejection was examined using an integrated CFD-DEM model. The results of these models matched reasonably well with physical measurements. The models created can be used as a basis for the prediction of sorter efficiency.

Rare earth elements (REE) are critical to a wide range of technologies ranging from mobile phones to wind turbines. Processing and extraction of REE minerals from ore bodies is, however, both challenging and relatively poorly understood, as the majority of deposits contain only limited enrichment of REEs. An improved understanding of the surface properties of the minerals is important in informing and optimising their processing, in particular for separation by froth flotation. The measurement of zeta potential can be used to extract information regarding the electrical double layer, and hence surface properties of these minerals. There are over 34 REE fluorcarbonate minerals currently identified, however bastnäsite, synchysite and parisite are of most economic importance. Bastnäsite-(Ce), the most common REE fluorcarbonate, supplies over 50% of the world's REE. Previous studies of bastnäsite have showed a wide range of surface behaviour, with the iso-electric point (IEP), being measured between pH values of 4.6 and 9.3. In contrast, no values of IEP have been reported for parisite or synchysite. In this work, we review previous studies of the zeta potentials of bastnäsite to investigate the effects of different methodologies and sample preparation. In addition, measurements of zeta potentials of parisite under water, collector and supernatant conditions were conducted, the first to be reported. These results showed an iso-electric point for parisite of 5.6 under water, with a shift to a more negative zeta potential with both collector (hydroxamic and fatty acids) and supernatant conditions. The IEP with collectors and supernatant was <3.5. As zeta potential measurements in the presence of reagents and supernatants are the most rigorous way of determining the efficiency of a flotation reagent, the agreement between parisite zeta potentials obtained here and previous work on bastnäsite suggests that parisite may be processed using similar reagent schemes to bastnäsite. This is important for future processing of REE deposits, comprising of more complex REE mineralogy.

Abstract:Tungsten is considered by the European Union as a critical raw material for future development due to its expected demand and scarcity of resource within Europe. It is therefore, critical to optimize European tungsten operations and maximise recoveries. The role of enhanced gravity/centrifugal concentrators in recovering tungsten from ultra-fine fractions should form an important part of this aim. Reported herein are the results of investigations to improve efficiency of Wolf Minerals' Draklends mine, a major European tungsten mine, by recovering saleable material from a magnetic waste stream of a low-intensity magnetic separator using an enhanced gravity concentrator. The mine hosts wolframite and ferberite as the main tungsten bearing mineral species. A Mozley multi-gravity separator (MGS) C-900 was selected as it is suited to exploiting small variations in mineral density to affect a separation. Working with a current manufacturer, a novel scraping blade system was tested. To assess the MGS in a statistically valid manner, a response surface methodology was followed to determine optimal test conditions. The test programme showed that the most important parameters were drum speed and wash water rate. Under optimal conditions the model predicted that 40% of the tungsten could be recovered above the required grade of 43% WO 3 .