Quantitative X-Ray CT Measurement of the Effect of Ore Characteristics On

minerals

Article Quantitative X-ray µCT Measurement of the Eﬀect of Ore Characteristics on Non-Surface Mineral Grain Leaching

Mahdi Ghadiri 1,2,3 , Susan T.L. Harrison 3 and Marijke A. Fagan-Endres 3,* 1 Institute of Research and Development, Duy Tan University, Da Nang 550000, Vietnam; [email protected] 2 The Faculty of Environment and Chemical Engineering, Duy Tan University, Da Nang 550000, Vietnam 3 Centre for Bioprocess Engineering Research, Department of Chemical Engineering, University of Cape Town, South Lane, Rondebosch, Cape Town 7700, South Africa; [email protected] * Correspondence: [email protected]; Tel.: +27-21-650-1806

Received: 30 June 2020; Accepted: 14 August 2020; Published: 23 August 2020

Abstract: In heap (bio)leaching processes, a substantial fraction of the valuable mineral is positioned below the ore particle surface. X-ray micro-computed tomography (µCT) was used to quantify the effect of ore type and structure and operating temperature on the leaching of this mineral, to investigate the rate-controlling factors. Mini-leaching columns containing agglomerated chalcopyrite, pyrite, and malachite ores were scanned by X-ray µCT (13.40 µm resolution) at select time intervals. The leaching of a relatively porous malachite ore was reaction-controlled, with no leaching penetration limitation into the ore particles. For two less porous ore types, the structure and higher porosity of the agglomerate rim and conditions that resulted in the degradation of the full ore matrix structure were found to be the determining variables of the leaching extent and time. In the case of a chalcopyrite ore, an enhancement of copper recovery and sulphide mineral dissolution with increasing temperature was attributable to the increased leaching penetration distance and crack development in addition to thermodynamically expected increased leaching rate. Increasing temperature did not affect the maximum penetration distance for the waste rock containing pyrite, with no crack development observed. Overall increases in iron recovery were due to accelerated leaching rates, though diffusion or mineral access limitations were evident at a higher temperature.

Keywords: leaching; non-surface mineral; copper; ore type; temperature; porosity; X-ray; tomography

1. Introduction The efficiency of the chemical or microbial dissolution of mineral grains during heap leaching is strongly dependent on the ore nature. This includes its type, origin, and chemical composition [1,2]. Depending on these factors, different intermediates can be formed during metal dissolution and this affects mineral leaching kinetics [3]. Copper-bearing ores are found in various forms of oxides, primary and secondary sulphides. Oxides such as tenorite and malachite might need only hours of leaching to achieve a high extraction value, even at low temperatures, while secondary sulphides like chalcocite and covellite require months of leaching. Chalcopyrite, the world’s main copper resource, can require years of leaching [2]. In addition to knowledge of the main mineral of interest, an ore’s overall mineral composition is also important. Most copper ores contain pyrite and its presence can have some disadvantages such as the precipitation of potentially interfering ferri-hydroxides and jarosite. In aerated heaps, it can scavenge available oxygen. However, pyrite oxidation is also advantageous as it provides acid and heat in the heap [1]. The presence of gangue minerals such as silicate and limonite consume

Minerals 2020, 10, 746; doi:10.3390/min10090746 www.mdpi.com/journal/minerals Minerals 2020, 10, 746 2 of 27 acid during initial leaching. Soluble silicate breakdown products may regenerate acid by reaction with each other during the formation of various precipitates and form new solid silicate alteration products [4]. Sulphide minerals also exhibit a surface rest potential and can therefore corrode by galvanic action [5]. For example, galvanic interaction between pyrite and copper sulphide minerals causes the copper minerals to corrode more rapidly than the pyrite and this effect is accelerated in the presence of micro-organisms [6]. Heap (bio)leaching reactions are exothermic and temperatures in heaps are typically higher than ambient, varying with position in an ore bed. Increasing temperature changes the microbial community in a bioleach from predominantly mesophilic to thermo-tolerant and moderate thermophilic microorganisms to thermophilic microorganisms [7]. Chalcopyrite leaching in particular is known to require higher temperatures to achieve a rapid copper leaching rate [2], due to the high values of 1 activation energy (130.7 kJ mol− in the temperature range between 35 and 68 ◦C[8]) required to break down bonds in the chalcopyrite crystal lattice. Temperature, additionally, has an effect on the physical properties of the heap liquid, including the viscosity, density and solubility of copper sulphates in a saturated solution [9]. Increases in the temperature lead to the enhancement of density and solubility but the reduction of viscosity [9], with both of these factors affecting oxygen mass transfer from the gas phase to liquid phase in a heap [10]. The target mineral grain dissemination and size in large ore particles plays a vital role in heap leaching performance because the contact of mineral grains and leaching reagent is necessary for leaching of the mineral grain to occur [11]. The effect of temperature, ore type and the addition of chemicals on bulk metal recovery have long been quantified based on solution chemistry results and traditional mineralogical analyses (e.g., X-ray diffraction (XRD), quantitative evaluation of minerals by scanning electron microscopy (QEMSCAN), and scanning electron microscope (SEM)), but these techniques cannot be used to study the effect of interplay between these operating parameters and ore particle structure and the mineral grains’ position in particles. However, analytical tomographic techniques such as high-resolution X-ray micro-computed tomography (µCT) have opened new avenues for the study of non-surface grain leaching [12,13]. In the current study, the visualisation and quantitative analysis using X-ray µCT was used to track non-surface mineral grain leaching for different mineral ore types, selected because of their different physical and mineral leaching characteristics (malachite, pyrite and chalcopyrite). Critical to this is the inclusion of the effect of temperature on the leaching behaviour, as this operating parameter is intrinsically tied to the leaching system optimisation for the various ores. The aim of the work was to disaggregate the various potential effects of the conditions and identify the leaching rate controlling factors, and so to advise towards higher metal recoveries.

2. Experimental

2.1. Ores

Three diﬀerent ores were used: a malachite (Cu2(OH)2CO3) ore provided by Mintek (South Africa), a waste rock containing pyrite (FeS2) obtained from the Gamsberg mine in South Africa, and a Pinto Valley (Arizona, USA) chalcopyrite (CuFeS2) ore. The mineralogical characterisation of the ores was done through quantitative evaluation of minerals by scanning electron microscopy (QEMSCAN), using the unit located at the University of Cape Town (FEI QEMSCAN 650F with two Bruker silicon drift detector (SDD) detectors, Cape Town, South Africa). Operating conditions were set at 25 kV and 10 nÅ beam current. Individual ore particles (8 to 16 mm) were analysed using the Field Image analysis routine. A pixel spacing of 14.5 µm was used for the Field Image analysis and the determination of grain size distribution. Ore samples were mounted in epoxy resin and prepared into 30 mm diameter polished resin blocks. In the bulk mineralogy routine, used for quantitative mineral composition determination, all size fractions with a Minerals 2020, 10, x FOR PEER REVIEW 3 of 28 Minerals 2020, 10, 746 3 of 27 The chalcopyrite ore comprised 1.5 wt% chalcopyrite, 0.7 wt% pyrite and 0.3 wt% other sulphide minerals, while the pyrite ore contained 29.4 wt% pyrite, 6.3 wt% sulphide trap and 3.5 wt% certain weight percentage were mixed and ground using a pulveriser and then the ground ore was pyrrhotite. In the malachite ore, the dominant copper minerals were malachite (6.8 wt%) and bornite mounted in epoxy resin [14]. (2.4 wt%). The main gangue minerals found in the three ores are detailed in Table 1. The chalcopyrite ore comprised 1.5 wt% chalcopyrite, 0.7 wt% pyrite and 0.3 wt% other sulphide minerals, while the pyrite ore contained 29.4 wt% pyrite, 6.3 wt% sulphide trap and 3.5 wt% pyrrhotite. Table 1. Main gangue mineral constituents of the three ores. In the malachite ore, the dominant copper minerals were malachite (6.8 wt%) and bornite (2.4 wt%). The main gangueChalcopyrite minerals found in the three oresPyrite are detailed in Table1. Malachite Mineral Amount (wt%) Mineral Amount (wt%) Mineral Amount (wt%) Quartz 37.6Table 1. Main gangueQuartz mineral constituents16.5 of the threeQuartz ores. 76.8 Muscovite 19.1 Muscovite 29.6 Muscovite 3.6 Chalcopyrite Pyrite Malachite K-feldspar 37.5 Limonite 5.0 Fe–Ti oxide 4.5 Mineral Amount (wt%) Mineral Amount (wt%) Mineral Amount (wt%) Other 3.3 Other 9.7 Other 5.9 Quartz 37.6 Quartz 16.5 Quartz 76.8 2.1.1.Muscovite Ore Particle Size 19.1 Distribution Muscovite 29.6 Muscovite 3.6 K-feldspar 37.5 Limonite 5.0 Fe–Ti oxide 4.5 OtherThe chalcopyrite 3.3 ore sample, after Other primary crushing 9.7 by a hydraulic Other rock splitter 5.9 into small particles, was further reduced in size by the Sturtevant laboratory jaw-crusher. The waste rock and 2.1.1.malachite Ore Particle ores were Size received Distribution ready crushed. The ores were sieved into six fractions (<0.25 mm, 0.25–1 mm, 1–2 mm, 2–5.6 mm, 5.6–8 mm, 8– The chalcopyrite ore sample, after primary crushing by a hydraulic rock splitter into small particles, 16 mm). Figure 1 shows the resulting cumulative particle size distribution (PSD) of the chalcopyrite, was further reduced in size by the Sturtevant laboratory jaw-crusher. The waste rock and malachite to which the other ores were matched. ores were received ready crushed. Each ore size fraction was representatively split into small portions using a rotary splitter. The The ores were sieved into six fractions (<0.25 mm, 0.25–1 mm, 1–2 mm, 2–5.6 mm, 5.6–8 mm, different size fractions were selectively recombined to create 50 g batches of representative samples 8–16 mm). Figure1 shows the resulting cumulative particle size distribution (PSD) of the chalcopyrite, for testing. to which the other ores were matched.

100 90 80 70 60 50 40 30 20 10 Cumulative percent passing (%) percent Cumulative 0 1 10 100 1000 10000 100000 Particle size (µm)

Figure 1. Particle size distributions of the chalcopyrite ore. Figure 1. Particle size distributions of the chalcopyrite ore. Each ore size fraction was representatively split into small portions using a rotary splitter. The2.1.2. diﬀ erentOre A sizegglomeration fractions were selectively recombined to create 50 g batches of representative samples for testing. Ore was agglomerated using a ratio of 2 kg acid/ton ore and 5.5% moisture, where 2.1.2.approximately Ore Agglomeration 0.5% comes with the ore [15,16]. This corresponded to an acid water solution prepared at a ratio of 2.6 mL water to 0.1 mL H2SO4 combined with 50 g of ore. The acidified water was added to theOre ore was and agglomerated then agglomerated using a ratio by rotating of 2 kg acid in a/ton bucket ore and drum, 5.5% to moisture, ensure a wherehomogeneous approximately clumpy 0.5%sludge. comes The with agglomerated the ore [15 ,ore16]. was This immediately corresponded packed to an into acid the water experimental solution prepared apparatus. at a ratio of 2.6 mL water to 0.1 mL H2SO4 combined with 50 g of ore. The acidiﬁed water was added to the 2.2. Experimental Setup

Minerals 2020, 10, 746 4 of 27 ore and then agglomerated by rotating in a bucket drum, to ensure a homogeneous clumpy sludge. The agglomerated ore was immediately packed into the experimental apparatus.

2.2.Minerals Experimental 2020, 10, x FOR Setup PEER REVIEW 4 of 28

2.2.1.2.2.1. Mini-LeachingMini-Leaching C Columnsolumns µ Mini-leachingMini-leaching columnscolumns werewere designed designed based based the the X-ray X-ray CTμCT ﬁeld field of of view view (FOV) (FOV) required required to beto ablebe toable accurately to accurately image image the full the chalcopyrite full chalco mineralpyrite grainmineral size grain distribution, size distribution determined, determined using QEMSCAN. using GlassQEMSCAN columns,. Glass with columns, a diameter with of a diameter 20 mm and of 20 a length mm and of 150a length mm, of were 150 constructedmm, were constructed by Glasschem by (Stellenbosch,Glasschem (Stellenbosch, South Africa). South The ends Africa). were The closed ends with were screw-cap closed with lids withscrew a-cap rubber lids stopper with a and rubber glass nipple.stopper Aand peristaltic glass nipple. pump A (Masterﬂex peristaltic pump Console (Masterflex Drive, 7521-57) Console was Drive, connected 7521-57) to was the glassconnected nipple to to allowthe glass the nipple solution to allow to be pumpedthe solution in fromto be thepumped top of in the from column, the top with of the a collectioncolumn, with of liquid a collection out the bottom.of liquid Glass out the wool bottom. and 50 Glass glass wool beads and (4 50 mm glass diameter, beads Lasec)(4 mm werediameter, placed Lasec) at the were top placed and bottom at the of thetop columnand bottom to ensure of the the column uniform to ensure distribution the uniform of liquid distribution in the column. of liquid in the column.

2.2.2.2.2.2. Incubators TwoTwo fourfour andand eighteight mini-columnmini-column incubatorsincubators werewere designeddesigned andand constructed, illustrated in Figure2 . They2. They were were ﬁtted fitted with with a a heater heater and and a afan fan toto circulatecirculate the air for for uniform uniform temperature temperature distribution. distribution. AnAn electronicelectronic controllercontroller was used to set the temperature by by altering altering the the pow powerer to to the the heater. heater. 40 cm

20 cm 50 cm

Figure 2.2. Schematic of of the the 8 8 mini mini-column-column incubator incubator from from the the front, front, side, side, and and top top views. views. 2.3. Solution Chemistry 2.3. Solution Chemistry A Metrohm 827 pH/redox lab meter with a Metrohm 6.0451.100 probe was used to measure the A Metrohm 827 pH / redox lab meter with a Metrohm 6.0451.100 probe was used to measure the redox potential. The pH was monitored using a Metrohm 713 pH meter with a Metrohm 6.0258.000 redox potential. The pH was monitored using a Metrohm 713 pH meter with a Metrohm 6.0258.000 probe. The ferrous and total iron concentrations were determined using the 1–10 phenanthroline probe. The ferrous and total iron concentrations were determined using the 1–10 phenanthroline method [17]. Copper concentrations were analysed using an atomic adsorption spectrophotometer method [17]. Copper concentrations were analysed using an atomic adsorption spectrophotometer (AAS)(AAS) (Varian(Varian SpectraSpectra AAAA 110,110, VarianVarian Inc.,Inc., Palo Alto,Alto, CA,California, USA). USA).

2.4. Flow-Through Leaching Experiments The mini-columns were loaded with 50 g of an ore and operated as a continuous unsaturated flow-through system. The leaching operating conditions, summarised in Table 2, were based on typical, best-practice or optimised operating conditions for each mineral ore type. The loaded mini-columns were washed and conditioned with acidified solution (pH = 1.15, prepared using concentrated H2SO4) prior to the introduction of feed solution. The leaching liquid

Minerals 2020, 10, 746 5 of 27

2.4. Flow-Through Leaching Experiments The mini-columns were loaded with 50 g of an ore and operated as a continuous unsaturated ﬂow-through system. The leaching operating conditions, summarised in Table2, were based on typical, best-practice or optimised operating conditions for each mineral ore type.

Table 2. Operating conditions of the mini-columns and feed solution characteristics.

Ore Type Feed pH Temperature

Malachite Acidiﬁed water 1.20 30 ◦C 3+ Pyrite Fe solution 1.15 37 ◦C 3+ Pyrite Fe solution 1.15 65 ◦C 3+ 2+ Chalcopyrite Fe and Fe solution 1.15 37 ◦C 3+ 2+ Chalcopyrite Fe and Fe solution 1.15 65 ◦C

The loaded mini-columns were washed and conditioned with acidified solution (pH = 1.15, prepared using concentrated H2SO4) prior to the introduction of feed solution. The leaching liquid feed was then pumped into the top of the mini-columns from a single drip emitter point source at a 1 flowrate of 2.55 mL h− for a period of 26 days for malachite and 5.5 months for chalcopyrite and pyrite. An acidified solution with a pH of 1.20 was used during the malachite leaching. Pyrite leaching was 1 3+ conducted using a feed solution with a pH of 1.15 and 8.60 g L− Fe . For the chalcopyrite ore, the feed 1 3+ 1 2+ had a pH of 1.15 and contained 4.30 g L− Fe and 8.33 g L− Fe , equivalent to 440 mV redox potential. Hiroyoshi et al. [18] and Peterson and Dixon [19] reported that chalcopyrite leaches more slowly at high potentials, while the pyrite oxidation rate increases with increasing redox potential. There is a range of critical redox potential from 410 to 490 mV at which chalcopyrite leaching is maximized. The lower redox potential was selected to maximise chalcopyrite leaching while maintaining low pyrite oxidation. Experiments were conducted in incubators at 30 ◦C, 37 ◦C and 65 ◦C. The lower temperature was anticipated to be appropriate for the more readily leachable malachite ore. The two other temperatures correspond to conditions for mesophilic microorganisms (active at 37 ◦C) and thermophilic microorganisms (active at 65 ◦C) which are active in pyrite and chalcopyrite bioleaching.

2.5. X-ray µCT Image Acquisition X-ray scans were performed at X-SIGHT X-RAY Services in Cape Town using a Nikon HMX ST 225, Metris X-Tek, London, UK which permits resolutions of 3–70 µm, depending on the sample size. The mini-columns were imaged in their entirety at the start and end of an experiment. These images of the whole mini-columns were acquired as five separate sections from top (1) to bottom (5), because the division into small parts permitted a smaller FOV and thus a finer image resolution. Each section was individually scanned with X-ray µCT for 50 min at 100 kV and 150 mA using a 0.38 mm copper filter (to reduce the effect of beam hardening and noise caused by low level energy) and at a distance of 59.40 mm between X-ray source and specimen. The scans collected 3000 projections at 0.12 angular increments on a 1900 1500 pixel detector. All the scans were performed at the same × resolution (voxels of approximately 13.40 µm 13.40 µm 13.40 µm). Copper wires were attached to × × the outside of the column for image registration. During the leaching experiments, the mini-columns were removed periodically from the flow to allow the scanning of three regions (top, middle and bottom). This was done at four time points over the 165-day leaching period for pyrite and chalcopyrite and at 1 time point for malachite over the 26-day experimental period. The imaging time points were chosen based on the leaching rates observed in preliminary leaching experiments. The advanced 3D analysis software Avizo® 9 (Thermo Fisher Scientific, Waltham, MA, USA) and ImageJ-Fiji (University of Wisconsin, Madison, WI, USA) [20] were used to visualize and analyse the image data. Minerals 2020, 10, 746 6 of 27

3. Image Processing Design

3.1. Mineral Grain Segmentation Figure3 shows the example side and top views and a volume-rendered 3D view of a packed Mineralsmini-column 2020, 10, reconstructedx FOR PEER REVIEW data set. The metal oxide/sulphide mineral grains are represented6 byof 28 the brighter voxels, as they have high X-ray attenuation, attributed to their relatively high densities and atomic numbers. By By tracking tracking these these voxels voxels and and converting converting this this to to the the volume volume of of target target mineral mineral present present at a given point in time, the X-ray images can be used as a measure of leaching extent. at a given point in time, the X-ray images can be used as a measure of leaching extent.

(a) 24 mm (b) 24 mm

Figure 3.3. ExampleExample X-rayX-ray micro-computed micro-computed tomography tomography (µ CT)(μCT) side side and and top views top views and a andvolume-rendered a volume- rendered3D view of3D aview mini-column of a mini- packedcolumn withpacked the with low-grade the low- chalcopyritegrade chalcopyrite ore. ( aore.) side (a) viewside view in X in and X Z anddirection; Z direction (b)side; (b view)side inview Y and in Y Z and direction; Z direction; (c) top (c view;) top view; (d) 3D (d volume.) 3D volume. Segmentation involves assigning labels to image voxels to identify and separate objects in a 3D Segmentation involves assigning labels to image voxels to identify and separate objects in a 3D image. It is one of the most critical steps in the process of reducing images to more useful information. image. It is one of the most critical steps in the process of reducing images to more useful information. In mineral processing, segmentation allows the different minerals to be distinguished and for solid In mineral processing, segmentation allows the different minerals to be distinguished and for solid ore to be distinguished from any gaseous and/or liquid phases present. Additional information from ore to be distinguished from any gaseous and/or liquid phases present. Additional information from other techniques including QEMSCAN, X-rayX-ray fluorescencefluorescence (XRF)(XRF) and SEM–EDSSEM–EDS areare oftenoften requiredrequired to µ tosegment segment between between diff differenterent mineral mineral phases phases in a X-rayin a X-CTray datasetμCT dataset effectively effectively [21]. Furthermore, [21]. Furthermore, accurate accurateand quantitative and quantitative processing processing requires segmentation requires segmentation which clearly which identifies clearly theidentifies mineral the boundaries. mineral boundaries.Correct or unique Correct thresholds or unique cannot thresholds be determined cannot be easily determine or accuratelyd easily ifor the accurately edges are if blurred the edges by noiseare blurredor partial by volume noise oreff ects. partial Global volume and effects. local thresholding Global and techniques local thresholding and feature-based techniques classification and feature are- basedused to classification overcome this. are used to overcome this. The suitability of different segmentation options for the thresholding of the metal oxide/sulphide mineral grains were evaluated by comparing the X-ray results to an equivalent QEMSCAN field image. Examples of the resulting 2D slices are presented in Figure 4. Table 3 gives a measure of the accuracy of the different methods by comparing the total target mineral area (and equivalent number of voxels) to the QEMSCAN field image.

Minerals 2020, 10, 746 7 of 27

The suitability of different segmentation options for the thresholding of the metal oxide/sulphide mineral grains were evaluated by comparing the X-ray results to an equivalent QEMSCAN field image. Examples of the resulting 2D slices are presented in Figure4. Table3 gives a measure of the accuracy of the different methods by comparing the total target mineral area (and equivalent number of voxels) to the QEMSCAN field image. The 3D watershed segmentation process is a local thresholding algorithm commonly used for multiphase mineral particles. It is appropriate for mineral grains with a scale parameter greater than 30 (mineral grain size/voxel size) and a density lower than 4000 kg/m3 [22]. The watershed segmentation’s strong gradient sensitivity leads to the over-segmentation of bright mineral grains, while it cannot pick small mineral grains [22,23]. Based on the resolution of the X-ray image (13.4 µm), the mineral grain size should be higher than 400 µm to accurately segment using watershed segmentation. However, in the chalcopyrite ore, more than 60% of pyrite and 90% of chalcopyrite grains are smaller than 400 µm, as is typical for low-grade sulphide ores. Furthermore, the sulphide mineral’s density is larger than 4000 kg/m3. Thus, the watershed segmentation method was not satisfactory to obtain accurate mineralogical data for the ores in this study. Trainable Weka segmentation (TWS) or feature-based segmentation [24] combines a collection of machine learning algorithms with a set of selected image features to produce pixel-based segmentations. It has been suggested for the segmentation of fine or high density/high atomic number mineral grains [22] and can be used to correct partial volume effects in images. A good agreement between the TWS result (Figure4d) and the QEMSCAN image was achieved (error of 2.62%). However, the TWS method is very computing memory intensive and hence time consuming for the quantitative evaluation of a large image dataset and requires high-speed computing. Lin et al. [23] used algorithms based on the measurement of the maximum entropy of the sulphide mineral grain phase segmentation. The Maximum Entropy algorithm is similar to the Otsu Thresholding technique. However, rather than maximizing the inter-class variance, the inter-class entropy is maximized [25]. The accuracy of this method depends on the ore mineralogy. When applied, this method led to a number of gangue minerals with high intensity being identified as a sulphide mineral as well as causing over-segmentation (Figure4e) and a high error of 21.32% resulted. The Avizo® 9 Interactive Thresholding function is based on intensity range partitioning. When tested for the segmentation of the sulphide and high dense/atomic number mineral grains (Figure4f), it resulted in accurate mineral grain phase segmentation (error of 3.3%) in comparison with the QEMSCAN results (Figure4b). It was additionally less computing memory intensive and hence faster than local thresholding methods and TWS. It was thus found to be the best segmentation method for this study and is supported by its low error reported in Table3. This method was able to segment malachite and bornite from the gangue minerals in the malachite ore, chalcopyrite and pyrite from gangue minerals in the chalcopyrite ore, and pyrite from the gangue minerals in the waste rock. The labelling of each sulphide mineral grain was done after segmentation to extract the statistical and numerical information, allowing the progression of leaching to be followed. Figure5 shows 2D and 3D views of the segmented and labelled images. The segmentation of different sulphide minerals from the X-ray µCT images was not possible because their grey level values were too similar. Therefore, the total sulphide or oxide mineral volume reduction was considered in order to investigate copper and iron leaching and the results were compared with the copper and iron leaching data obtained using conventional techniques. Minerals 2020, 10, 746 8 of 27 Minerals 2020, 10, x FOR PEER REVIEW 8 of 28

K-feldspar (a) Quartz (b) Muscovite Pyrite Chalcopyrite

30 mm

(e) (f)

Figure 4. Comparison of the different segmentation methods to threshold target mineral grains. A (a) referenceFigure quantitative 4. Comparison evaluation of the different of minerals segmentation by scanning methods electron to threshold microscopy target mineral (QEMSCAN) grains. A image (a) reference quantitative evaluation of minerals by scanning electron microscopy (QEMSCAN) image is is used to (b) identify the target mineral grains identified. This was used as a comparison for the (c) used to (b) identify the target mineral grains identified. This was used as a comparison for the (c) original X-ray µCT image after having been segmented using (d) trainable Weka segmentation (TWS), original X-ray μCT image after having been segmented using (d) trainable Weka segmentation (TWS), (e) Max Entropy and (f) Interactive Thresholding modules. (e) Max Entropy and (f) Interactive Thresholding modules. Table 3. The total target mineral area, number of voxels and error compared to the QEMSCAN field imageTable calculated 3. The total for thetarget diff mineralerent thresholding area, number techniques. of voxels and error compared to the QEMSCAN field image calculated for the different thresholding techniques. Thresholding Technique Area (µm2) Number of Pixels Error (%) Thresholding Technique Area (µm2) Number of Pixels Error (%) QEMSCANQEMSCAN 10,490,42410,490,424 49895 49895 - - Weka segmentationWeka segmentation 10,764,53410,764,534 38,598 38,598 2.62 2.62 Max Entropy 12,727,447 45,636 21.32 Max Entropy 12,727,447 45,636 21.32 Interactive Thresholding 10,839,488 38,867 3.30 Interactive Thresholding 10,839,488 38,867 3.30

Minerals 2020, 10, 746 9 of 27 Minerals 2020, 10, x FOR PEER REVIEW 9 of 28

20 mm 20 mm 20 mm

(a) (b) (c) 20 mm 20 mm

(d) (e)

Figure 5. The 2D (a–c) and 3D (d–e) views of the segmented and labelled images of mineral grains. TheFigure (a) original 5. The 2D X-ray (a–c grey) and level 3D image(d–e) views has the ofmineral the segmented grains segmented and labelled in (imagesb) and (ofd ).mineral Images grains. (c) and (eThe) demonstrate (a) original theX-ray labelling grey level of individual image has mineral the mineral grains. grains segmented in (b) and (d). Images (c) and (e) demonstrate the labelling of individual mineral grains. 3.2. Mineral Grain Distance Mapping 3.2. AMineral mineral Grain grain Distance distance Mapping map analysis which quantiﬁes the distance of the mineral grains from the oreA particlemineral surfacegrain distance was developed map analysis as a which tool to quantifies understand the thedistance positional of the dependencemineral grains of from leach performance.the ore particle The surface procedure was isdeveloped shown in as Figure a tool6. to understand the positional dependence of leach performance.The Interactive The procedure Thresholding is shown module in Figure was applied 6. to create a binary image with the packed ore as the foregroundThe Interactive and air Thresholding as the background module (Figure was applied6c). The to distancecreate a binary map algorithm image with on the a binary packed image ore givesas the a greyforeground level image and air where as the each background voxel intensity (Figure represents 6c). The thedistance minimum map distancealgorithm in on voxels a binary from theimage object gives boundary. a grey level Low-level image where intensity each meant voxel intensity that the voxelrepresent wass closethe minimum to the object distance surface in voxels while high-levelfrom the intensityobject boundary. meant that Low part-level ofthe intensity object wasmeant far that from the the voxel object was surface. closeThe to the Chamfer object Distancesurface Mapwhile module high-level was appliedintensity to meant the thresholded that part of binary the object image was (Figure far from6c) tothe create object the surface. distance The map Chamfer image. AnotherDistance Interactive Map module Thresholding was applied module to the thresholded was used tobinary separate image the (Figure metal 6 oxidec) to /createsulphide the distance minerals frommap theimage. gangue Another minerals Interactive and air Thresholding (Figure6e). The module distance was mapused imageto separate was maskedthe metal with oxide/ thissulphide second thresholdedminerals from image the (Figuregangue6 mineralse). This gaveand air a grey (Figure image 6e). where The distance each non-null map image intensity was representedmasked with a voxelthis second of the metalthresholded oxide/sulphide image (Figure mineral 6e grains). This andgave the a intensitygrey image value where was each equal non to- thenull distance intensity in voxelsrepresented from the a voxel ore surface of the (Figuremetal oxide/6f). Thesulphide mineral mineral grain distancegrains and from the the intensity ore surface value was was calculated equal to usingthe distance the “Multiply in voxels By from Value” themodule ore surface on the(Fig maskedure 6f). The image. mineral The accuracygrain distance of the from distance the ore values surface was awasﬀected calculated by the position using the of “Multiply the mineral By grain Value” edges module relative on tothe the masked voxel boundaries.image. The accuracy An uncertainty of the intervaldistance of values three times was the affected voxel by size the resulted position ( 13.4 of the3 = mineral40.2 µ grainm). edges relative to the voxel ± × ± boundaries.The generated An uncertainty maps were interval used toof extractthree times a descriptor the voxel for size the resulted leaching (±13.4 solution × 3 = penetration ±40.2 μm). from the oreThe surface generated into the maps particles were used to leach to extract the target a descriptor mineral grains.for the leaching The maximum solution linear penetration distance from from thethe nearest ore surface ore surfaceinto the (interfaceparticles to with leach air the/solution) target mineral at which grains. a change The maximum in mineral linear grain distance content from was measuredthe nearest is ore termed surface the leaching(interface penetration with air/solution) distance. at which This descriptor a change canin mineral be tracked grain with content time. was measuredThe separation is termed ofthe ore leaching particles penetration was not distance. included This as part descriptor of the analysis.can be tracked Thus, with agglomerated time. particlesThe were separation considered of ore as parti a singlecles was solid not phase, included should as part no clear of the interface analysis. with Thus, air agglomerated or solution be evidentparticles between were considered the particles. as a single solid phase, should no clear interface with air or solution be evident between the particles.

Minerals 2020, 10, 746 10 of 27 Minerals 2020, 10, x FOR PEER REVIEW 10 of 28

20 mm

FigureFigure6. 6. ProcedureProcedure forfor thethe calculationcalculation of mineral grain distance from from the the ore ore surface. surface. The The (a (a) )original original imageimage has has ( (bb)) thethe columncolumn wallwall removed.removed. The ( (c)) solid solid ore ore was was thresholded thresholded from from the the background background and and thethe ( d(d)) distance distance ofof eacheach voxelvoxel fromfrom thethe oreore surfacesurface waswas found. The The ( (ee)) metal metal oxide/ oxide/sulphidesulphide miner mineralal grainsgrains were were thresholded thresholded from from ( b(b),) and, and mapped mapped onto onto ( d(d),) to, to produce produce (f (),f) which, which gave gave the the distance distance map map of theof the target target mineral mineral from from the the ore ore surface. surface. 4. Results and Discussion 4. Results and Discussion 4.1. Ore Structure Characterisation 4.1. Ore Structure Characterisation The number of pores with a dimension of 40 µm or greater (defined by resolution of 13.4 µm) The number of pores with a dimension of 40 μm or greater (defined by resolution of 13.4 μm) present in the agglomerated pyrite, chalcopyrite and malachite ores are plotted as a function of distance present in the agglomerated pyrite, chalcopyrite and malachite ores are plotted as a function of from the agglomerate particle surface in Figure7. The average porosities were 1.06% for the malachite distance from the agglomerate particle surface in Figure 7. The average porosities were 1.06% for the ore, 0.066% for the pyrite ore, and 0.43% for the chalcopyrite ore. malachite ore, 0.066% for the pyrite ore, and 0.43% for the chalcopyrite ore. In the case of the malachite agglomerates, a good porosity was maintained even beyond 3000 µm In the case of the malachite agglomerates, a good porosity was maintained even beyond 3000 from the ore surface. This confirmed that the ore itself was porous in addition to high-porosity μm from the ore surface. This confirmed that the ore itself was porous in addition to high-porosity agglomerate rims having formed. The maximum porosity was observed 750 µm from the ore surface. agglomerate rims having formed. The maximum porosity was observed± ±750 μm from the ore The pyrite agglomerates had the lowest porosity, with the maximum occurring at 500 µm from surface. ± the ore surface. A very low porosity was recorded beyond 1500 µm from the surface. The low The pyrite agglomerates had the lowest porosity, with the ±maximum occurring at ± 500 μm from porosity of these agglomerates could be because pyrite is hydrophobic at pH values lower than 4 [26]. the ore surface. A very low porosity was recorded beyond ±1500 μm from the surface. The low This would have caused the decreased adsorption of acidified solution onto the ore and consequently porosity of these agglomerates could be because pyrite is hydrophobic at pH values lower than 4 [26]. aThisffected would the have formation caused of the bridges decreased and adsorption porous structures of acidified between solution the onto fine the particles ore and asconsequently well as fine particlesaffected aroundthe formation large particles. of bridges and porous structures between the fine particles as well as fine particlesThe totalaround porosity large particles. of the agglomerated chalcopyrite ore was less than half that of the malachite, however,The ittotal was porosity an order of of the magnitude agglomerated larger chalcopyrit than the pyrite.e ore was The less maximum than half distribution that of the ofmalachite, the pores was 500 µm from the ore surface. The porosity decreased with increasing distance until 2000 µm, however,± it was an order of magnitude larger than the pyrite. The maximum distribution of ±the pores beyondwas ±500 which μm thefrom pores the ore were surface. negligible. The porosity Images ofdecreased non-agglomerated with increasing chalcopyrite distance yielded until ±2000 an average μm, porositybeyond of whi 0.0094%,ch the pores confirming were thatnegligible the ore. Images itself had of anon very-agglomerated low porosity. chalcopyrite Therefore, theyielded porosity an average porosity of 0.0094%, confirming that the ore itself had a very low porosity. Therefore, the

MineralsMinerals2020 2020,,10 10,, 746 x FOR PEER REVIEW 1111of of 2728

porosity seen in the agglomerated ore resulted from the pores formed between the particles in the seen in the agglomerated ore resulted from the pores formed between the particles in the aggregate, aggregate, consistent with the porous region location. consistent with the porous region location. The substantial differences in the pore availability and distribution for the three different ores The substantial diﬀerences in the pore availability and distribution for the three diﬀerent ores supported the choice of ores for the investigation of particle structure and mineralogy on potential supported the choice of ores for the investigation of particle structure and mineralogy on potential lixiviant contact. lixiviant contact.

1.8E+7 1.6E+7 1.4E+7 Malachite 1.2E+7 Chalcopyrite 1.0E+7 Pyrite 8.0E+6 6.0E+6

Nmuber of pore voxels pore of Nmuber 4.0E+6 2.0E+6 0.0E+0 0 1000 2000 3000 4000 Distance from ore surface (µm)

Figure 7. Comparison of the pore distribution of the three ores at a different distance to the surface Figure 7. Comparison of the pore distribution of the three ores at a different distance to the surface values. The uncertainty in the pore distance from the ore surface is 40.2 µm. values. The uncertainty in the pore distance from the ore surface is± ±40.2 μm. 4.2. Leaching Results 4.2. Leaching Results 4.2.1. Malachite 4.2.1. Malachite Copper oxide minerals such as malachite contain copper in the divalent state. These are completely solubleCopper in sulphuric oxide acid minerals at room such temperature. as malachite The contain typical reactioncopper in of malachitethe divalent with state. sulphuric These acid are iscompletely [27]: soluble in sulphuric acid at room temperature. The typical reaction of malachite with sulphuric acid is [27]: Cu (OH) CO + 2H SO 2CuSO + CO + 3H O, (1) 2 2 3 2 4 → 4 2 2 The effect of leaching timeCu on2(OH) the dissolution2CO3 + 2H2SO of4 malachite → 2CuSO at4 + 30 CO◦C2 + is 3H shown2O, in Figure8. The copper(1) leached quickly, with 50% copper recovery achieved by day 6. There was a corresponding rapid The effect of leaching± time on the dissolution of malachite at 30 °C is shown in Figure 8. The decreasecopper leached in pH fromquickly, circa with 4 to ±50% 1.84 copper during recovery first 6 days, achieved after by which day the6. There pH gradually was a corresponding fell to 1.22. Therapid recovery decrease increased in pH from to 87% circa after 4 to 26 1.84 days. during first 6 days, after which the pH gradually fell to 1.22. The Therecovery malachite increased ore contained to 87% after 2.44% 26 bornite,days. accounting for some 18% of the copper present in the ore. TheThe leaching malachite rate ore of bornitecontained using 2.44% acidified bornite solution, accounting is slow for [28 ].some The 18% leach of curve the copper in Figure present8 shows in thethe rapidore. The leaching leaching of somerate of 70–80% bornite of using the copper acidified over solution a 9 day is period, slow [28] followed. The leach by consistent curve in Figure slower 8 leachingshows the to rapid recover leaching>85% of thesome copper 70–80% over of 26the days. copper The over slower a 9 day leaching period, and followed hence the by flatteningconsistent ofslower the copper leaching recovery to recover curve >85% towards of the the copper end of theover leaching 26 days. period The slower couldthus leaching be attributed and hence to thethe leachingflattening of bornite,of the copper assuming recovery a small curve fraction towards of both minerals the end remain of the unliberated. leaching period The intensity could thus of the be X-rayattributedµCT signalto the didleaching not allow of bornite ready, assuming differentiation a small between fraction these of both minerals. minerals remain unliberated. The intensity of the X-ray μCT signal did not allow ready differentiation between these minerals.

Minerals 2020, 10, 746 12 of 27 Minerals 2020, 10, x FOR PEER REVIEW 12 of 28

100 100 90 90 80 80 70 70 60 60 ray μCT (%) ray - 50 50 Exposed to X-ray 40 40 Non-exposed to X-ray 30 30 X-ray CT data

20 20 X by measured

10 10 leached sulphidemineral and Oxide Copper recovery measured by by (%) AAS measured recovery Copper 0 0 0 5 10 15 20 25 30 Time (days)

Figure 8. Comparison of the copper recovery measured by atomic adsorption spectrophotometer (AAS) Figure(solid 8 and. Comparison dashed lines) of andthe copper the oxide recovery and sulphide measured mineral by atomic leached adsorption based on imagespectrophotometer measurement (AAS)(green (solid columns) and for dash theed malachite lines) and ore. the oxide and sulphide mineral leached based on image measurement (green columns) for the malachite ore. The oxide and sulphide recovery measured using the X-ray µCT images was consistent with the copperThe recoveryoxide and measured sulphide byrecovery AAS, though measured about using 3% the to 4% X-ray lower μCT than images the bulk was measurementconsistent with results. the copperThe 3D recovery images ofmeasured the copper by mineralAAS, though grains about (Figure 3%9) to make 4% lower it evident than that the bulk the remaining measurement copper results. in the Theresidue 3D images ore was of mostlythe copper from mineral large mineral grains grains.(Figure 9) make it evident that the remaining copper in the residueThe distributions ore was mostly of the from copper large mineral mineral distance grains. from the ore particle surface at the different time points are shown in Figure 10. In Sections2–5, the copper mineral grains were positioned less than 2000 µm from the surface. The existence of large mineral grains in the top most section (evident in Figure9) was responsible for the overall larger maximum distance from the ore surface. The maximum distance decreased to approximately 1800 µm over the experimental period. This meant that the deeper minerals had been leached, or that the large mineral grains became smaller as leaching progressed. Figure 11 confirms that the distance from the ore particle surface did not influence the rate of copper recovery, except initially at the farthest distance, which was attributed to the large grains in Section1. Therefore, ensuring contact between the mineral grains and leaching solution, even at increased distance from the surface, did not constrain leaching for this ore in accordance with the high measured porosity values. The dissolution of malachite was thus controlled by chemical reaction rather than diffusion. Another study by Nicol [27] also showed that the kinetics of malachite dissolution were governed by the rate-determining surface chemical reaction.

MineralsMinerals 20202020, ,1010, ,x 746 FOR PEER REVIEW 1313 of of 28 27

Day 0 Day 6 Day 26

Top

(1)

(2)

(3)

(4)

(5)

Bottom

FigureFigure 9. 9. TheThe 3D 3D views views of the of themalachite malachite copper copper mineral mineral grain grain volumes volumes in the in5 sections the 5 sections of the mini of the- columnmini-column (from top (from to topbottom) to bottom) on days on 0, days 6, and 0, 6,26. and 26.

The distributions of the copper mineral distance from the ore particle surface at the different time points are shown in Figure 10. In Sections 2–5, the copper mineral grains were positioned less than 2000 μm from the surface. The existence of large mineral grains in the top most section (evident in Figure 9) was responsible for the overall larger maximum distance from the ore surface. The maximum distance decreased to approximately 1800 μm over the experimental period. This meant that the deeper minerals had been leached, or that the large mineral grains became smaller as leaching progressed. Figure 11 confirms that the distance from the ore particle surface did not influence the

Minerals 2020, 10, x FOR PEER REVIEW 14 of 28 rateMinerals of copper 2020, 10 , recoveryx FOR PEER, except REVIEW initially at the farthest distance, which was attributed to the 14large of 28 grains in Section 1. rate of copper recovery, except initially at the farthest distance, which was attributed to the large Therefore, ensuring contact between the mineral grains and leaching solution, even at increased grains in Section 1. distance from the surface, did not constrain leaching for this ore in accordance with the high Therefore, ensuring contact between the mineral grains and leaching solution, even at increased measured porosity values. The dissolution of malachite was thus controlled by chemical reaction distance from the surface, did not constrain leaching for this ore in accordance with the high rather than diffusion. Another study by Nicol [27] also showed that the kinetics of malachite measured porosity values. The dissolution of malachite was thus controlled by chemical reaction dissolution were governed by the rate-determining surface chemical reaction. rather than diffusion. Another study by Nicol [27] also showed that the kinetics of malachite Minerals 2020, 10, 746 14 of 27 dissolution were governed by the rate-determining surface chemical reaction. 2.5E+7 2.5E+7 2.0E+7 Day 0 2.0E+7 DayDay 6 0 1.5E+7 DayDay 26 6 1.5E+7 Day 26 1.0E+7 1.0E+7 5.0E+6

Number of copper minerals (voxels) minerals copperofNumber 5.0E+6

Number of copper minerals (voxels) minerals copperofNumber 0.0E+0 0.0E+0 0 1000 2000 3000 4000 5000 6000 0 1000 Distance2000 from3000 ore surface4000 (µm) 5000 6000 Distance from ore surface (µm) Figure 10. Change in the distance of mineral grains from the edge of the ore particle as a function of Figure 10. Change in the distance of mineral grains from the edge of the ore particle as a function of time for the malachite ore. The uncertainty in the grain distance from the ore surface is ±40.2 μm. timeFigure for 10 the. Change malachite in the ore. distance The uncertainty of mineral in thegrains grain from distance the edge from of thethe oreore surfaceparticle is as 40.2a functionµm. of ± time for the malachite ore. The uncertainty in the grain distance from the ore surface is ±40.2 μm. 100 10090 8090 7080 6070 5060 4050 3040 Day 6 2030 DayDay 26 6 1020

Oxide and sulphide mineral leached (%) leached mineral sulphideand Oxide Day 26 100 Oxide and sulphide mineral leached (%) leached mineral sulphideand Oxide 0 0 500 1000 1500 2000 2500 3000 0 500 Distance1000 from1500 ore surface2000 (µm) 2500 3000

Figure 11. The oxide and sulphide mineralDistance leached from at ore diﬀ erentsurface distances (µm) against the average initial mineral grain size on days 6 and 26.

4.2.2. Pyrite Changes in pH, redox potential, ferrous ion (Fe2+), and ferric ion (Fe3+) concentrations of the eﬄuent solution of the pyrite agglomerate mini-columns over the leaching period are shown in Figure 12. There was acid consumption by some gangue minerals such as calcite and limonite during the acid wash (pH = 1.15) over the ﬁrst 7 days. The pH decreased from 2.04 to 1.71 for the 37 ◦C Minerals 2020, 10, x FOR PEER REVIEW 15 of 28

Figure 11. The oxide and sulphide mineral leached at different distances against the average initial mineral grain size on days 6 and 26.

4.2.2. Pyrite

Changes in pH, redox potential, ferrous ion (Fe2+), and ferric ion (Fe3+) concentrations of the effluent solution of the pyrite agglomerate mini-columns over the leaching period are shown in Figure 12. MineralsThere2020 ,was10, 746 acid consumption by some gangue minerals such as calcite and limonite during15 ofthe 27 acid wash (pH = 1.15) over the first 7 days. The pH decreased from 2.04 to 1.71 for the 37 °C mini- column and from 2.75 to 1.88 for the 65 °C mini-column. Further decrease in pH to 1.1 for the 37 °C mini-column and from 2.75 to 1.88 for the 65 ◦C mini-column. Further decrease in pH to 1.1 for the mini-column and 1 for the 65 °C mini-column occurred subsequently to the introduction of the feed 37 ◦C mini-column and 1 for the 65 ◦C mini-column occurred subsequently to the introduction of the solution containing 8.6 g L−1 ferric1 ion at a pH of 1.15. Equation (2) shows that this decrease may be feed solution containing 8.6 g L− ferric ion at a pH of 1.15. Equation (2) shows that this decrease may accountedbe accounted for forby bythe the ferric ferric leaching leaching of ofpyrite pyrite which which produces produces a ahydrogen hydrogen ion ion and and so so reduces reduces the the pH pH of the solution [29] [29]:: 3+ 2+ + 2 FeS2FeS+ 14Fe2 + 14Fe+3+8H + 8H2O2O →15Fe 15Fe2++ + 16H16H+ + 2SO2SO442−,− ,( (2)2) → The solution redoxredox potential potential was was approximately approximately 330 330 and and 300 300 mV mV during during the acidthe acid wash wash for the for 37 the◦C 37and °C 65 and◦C mini-columns, 65 °C mini-columns respectively., respectively. Reduction Reduction in the pyrite in oxidation the pyrite rate oxidation over the rate experimental over the experimentalperiod results period in an upwardresults in gradual an upward trend gradual of the redox trend potential.of the redox The potential redox potential. The redox for thepotential 65 ◦C formini-column the 65 °C increased mini-column rapidly increased between rapidly days 7 between and 15. Theredays 7 was and then 15. a There gradual was increase then a until gradual the increaseend of the until experiment the end of at the which experiment time the at highest which recorded time the redoxhighest potential recorded of redox 464 mV potential was recorded. of 464 mVThe increase was recorded. in redox The potential increase in the in PLSredox corresponded potential in to the a decreased PLS corresponded Fe2+ concentration to a decreased in a solution Fe2+ concentrationcoupled with anin increasea solution in coupled the Fe3+ withconcentration, an increase shown in the in Fe Figure3+ concentration, 12c,d. This meantshown thatin Figure the pyrite 12c andoxidation d. This rate meant decreased that the over pyrite the oxidation experimental rate period.decreased In addition,over the experimental the results showed period. that In theaddition, redox thevalues results at 65 showed◦C were that lower the thanredox at values 37 ◦C, at indicating 65 °C were that lower increasing than at temperature 37 °C, indicating increased that pyrite increasi ferricng temperatureoxidation, producing increased more pyrite Fe ferric2+ in theoxidation, system. producing more Fe2+ in the system.

(a) (b)

1 Figure 12. Changes in the eﬄuent (a) pH, (b) redox potential (mV), (c) ferrous ion (g L− ) and (d) ferric

ion concentration (g L 1) for pyrite leaching at 37 C( ) and 65 C(N). − ◦ • ◦ Iron recovery for the diﬀerent temperature conditions is given as a function of time in Figure 13, based on the spectroscopy data as well as the overall percentage sulphide mineral leached calculated through the measurement of the mineral volume in the X-ray µCT images. Increasing the temperature accelerated the pyrite dissolution rate, consistent with thermodynamics [30]. Ahonen and Tuovinen [31] reported a strong temperature dependence for pyrite dissolution, showing a leaching rate enhancement Minerals 2020, 10, x FOR PEER REVIEW 16 of 28

Figure 12. Changes in the effluent (a) pH, (b) redox potential (mV), (c) ferrous ion (g L−1) and (d) ferric ion concentration (g L−1) for pyrite leaching at 37 °C (●) and 65 °C (▲).

Iron recovery for the different temperature conditions is given as a function of time in Figure 13, based on the spectroscopy data as well as the overall percentage sulphide mineral leached calculated through the measurement of the mineral volume in the X-ray μCT images. Increasing the temperature accelerated the pyrite dissolution rate, consistent with thermodynamics [30]. Ahonen and Tuovinen [31] reported a strong temperature dependence for pyrite dissolution, showing a leaching rate enhancement from 0.11% day−1 to 4.54% day−1 when the temperature rose from 4 °C to 37 °C. Moreover, Dew et al. [32] and Nemati and Harrison [33] reported an increase in the pyrite dissolution with temperature increasing in the 37–65 °C range. Minerals 2020, 10, 746 16 of 27 Rapid mineral dissolution occurred over the first 20 days. After this time, the dissolution rate decreased until the end of the experiment at both temperatures. The maximum recovery was 32% at 1 1 37from °C and 0.11% 66% day at− 65to °C 4.54% based day on− thewhen chemistry the temperature data. The rose recovery from 4 was◦C to 33% 37 ◦ C.at Moreover,37 °C and 68% Dew at et 65 al. [°32C ] accordingand Nemati to and image Harrison quantification [33] reported data. an increase Thus, the in the calculated pyrite dissolution percentage with iron temperature released increasing showed consistencyin the 37–65 between◦C range. the two quantification methods.

70 70 37 °C, Spectroscopy data 65 °C, Spectroscopy data

60 60 µCT ray -

37 °C, X-ray µCT data X

50 65 °C, X-ray µCT data 50

40 40 (%) 30 30

20 20

10 10 Iron recovery measured by spectroscopy (%) spectroscopy by measured recovery Iron

0 0 by measured leached mineral Sulphide 0 20 40 60 80 100 120 140 Time (days)

Figure 13. Comparison of iron recovery measured by spectroscopy (solid lines) and sulphide mineral Figureleached 13. based Comparison on image of measurementiron recovery (dashedmeasured lines) by spectroscopy for the pyrite (solid containing lines) and waste sulphide rock. mineral leached based on image measurement (dashed lines) for the pyrite containing waste rock. Rapid mineral dissolution occurred over the first 20 days. After this time, the dissolution rate decreasedThe distribution until the endof the of thesulphide experiment mineral at grains both temperatures. as a function of The distance maximum from recovery the ore wasparticle 32% surfaceat 37 ◦ Cat and37 °C 66% on atdays 65 ◦0C and based 132 on(at thewhich chemistry point no data. further The changes recovery were was observable) 33% at 37 ◦ Cand and at 68%65 °C at on65 days◦C according 0 and 159 to are image given quantification in Figure 14. The data. maximum Thus, the leaching calculated penetration percentage distance iron released was 2700 showed μm forconsistency both temperature between the conditions. two quantification Thus, an methods.increase in temperature did not affect the maximum penetrationThe distribution distance. of the sulphide mineral grains as a function of distance from the ore particle surfaceThe atsum 37 of◦C three on days mineral 0 and grain 132 volumes (at which in point the tracked no further sections changes at different were observable) time points and are shown at 65 ◦C inon Figure days 015 and and 159 Figure are given 16. The in Figureplots demonstrate 14. The maximum that the leaching leaching penetration progressed distance deeper wasinto 2700the oreµm particlesfor both over temperature time. At 37 conditions. °C, mineral Thus, leaching an had increase progressed in temperature to a depth did of ±0.75 not a mmffect by the day maximum 11 and topenetration ±1.5 mm by distance. day 45. However, in the 65 °C mini-column, the mineral was leached at the distance of The sum of three mineral grain volumes in the tracked sections at different time points are shown in Figures 15 and 16. The plots demonstrate that the leaching progressed deeper into the ore particles over time. At 37 C, mineral leaching had progressed to a depth of 0.75 mm by day 11 and to 1.5 mm ◦ ± ± by day 45. However, in the 65 C mini-column, the mineral was leached at the distance of 1.5 mm ◦ ± from the ore edge by 11 days, with mineral recovery extending to a penetration of 2.4 mm by day 45. ± The maximum leaching penetration was achieved by day 79 for both temperature conditions. The percentage of iron recovery as a function of the distance from ore edge was plotted in Figure 17. The recovery at 37 ◦C remained between 29 and 34% at all distances less than the maximum penetration distance. However, at 65 ◦C the iron recovery was 83% at 200 µm and 32% at 2600 µm from the ore surface, with the recovery showing a steady trend at distances between these. Minerals 2020, 10, x FOR PEER REVIEW 17 of 28

±1.5 mm from the ore edge by 11 days, with mineral recovery extending to a penetration of ±2.4 mm by day 45. The maximum leaching penetration was achieved by day 79 for both temperature conditions. The percentage of iron recovery as a function of the distance from ore edge was plotted in Figure 17. The recovery at 37 °C remained between 29 and 34% at all distances less than the maximum Minerals 2020 10 penetration ,distance., 746 However, at 65 °C the iron recovery was 83% at 200 μm and 32% at 260017 μm of 27 from the ore surface, with the recovery showing a steady trend at distances between these. ThereThere are are two kinetic kinetic regimes regimes which which can can control control the leaching the leaching process, process, namely namely the chemical the chemical reaction reactionor diffusion or diffusion of reagents of throughreagents thethrough ore matrix the ore and matrix reaction and products. reaction The products. regime is The dependent regime ison dependentfactors including on factors operating including conditions, operating ore conditions, type and size ore [type34,35 and]. The size chemical [34,35]. reactionsThe chemical are primarily reactions a arefunction primarily of temperature a function of and temperature are influenced and by are the influenced activation by energy, the activation concentration energy, of reactants,concentration and sizeof reactants,of mineral. and The size waste of mineral. rock used The in waste the current rock used study in hadthe current about 30% study disseminated had about 30% pyrite. disseminated This meant pyrite.that the This inaccessibility meant that ofthe mineral inaccessibility grains should of mineral not have grains been should initially not rate-limiting have been with initially the rate rate of- limitingreaction with being the controlling rate of reaction at the being early controlling stage of the at leachingthe early process.stage of the However, leaching the process. leaching How kineticsever, theare leaching expected kinetics to shift to are a combination expected to of shift reaction–di to a combinationffusion rate of limitation reaction– followingdiffusion therate depletion limitation of followingaccessible the mineral depletion grains. of Di accessibleffusion of the mineral lixiviant grains. into the Diffusion deeper subsurface of the lixiviant zones intothen thebecomes deeper the subsurfacedominant kineticzones then factor becomes in theleaching the dominant process. kinetic factor in the leaching process. The leaching from the mini-column operated at 37 °C was mainly reaction limited as the iron The leaching from the mini-column operated at 37 ◦C was mainly reaction limited as the iron recoveryrecovery wa wass the the same same for for the the entire entire range range of of distance distance values. values. Increasing Increasing temperature temperature did did increase increase thethe rate rate of of leaching, leaching, as as demonstrated demonstrated in in Figure Figure 1313. . However, However, the the higher higher leaching leaching rate rate at at the the ore ore particleparticle surface surface compared compared to to that that at at larger larger distances distances from from the the ore ore surface surface indicates indicates that that leaching leaching at at thethe higher higher temperature temperature became became limited limited by by access access to to the the lixiviant. lixiviant. This This points points to to either either a apartially partially diffusiondiffusion-controlled-controlled system system or or a abias bias due due to to more more completely completely occluded occluded (inaccess (inaccessible)ible) pyrite pyrite mineral mineral grainsgrains existing existing further further from thethe oreore particle particle surface. surface. This This conclusion conclusion is supportedis supported by theby the rapid rapid and and slow slowleaching leaching periods periods evident evident in Figure in 13Figure. In the 13 first. In period, the first easy period, leachable easy minerals leachable led minerals to comparatively led to comparativelyrapid iron extraction. rapid iron The extraction. extraction T ratehe extraction then decreased rate then in the decreased second period, in the second due to theperiod, depletion due to of therapidly depletion leachable of rapidly and more leachable accessible and more minerals. accessible minerals.

6.0E+7

5.0E+7 T=37 °C, Day 0 T=37 °C, Day 132 4.0E+7 T=65 °C, Day 0 T=65 °C, Day 159 3.0E+7

2.0E+7

1.0E+7 Number of sulphide mineral voxels ofsulphidemineral Number 0.0E+0 0 500 1000 1500 2000 2500 3000 3500 4000 4500 Mineral distance from ore particle surface (µm)

Figure 14. Change in the distribution of sulphide minerals as a function of position and time for the

Figurewaste rock14. Change containing in the pyrite distribution at 37 and of 65 sulphide◦C. The uncertaintyminerals as ina function the grain of distance position from and the time ore for surface the wasteis 40.2 rockµ m.containing pyrite at 37 and 65 °C. The uncertainty in the grain distance from the ore surface ± is ±40.2 μm.

Minerals 2020, 10, x FOR PEER REVIEW 18 of 28 Minerals 2020, 10, 746 18 of 27 Minerals 2020, 10, x FOR PEER REVIEW 18 of 28 3.5E+7 3.5E+7 3.0E+7 Day 0 Day 11 3.0E+7 Day 0 2.5E+7 DayDay 45 11 2.5E+7 Day 79 2.0E+7 Day 45 DayDay 133 79 2.0E+7 1.5E+7 Day 133 1.5E+7 1.0E+7 1.0E+7 5.0E+6

Number of sulphide mineral voxels ofsulphideNumbermineral 5.0E+6 0.0E+0 Number of sulphide mineral voxels ofsulphideNumbermineral 0.0E+0 0 500 1000 1500 2000 2500 3000 3500 4000 0 500Mineral1000 distance1500 from 2000ore particle2500 surface3000 (µm)3500 4000 Mineral distance from ore particle surface (µm) Figure 15. Change in the distribution of sulphide minerals as a function of position and time for the Figure 15. waste rock containingChange in pyrite the distribution at 37 °C (the of sum sulphide of three minerals tracked as sections). a function The of uncertainty position and in time the grain for the Figurewaste rock15. Change containing in the pyrite distribution at 37 C (theof sulphide sum of threeminerals tracked as a sections).function of The position uncertainty and time in the for grain the distance from the ore surface is ±40.2◦ μm. wastedistance rock from containing the ore surfacepyrite at is 3740.2 °C (theµm. sum of three tracked sections). The uncertainty in the grain ± distance from the ore surface is ±40.2 μm. 3.5E+7 3.5E+7 3.0E+7 Day 0 3.0E+7 DayDay 11 0 2.5E+7 DayDay 45 11 2.5E+7 2.0E+7 DayDay 79 45 2.0E+7 DayDay 132 79 1.5E+7 DayDay 159 132 1.5E+7 1.0E+7 Day 159 1.0E+7 5.0E+6 Number of sulphide mineral voxels sulphideofmineral Number 5.0E+6 0.0E+0 Number of sulphide mineral voxels sulphideofmineral Number 0.0E+0 0 500 1000 1500 2000 2500 3000 3500 4000 4500 0 Sulphide500 1000 mineral1500 distance2000 from2500 ore particle3000 surface3500 (µm)4000 4500 Figure 16. Change in theSulphide distribution mineral of sulphide distance minerals from as ore a function particle of position surface and (µm) time for the Figurewaste 16 rock. Change containing in the pyrite distribution at 65 ◦C of (the sulphide sum of minerals three tracked as a function sections). of Theposition uncertainty and time in thefor grainthe wastedistance rock fromcontaining the ore pyrite surface at is65 °C40.2 (theµm. sum of three tracked sections). The uncertainty in the grain Figure 16. Change in the distribution± of sulphide minerals as a function of position and time for the distance from the ore surface is ±40.2 μm. waste rock containing pyrite at 65 °C (the sum of three tracked sections). The uncertainty in the grain distance from the ore surface is ±40.2 μm.

MineralsMinerals 20202020,, 1010,, 746x FOR PEER REVIEW 1919 ofof 2728

90 80 70 37 °C

(%) 60 65 °C 50 40 30 Pyrite recovery Pyrite

20 10 0 0 500 1000 1500 2000 2500 3000 Distance from ore surface (μm)

Figure 17. Comparison of the final iron recovery at different distances to the ore particle surface at 37Figure◦C and 17 65. Comparison◦C. of the final iron recovery at different distances to the ore particle surface at 37 °C and 65 °C. 4.2.3. Chalcopyrite 4.2.3.Changes Chalcopyrite in the pH, redox potential, ferrous ion (Fe2+) and ferric ion (Fe3+) concentrations of the effluent solution from the chalcopyrite leach are shown in Figure 18. There are no meaningful Changes in the pH, redox potential, ferrous ion (Fe2+) and ferric ion (Fe3+) concentrations of the differences in these parameters at the two different temperatures because of the high concentration of effluent solution from the chalcopyrite leach are shown in Figure 18. There are no meaningful ferric and ferrous ion in the solution and the relatively small amount of mineral in the mini-columns. differences in these parameters at the two different temperatures because of the high concentration The pH of the effluent during the acid wash (first 5 days) was initially 1.8 and decreased to 1.25, of ferric and ferrous ion in the solution and the relatively small amount of mineral in the mini- owing to the dissolution of acid soluble gangue minerals in the ore. After the introduction of the columns. lixiviant feed solution, the pH decreased further and reached approximately pH 1.15 on day 25. The pH The pH of the effluent during the acid wash (first 5 days) was initially 1.8 and decreased to 1.25, subsequently remained between pH 1.14 and 1.17. owing to the dissolution of acid soluble gangue minerals in the ore. After the introduction of the The redox potentials increased from 395–400 mV to about 430 mV during the acid washing. In the lixiviant feed solution, the pH decreased further and reached approximately pH 1.15 on day 25. The first 15 days of ferric leaching, the redox rose from 430 to 440 mV. This can be attributed to the fast pH subsequently remained between pH 1.14 and 1.17. leaching of exposed mineral grains and the precipitation of ferric ion because of the high temperature The redox potentials increased from 395–400 mV to about 430 mV during the acid washing. In (65 C). It subsequently remained in the range of 443–446 mV, slightly higher than the feed redox the ◦first 15 days of ferric leaching, the redox rose from 430 to 440 mV. This can be attributed to the value of 440 mV. The redox changes were corroborated by ferrous and ferric ion concentrations in the fast leaching of exposed mineral grains and the precipitation of ferric ion because of the high effluent solution. temperature (65 °C). It subsequently remained in the range of 443–446 mV, slightly higher than the feed redox value of 440 mV. The redox changes were corroborated by ferrous and ferric ion concentrations in the effluent solution.

Minerals 2020, 10, x FOR PEER REVIEW 20 of 28 Minerals 2020, 10, 746 20 of 27

(a) (b)

Figure 18. Changes of the effluent (a) pH, (b) redox potential (mV), (c) ferrous ion (g L1−1) and (d) ferric Figure 18. Changes of the effluent (a) pH, (b) redox potential (mV), (c) ferrous ion (g L− ) and (d) ferric −1 ionion concentrationconcentration (g(g LL 1) for chalcopyrite leaching at 37 °CC( (●) and 65 °CC( (▲N).). − ◦ • ◦ FigureFigure 19 19 showsshows thethe copper copper recovery recovery from from the the chalcopyrite chalcopyrite ore, ore, based based on on thethe chemistrychemistry measurementsmeasurements fromfrom AAS,AAS, asas wellwell asas thethe overalloverall percentagepercentage ofof sulphidesulphide mineralmineral leached,leached, calculatedcalculated fromfrom the the mineral mineral volume volume in in the the X-ray X-rayµCT μCT images. images. The The results results show show the progressionthe progression from from rapid rapid to slow to ferricslow ionferric leaching ion leaching periods. periods. In the first In the period, first easilyperiod leachable, easily leachable minerals ledminerals to rapid led copper to rapid extraction. copper Theextraction. copper extractionThe copper rate extraction decreased rate in thedecreased second period,in the duesecond to the period, depletion due ofto thethe rapidlydepletion leachable of the andrapidly more leachable accessible and minerals. more This accessible corresponds minerals. to the This effluent corresponds data, which to indicated the effluent rapid data, leaching which at theindicated start, followed rapid leaching by little at consumption the start, followed of the leachingby little consumption reagents provided of the in leaching the feed reagents from circa provided day 20. in theThere feed are from only circa 3% andday 2%20. differences between the chemistry results and the X-ray µCT imaging data at 37 ◦C and 65 ◦C, respectively. This confirms that the X-ray µCT images are a good measure of copper leaching. Larger deviations between the two analysis methods towards the end of the experimental period can be attributed to the cumulative effect of leaching of other non-copper-containing minerals present in the ore (e.g., pyrite) which are thresholded along with the chalcopyrite during the X-ray µCT image analysis. Increasing the temperature from 37 ◦C to 65 ◦C resulted in the clear enhancement of leaching, with the copper recovery increasing from 20% at 37 ◦C to 64% at 65 ◦C by the end of the leaching period, and the overall sulphide mineral dissolution increasing from 24% to 67%.

MineralsMinerals2020 2020, 10, 10, 746, x FOR PEER REVIEW 2121 of of 27 28

70 37 °C, AAS data 70 65 °C, AAS data

60 60 µCT ray

37 °C, X-ray µCT data - X 65 °C, X-ray µCT data 50 50

40 40 (%) 30 30

20 20

Copper recovery measured by by (%) AAS measured recovery Copper 10 10

0 0 by measured leached mineral Sulphide 0 30 60 90 120 150 Time (days)

Figure 19. Comparison of the copper recovery measured by AAS (solid lines) and the sulphide mineral Figure 19. Comparison of the copper recovery measured by AAS (solid lines) and the sulphide leached based on image measurement (dashed lines) for chalcopyrite. mineral leached based on image measurement (dashed lines) for chalcopyrite. Figure 20 shows the distributions of the sulphide mineral within the ore, expressed as the distance There are only 3% and 2% differences between the chemistry results and the X-ray μCT imaging from the ore particle surface, before the start of leaching (day 0) and at the end of the leaching (day 165) data at 37 °C and 65 °C, respectively. This confirms that the X-ray μCT images are a good measure of for the mini-columns operated at 37 ◦C and 65 ◦C. The sums of the three tracked sections at different copper leaching. Larger deviations between the two analysis methods towards the end of the time points are presented in Figures 21 and 22. experimental period can be attributed to the cumulative effect of leaching of other non-copper- The maximum leaching penetration distance was 1.7 mm at 37 ◦C, beyond which no mineral containing minerals present in the ore (e.g., pyrite) which are thresholded along with the chalcopyrite volume change was observed. This increased to 2.5 mm at 65 ◦C. At the lower temperature, minerals during the X-ray μCT image analysis. were leached within 0.6 mm of the ore particle surfaces during the first two weeks. The leaching Increasing the temperature from 37 °C to 65 °C resulted in the clear enhancement of leaching, penetration distance then increased to 1.2 mm by day 84, with the small amount of leaching at distances with the copper recovery increasing from 20% at 37 °C to 64% at 65 °C by the end of the leaching between 1.2 and 1.7 mm occurring during the later stages of leaching. Crack development was not period, and the overall sulphide mineral dissolution increasing from 24% to 67%. observed at 37 ◦C and the majority of the leaching was carried out in the more porous rim section of Figure 20 shows the distributions of the sulphide mineral within the ore, expressed as the the agglomerate structure, as presented in Figure7. At 65 ◦C, changes in the mineral content were distance from the ore particle surface, before the start of leaching (day 0) and at the end of the leaching limited to a distances less than 2.1 mm until day 84. This distance corresponds to the higher porosity (day 165) for the mini-columns operated at 37 °C and 65 °C. The sums of the three tracked sections at region of the agglomerates, as presented in Figure7. By day 165, the mineral recovery was observed at different time points are presented in Figure 21 and Figure 22. distances greater than 2.1 mm from the ore surface. The maximum leaching penetration distance was 1.7 mm at 37 °C, beyond which no mineral The copper recoveries at different distances from the ore surface are presented in Figure 23. volume change was observed. This increased to 2.5 mm at 65 °C. At the lower temperature, minerals The mini-column at 37 ◦C had a copper recovery in the range of 30% to 14% across the range of distance were leached within 0.6 mm of the ore particle surfaces during the first two weeks. The leaching values. The copper recovery first increased from 24% at the distance value of 200 µm to 30% in the penetration distance then increased to 1.2 mm by day 84, with the small amount of leaching at range of 400–600 µm. It decreased to 14% at a distance value of 1.2 mm. It subsequently remained low, distances between 1.2 and 1.7 mm occurring during the later stages of leaching. Crack development in the range of 14–17% between 1200 and 1700 µm. This is indicative of reaction kinetics, not lixiviant was not observed at 37 °C and the majority of the leaching was carried out in the more porous rim diffusion and contact, being the rate limiting factor for the chalcopyrite leaching at 37 ◦C, expected at section of the agglomerate structure, as presented in Figure 7. At 65 °C, changes in the mineral content this lower temperature. At 65 ◦C, there was a high recovery of the grains closer to the surface, with the were limited to a distances less than 2.1 mm until day 84. This distance corresponds to the higher same degree of leaching of >70% observed for the first 600 µm. There was no reagent limitation in porosity region of the agglomerates, as presented in Figure 7. By day 165, the mineral recovery was this region, with the reaction being controlled by kinetics. This distance correlates to the maximum in observed at distances greater than 2.1 mm from the ore surface. the agglomerated ore porosity (Figure7). Beyond 1 mm, the recovery decreased steadily from 69% The copper recoveries at different distances from the ore surface are presented in Figure 23. The mini-column at 37 °C had a copper recovery in the range of 30% to 14% across the range of distance values. The copper recovery first increased from 24% at the distance value of 200 μm to 30% in the

Minerals 2020, 10, x FOR PEER REVIEW 22 of 28 range of 400–600 μm. It decreased to 14% at a distance value of 1.2 mm. It subsequently remained low, in the range of 14–17% between 1200 and 1700 μm. This is indicative of reaction kinetics, not lixiviant diffusion and contact, being the rate limiting factor for the chalcopyrite leaching at 37 °C, expected at this lower temperature. At 65 °C, there was a high recovery of the grains closer to the surface, with the same degree of leaching of >70% observed for the first 600 μm. There was no reagent limitation in this region, with the reaction being controlled by kinetics. This distance correlates to the maximum in the agglomerated ore porosity (Figure 7). Beyond 1 mm, the recovery decreased steadily from 69% to 19%, attributable to the increasing limitation to lixiviant accessibility as the distance from the ore surface increased. Example image slices from before and at the end of leaching at 37 °C and 65 °C are shown in Figure 24. Crack development in the ore particles is evident at the higher temperature, but not at 37 °C. The leaching of the deeper mineral at 65 °C may therefore reasonably be attributed to the formation of cracks during the later stages of ferric leaching. The formation of the cracks was most likely due to the dissolution of the mineral lattice, as no significant pressure on the ore particles was present in the mini-columns. Significant enhancement of copper recovery with increased temperature, as presented in Figure 19, confirms the pronounced effect of temperature on chalcopyrite ferric leaching due to the high activationMinerals 2020 energies., 10, 746 However, the X-ray μCT acquisitions show that the enhanced recovery was22 not of 27 only due to the increased leaching rate, as the maximum penetration distance also increased by 0.8 mm at the higher temperature, increasing the availability of grains for leaching. Thus, an increasing to 19%, attributable to the increasing limitation to lixiviant accessibility as the distance from the ore temperature appears also to have reduced the diffusion limitation to leaching. surface increased.

4.0E+06

3.5E+06 T=37 °C, Day 0 3.0E+06 T=37 °C, Day 165 T=65 °C, Day 0 2.5E+06 T=65 °C, Day 165 2.0E+06

1.5E+06

1.0E+06

5.0E+05 Number of sulphide mineral voxels sulphideofmineral Number 0.0E+00 0 1000 2000 3000 4000 5000 Mineral distance from ore particle surface (µm)

Figure 20. Change in the distribution of sulphide minerals as a function of position and time for the

Figurechalcopyrite 20. Change ore in at the 37 ◦ distributionC and 65 ◦C. of Thesulphide uncertainty minerals in as the a grainfunction distance of position from and the oretime surface for the is Mineralschalcopyrite40.2 2020µm., 10 ore, x FOR at 37 PEER °C and REVIEW 65 °C. The uncertainty in the grain distance from the ore surface is ±40.2 23 of 28 ± μm. 2.0E+6 1.8E+6 1.6E+6 Day 0 Day 15 1.4E+6 Day 84 1.2E+6 Day 133 1.0E+6 Day 165

8.0E+5 6.0E+5 4.0E+5 2.0E+5 Number of sulphide mineral voxels ofsulphideNumbermineral 0.0E+0 0 1000 2000 3000 4000 5000

Sulphide mineral distance from ore particle surface (µm) FigureFigure 21. 21Change. Change in in the the distribution distribution of of sulphide sulphide minerals minerals as as a functiona function of of position position and and time time for for the the chalcopyritechalcopyrite ore ore at 37at ◦37C (the°C (the sum sum of three of three tracked tracked sections). sections). The uncertaintyThe uncertainty in the in grain the distancegrain distance from thefrom ore the surface ore surface is 40.2 isµ ±40.2m. μm. ±

2.0E+6 1.8E+6 Day 0 1.6E+6 Day 15 1.4E+6 Day 45 1.2E+6 Day 84 1.0E+6 Day 165 8.0E+5 6.0E+5 4.0E+5 2.0E+5 Number of sulphide mineral voxels sulphideofmineral Number 0.0E+0 0 1000 2000 3000 4000 5000 Sulphide mineral distance from ore particle surface (µm)

Figure 22. Change in the distribution of sulphide minerals as a function of position and time for the chalcopyrite ore at 65 °C (the sum of three tracked sections). The uncertainty in the grain distance from the ore surface is ±40.2 μm.

Minerals 2020, 10, x FOR PEER REVIEW 23 of 28

2.0E+6 1.8E+6 1.6E+6 Day 0 Day 15 1.4E+6 Day 84 1.2E+6 Day 133 1.0E+6 Day 165 8.0E+5 6.0E+5 4.0E+5 2.0E+5 Number of sulphide mineral voxels ofsulphideNumbermineral 0.0E+0 0 1000 2000 3000 4000 5000

Sulphide mineral distance from ore particle surface (µm) Figure 21. Change in the distribution of sulphide minerals as a function of position and time for the chalcopyrite ore at 37 °C (the sum of three tracked sections). The uncertainty in the grain distance Minerals 2020, 10, 746 23 of 27 from the ore surface is ±40.2 μm.

Figure 22. Change in the distribution of sulphide minerals as a function of position and time for the

chalcopyriteFigure 22. Change ore at 65in◦ theC (the distribution sum of three of sulphide tracked sections).minerals Theas a uncertaintyfunction of inposition the grain and distance time for from the Mineralsthechalcopyrite 2020 ore, 10 surface, x FOR ore isPEER at40.2 65 REVIEW °Cµm. (the sum of three tracked sections). The uncertainty in the grain distance24 of 28 ± from the ore surface is ±40.2 μm. 80 37 °C, X-ray µCT data 70 65 °C, X-ray µCT data

20 Sulphide mineral recovery (%) recovery mineral Sulphide

0 0 200 400 600 800 1000 1200 1400 1600 1800 2000 2200 2400 Distance from ore surface (µm)

Figure 23. Comparison of the copper recovery at diﬀerent distance to surface values for the low-grade Figurechalcopyrite 23. Comparison ore. of the copper recovery at different distance to surface values for the low-grade chalcopyrite ore. Example image slices from before and at the end of leaching at 37 ◦C and 65 ◦C are shown in Figure 24. Crack development in the ore particles is evident at the higher temperature, but not at 37 ◦C.

Minerals 2020, 10, 746 24 of 27

The leaching of the deeper mineral at 65 ◦C may therefore reasonably be attributed to the formation of cracks during the later stages of ferric leaching. The formation of the cracks was most likely due to the dissolution of the mineral lattice, as no significant pressure on the ore particles was present in the mini-columns. Significant enhancement of copper recovery with increased temperature, as presented in Figure 19, confirms the pronounced effect of temperature on chalcopyrite ferric leaching due to the high activation energies. However, the X-ray µCT acquisitions show that the enhanced recovery was not only due to the increased leaching rate, as the maximum penetration distance also increased by 0.8 mm at the higherMinerals temperature,2020, 10, x FOR PEER increasing REVIEW the availability of grains for leaching. Thus, an increasing temperature25 of 28 appears also to have reduced the diffusion limitation to leaching.

37 °C, Day 0 37 °C, Day 165

65 °C, Day 0 65 °C, Day 165

Figure 24. Example slices of the chalcopyrite leaching columns before and at the end of leaching at Figure 24. Example slices of the chalcopyrite leaching columns before and at the end of leaching at 37 37 C and 65 C, as evidence of crack development at the higher temperature. °C ◦and 65 °C,◦ as evidence of crack development at the higher temperature. 5. Conclusions 5. Conclusions X-ray µCT was used successfully to quantify the leaching of non-surface mineral grains in three diﬀerentX-ray ore μCT types was and used at disuccessfullyﬀerent operating to quantify conditions the leaching with the of aim non of-surface improving mineral the understandinggrains in three ofdifferent the limitations ore types to and their at recovery.different operating conditions with the aim of improving the understanding of the limitations to their recovery. For all three ore types, good agreement was demonstrated between the traditional chemistry- based analysis of the effluent to determine the metal leaching and quantification of the mineral volume changes from the X-ray μCT images segmented using the Avizo® 9 Interactive Thresholding function. Chemical reaction-controlled leaching was demonstrated for the highly porous malachite ore. In cases such as this, there is no observed limitation on lixiviant access (diffusion) and thus no motivation to modify the operating conditions or ore preparation to improve recoveries. The lower porosity pyrite and chalcopyrite-agglomerated ore systems showed more complex behaviour. In both cases, negligible changes in the leaching extent at different positions within the maximum penetration distances at the lower temperature condition were indicative of reaction- controlled leaching systems. Increasing the temperature saw increases in mineral leaching at the ore

Minerals 2020, 10, 746 25 of 27

For all three ore types, good agreement was demonstrated between the traditional chemistry-based analysis of the effluent to determine the metal leaching and quantification of the mineral volume changes from the X-ray µCT images segmented using the Avizo® 9 Interactive Thresholding function. Chemical reaction-controlled leaching was demonstrated for the highly porous malachite ore. In cases such as this, there is no observed limitation on lixiviant access (diffusion) and thus no motivation to modify the operating conditions or ore preparation to improve recoveries. The lower porosity pyrite and chalcopyrite-agglomerated ore systems showed more complex behaviour. In both cases, negligible changes in the leaching extent at different positions within the maximum penetration distances at the lower temperature condition were indicative of reaction-controlled leaching systems. Increasing the temperature saw increases in mineral leaching at the ore particle surfaces. However, the decreasing leaching extent with increasing distance from the agglomerated ore particle surface at the higher temperature indicated that leaching became limited by access to the lixiviant. This points to either a partially diffusion-controlled system or more completely occluded (inaccessible) mineral grains being located further from the ore particle surface i.e., in the centre of the ore particle compared with the agglomerated rim. In terms of chalcopyrite, the structure and higher porosity of the agglomerate rim and conditions that resulted in the degradation of the full ore matrix structure within the ore particle were found to be critical determining variables of the leaching rate and extent for the less porous ores. In the pyrite system, no changes in the maximum penetration distance were observed with a temperature increase. Therefore, increasing the temperature decreases the leaching time for this particular ore, but not the total recoverable metal. However, in the chalcopyrite leaching system, the higher temperature leach resulted in crack development in the particles and an associated increase in the leaching penetration distance, leading to an enhancement in copper recovery and sulphide mineral dissolution. Thus, increased chalcopyrite recovery was due to improved mineral access owing to change in the gangue-supporting matrix, as well as more favourable thermodynamic conditions for leaching. X-ray µCT has been demonstrated as an excellent tool for the investigation of these factors. Further development of the segmentation techniques for the improved identification of the various mineral types (including gangue phases) should be sought in line with this observation.

Author Contributions: Conceptualization, M.A.F.-E. and S.T.L.H.; methodology, M.G., M.A.F.-E. and S.T.L.H.; validation, M.G., M.A.F.-E. and S.T.L.H.; formal analysis, M.G., M.A.F.-E. and S.T.L.H.; investigation, M.G.; resources, M.A.F.-E. and S.T.L.H.; data curation, M.G., M.A.F.-E. and S.T.L.H.; writing—original draft preparation, M.G.; writing—review and editing, M.G., M.A.F.-E. and S.T.L.H.; supervision, M.A.F.E. and S.T.L.H.; project administration, M.A.F.-E.; funding acquisition, M.A.F.-E and S.T.L.H. All authors have read and agreed to the published version of the manuscript. Funding: This research was funded by South African Minerals to Metals Research Institute (SAMMRI), grant number S1510. The X-ray µCT imaging was additionally funded by the University of Cape Town (UCT) University Research Committee Start-up and Block Grant programmes. STLH gratefully acknowledges the DST and NRF of South Africa for funding through the SARChI National Research Chair in Bioprocess Engineering, grant UID 64778. Acknowledgments: We thank Mintek for granting permission to use their malachite ore for this study. We further thank Paul Keanly (X-Sight X-ray Services) and Dr Megan Becker (UCT) respectively for their assistance and guidance in the acquisition of the X-ray and QEMSCAN images. Conﬂicts of Interest: The authors declare no conﬂict of interest.

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