Application of near-infrared spectroscopy to sensor based sorting of a porphyry copper ore

Dalm, M.; Buxton, Michael; Ruitenbeek, F.J.A. van; Voncken, J. H. L.

doi:10.1016/j.mineng.2013.12.016

Cited by 60 publications

(46 citation statements)

References 18 publications

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“…Calcite (CaCO 3 ) was present as a main acid-consuming gangue mineral. X-ray diffraction provide a comprehensive analysis of the minerals and have been employed extensively for compositional analysis of different copper ores [20,21].…”

Section: Analysis Of Reko Diq Copper Orementioning

confidence: 99%

Catalytic Efficiency of <i>Acidithiobacillus ferrooxidans</i> for Bioleaching Copper from Chalcocite Containing Sulfide Ore from Reko Diq Deposits

Furqan¹,

Farooq²,

Liaquat³

et al. 2020

Pol. J. Environ. Stud.

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Bioleaching of low-grade secondary copper sulphide ores using different microbial strains is an ecologically safe technology for the recovery of metals in the mineral and mining industry. The purpose of the present study was to analyze the mineral contents of Reko Diq deposits and to assess the dissolution of copper from sulfide ore by an indigenously isolated strain of acidophilic iron-and sulfur-oxidizing bacterium (BSTFe-2) in shake flask experiments. X-ray diffraction (XRD) analysis of the ore sample suggested that it contained 0.81% Cu on dry matter basis and contained chalcocite (Cu 2 S) and covellite (CuS) as main copper minerals. Pyrite (FeS 2 ) was also present as a sulfide mineral. The other minerals detected in the ore matrix were muscovite (a di-octahedral mica mineral), quartz, feldspar (anorthite) and calcite. Quartz (SiO 2 ) was the main silicate mineral present in the sample. Calcite (CaCO 3 ) was found as the main acid-consuming gangue mineral. We observed that about 80-90% of the total Cu content present in the ore matrix was solubilized during 30 days of the leaching process mediated by Acidithiobacillus ferrooxidans at 30ºC. Copper dissolution from ore was found to be directly related to the reaction pH (1.5-1.9). The leaching data obtained from the pulp densities (5, 10 and 20% wt/

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Section: Analysis Of Reko Diq Copper Orementioning

confidence: 99%

Catalytic Efficiency of <i>Acidithiobacillus ferrooxidans</i> for Bioleaching Copper from Chalcocite Containing Sulfide Ore from Reko Diq Deposits

Furqan¹,

Farooq²,

Liaquat³

et al. 2020

Pol. J. Environ. Stud.

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“…This trend is also apparent in sample spectra as one goes from samples of host-rocks and slightly altered rocks to "altered monzogranite 2", the most pervasively altered rock type (see also Table 6). The depth of the 2200 nm feature, on the other hand, and its relation to the depth of the OH-H 2 O feature around 1900 nm is related to the crystallinity of the mica (e.g., [73,101]); zones of lower mica crystallinity typically being associated with higher amounts of water in the crystal structure, and vice versa. In the Naundorf scene, a band ratio of the Al-OH feature at 2202 nm and the water feature in this dataset anomalously occurring at 1943 nm, indicating the presence of flourine-rich mica or other phases in the Naundorf rocks (e.g., [102,103]), was used as a proxy for the mica crystallinity ( Figure 5B).…”

Section: Ground-based Vnir-swir Hyperspectral Imagingmentioning

confidence: 99%

Integration of Terrestrial and Drone-Borne Hyperspectral and Photogrammetric Sensing Methods for Exploration Mapping and Mining Monitoring

et al. 2018

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Mapping lithology and geological structures accurately remains a challenge in difficult terrain or in active mining areas. We demonstrate that the integration of terrestrial and drone-borne multi-sensor remote sensing techniques significantly improves the reliability, safety, and efficiency of geological activities during exploration and mining monitoring. We describe an integrated workflow to produce a geometrically and spectrally accurate combination of a Structure-from-Motion Multi-View Stereo point cloud and hyperspectral data cubes in the visible to near-infrared (VNIR) and short-wave infrared (SWIR), as well as long-wave infrared (LWIR) ranges acquired by terrestrial and drone-borne imaging sensors. Vertical outcrops in a quarry in the Freiberg mining district, Saxony (Germany), featuring sulfide-rich hydrothermal zones in a granitoid host, are used to showcase the versatility of our approach. The image data are processed using spectroscopic and machine learning algorithms to generate meaningful 2.5D (i.e., surface) maps that are available to geologists on the ground just shortly after data acquisition. We validate the remote sensing data with thin section analysis and laboratory X-ray diffraction, as well as point spectroscopic data. The combination of ground- and drone-based photogrammetric and hyperspectral VNIR, SWIR, and LWIR imaging allows for safer and more efficient ground surveys, as well as a better, statistically sound sampling strategy for further structural, geochemical, and petrological investigations.

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“…Additionally, research results were published in many papers. SBS is mostly applied in recycling (Gundupalli et al, 2017;Mesina et al, 2007;Rahman et al, 2014), mining (Knapp et al, 2014;Lessard et al, 2014;Dalm et al, 2014) and food (Alaya et al, 2019;Cubero et al, 2011;Tu et al, 2007) processing plants. Sound information on the sorting performance of such technologies is limited, however.…”

Section: Introductionmentioning

confidence: 99%

Influence of Throughput Rate and Input Composition on Sensor-Based Sorting Efficiency

Küppers

Seidler

Koinig

et al. 2020

Volume 09 - March 2020

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According to the Directive (EU) 2018/851 of the European Union, higher recycling rates for municipal waste will have to be met in the near future. Beside improvements to the collection systems, the efficiency of mechanical processing and sorting will have to be increased to reach the EU´s targets. Sensor-based sorting (SBS) plants constitute an integral part of today's sorting processes. Two main factors determine the sorting performance: throughput rate and input composition. To improve recycling efficiencies, especially SBS machines need to be optimized. Three evaluation criteria are used to describe the performance of these processes: recovery (content of input material -both eject and reject material discharged into the product fraction) or product quantity (amount of product generated via sorting within a specific interval -calculated by multiplying throughput rate and yield), yield (amount of eject material discharged into the product fraction), and product purity. For this study, 160 sorting experiments each with 1,000 red and white low-density polyethylene (LDPE) chips were conducted to investigate the effects of throughput rate and input composition on sorting processes. This simplified approach reduced the influence of other factors on the sorting performance, giving precise information on the effect of throughput rate and input composition. The testing results can enter process optimization. With increasing throughput rates, product quantity rises following a saturation graph (despite exponential decrease in recovery). In the experiments a higher throughput rate also resulted in an exponential decrease of the yield while a change to the input composition had no such effect. The third evaluation criteria, product purity, decreases linearly with increasing occupation density. The slope of this function depends on the input composition.

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Application of near-infrared spectroscopy to sensor based sorting of a porphyry copper ore

Cited by 60 publications

References 18 publications

Catalytic Efficiency of <i>Acidithiobacillus ferrooxidans</i> for Bioleaching Copper from Chalcocite Containing Sulfide Ore from Reko Diq Deposits

Catalytic Efficiency of <i>Acidithiobacillus ferrooxidans</i> for Bioleaching Copper from Chalcocite Containing Sulfide Ore from Reko Diq Deposits

Integration of Terrestrial and Drone-Borne Hyperspectral and Photogrammetric Sensing Methods for Exploration Mapping and Mining Monitoring

Influence of Throughput Rate and Input Composition on Sensor-Based Sorting Efficiency

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