Mineralogical Prediction of Flotation Performance for a Sediment-Hosted Copper–Cobalt Sulphide Ore
As part of a study investigating the influence of mineralogical variability in a sediment hosted copper–cobalt deposit in the Democratic Republic of Congo on flotation performance, the flotation of nine sulphide ore samples was investigated through laboratory batch kinetics tests and quantitative mi...
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doaj-331f73870be7481b9094152a7d9d1da32020-11-25T03:10:10ZengMDPI AGMinerals2075-163X2020-05-011047447410.3390/min10050474Mineralogical Prediction of Flotation Performance for a Sediment-Hosted Copper–Cobalt Sulphide OreLaurens T. Tijsseling0Quentin Dehaine1Gavyn K. Rollinson2Hylke J. Glass3Camborne School of Mines, University of Exeter, Penryn, Cornwall TR10 9FE, UKCamborne School of Mines, University of Exeter, Penryn, Cornwall TR10 9FE, UKCamborne School of Mines, University of Exeter, Penryn, Cornwall TR10 9FE, UKCamborne School of Mines, University of Exeter, Penryn, Cornwall TR10 9FE, UKAs part of a study investigating the influence of mineralogical variability in a sediment hosted copper–cobalt deposit in the Democratic Republic of Congo on flotation performance, the flotation of nine sulphide ore samples was investigated through laboratory batch kinetics tests and quantitative mineral analyses. Using a range of ore samples from the same deposit the influence of mineralogy on flotation performance was studied. Characterisation of the samples through QEMSCAN showed that bornite, chalcopyrite, chalcocite and carrollite are the main copper-bearing sulphide minerals while carrollite is the only cobalt-bearing mineral. Mineralogical characteristics were averaged per sample to allow for a quantitative correlation with flotation performance parameters. Equilibrium recoveries, rate constants and final grades of the samples were correlated to the feed mineralogy through Multiple Linear Regression (MLR). Target sulphide minerals content and particle size, magnesiochlorite content, carrollite liberation and association of the copper and cobalt minerals with magnesiochlorite and dolomite were used to predict flotation performance. Leave One Out Cross Validation (LOOCV) revealed that the final copper and cobalt grades are predicted with an R<sup>2</sup> of 0.80 and 0.93 and Root Mean Square Error of Cross Validation (RMSECV) of 4.41% and 1.34%. The recovery of cobalt and copper with time can be predicted with an R<sup>2</sup> of 0.94 for both and an overall test error of 4.70% and 5.14%. Overall, it was shown that quantitative understanding of changes in mineralogy allows for prediction of changes in flotation performance.https://www.mdpi.com/2075-163X/10/5/474flotation modellingmineralogygeometallurgycoppercobaltQEMSCAN. |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Laurens T. Tijsseling Quentin Dehaine Gavyn K. Rollinson Hylke J. Glass |
spellingShingle |
Laurens T. Tijsseling Quentin Dehaine Gavyn K. Rollinson Hylke J. Glass Mineralogical Prediction of Flotation Performance for a Sediment-Hosted Copper–Cobalt Sulphide Ore Minerals flotation modelling mineralogy geometallurgy copper cobalt QEMSCAN. |
author_facet |
Laurens T. Tijsseling Quentin Dehaine Gavyn K. Rollinson Hylke J. Glass |
author_sort |
Laurens T. Tijsseling |
title |
Mineralogical Prediction of Flotation Performance for a Sediment-Hosted Copper–Cobalt Sulphide Ore |
title_short |
Mineralogical Prediction of Flotation Performance for a Sediment-Hosted Copper–Cobalt Sulphide Ore |
title_full |
Mineralogical Prediction of Flotation Performance for a Sediment-Hosted Copper–Cobalt Sulphide Ore |
title_fullStr |
Mineralogical Prediction of Flotation Performance for a Sediment-Hosted Copper–Cobalt Sulphide Ore |
title_full_unstemmed |
Mineralogical Prediction of Flotation Performance for a Sediment-Hosted Copper–Cobalt Sulphide Ore |
title_sort |
mineralogical prediction of flotation performance for a sediment-hosted copper–cobalt sulphide ore |
publisher |
MDPI AG |
series |
Minerals |
issn |
2075-163X |
publishDate |
2020-05-01 |
description |
As part of a study investigating the influence of mineralogical variability in a sediment hosted copper–cobalt deposit in the Democratic Republic of Congo on flotation performance, the flotation of nine sulphide ore samples was investigated through laboratory batch kinetics tests and quantitative mineral analyses. Using a range of ore samples from the same deposit the influence of mineralogy on flotation performance was studied. Characterisation of the samples through QEMSCAN showed that bornite, chalcopyrite, chalcocite and carrollite are the main copper-bearing sulphide minerals while carrollite is the only cobalt-bearing mineral. Mineralogical characteristics were averaged per sample to allow for a quantitative correlation with flotation performance parameters. Equilibrium recoveries, rate constants and final grades of the samples were correlated to the feed mineralogy through Multiple Linear Regression (MLR). Target sulphide minerals content and particle size, magnesiochlorite content, carrollite liberation and association of the copper and cobalt minerals with magnesiochlorite and dolomite were used to predict flotation performance. Leave One Out Cross Validation (LOOCV) revealed that the final copper and cobalt grades are predicted with an R<sup>2</sup> of 0.80 and 0.93 and Root Mean Square Error of Cross Validation (RMSECV) of 4.41% and 1.34%. The recovery of cobalt and copper with time can be predicted with an R<sup>2</sup> of 0.94 for both and an overall test error of 4.70% and 5.14%. Overall, it was shown that quantitative understanding of changes in mineralogy allows for prediction of changes in flotation performance. |
topic |
flotation modelling mineralogy geometallurgy copper cobalt QEMSCAN. |
url |
https://www.mdpi.com/2075-163X/10/5/474 |
work_keys_str_mv |
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