Differential flotation of pyrite and arsenopyrite: Effect of hydrogen peroxide and collector type

Forson, Philip; Zanin, Massimiliano; Skinner, William; Asamoah, Richmond K.

doi:10.1016/j.mineng.2021.106808

Cited by 33 publications

(10 citation statements)

References 45 publications

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“…The difference in pH conditions accounts for the discrepancy in pyrite recoveries in these works. Philip Forson et al found that H2O2 could not completely depressed the pyrite flotation using potassium amyl xanthate or sodium diisobutyl dithiophosphateat as a collector pH 6.4 (Forson et al, 2021). Our study showed that H2O2 could prevent the H2O2 flotation at such pH.…”

Section: Depressing Behavior Of H2o2 For Pyrite Flotationmentioning

confidence: 44%

“…The application of this oxidant is attracting considerable attention (Chen et al, 2022;Suyantara et al, 2018), owing to its minimal impact on the environment and low price. H2O2 could oxidize pyrite in the wide pH of 5-11 (Forson et al, 2021;Khoso et al, 2019a). This oxidant could also be used in the special flotation of pyrite using seawater (Yang et al, 2022).…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

New insights into pyrite-hydrogen peroxide interactions during froth flotation: experimental and DFT study

Cao¹,

Yan²,

Liu³

et al. 2022

Physicochem. Probl. Miner. Process.

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Hydrogen peroxide (H2O2) is an efficient depressant for pyrite (FeS2) flotation. However, the depressing mechanism of H2O2 is not fully understood. In this paper, the depressing capacity of H2O2 for pyrite was examined by flotation tests. Results revealed that pyrite flotation could be inhibited by H2O2 at pH 6.4. The pyrite powder in H2O2 solution enhanced the release of O2 from H2O2. However, the O2 concentration in the solution was less than that of H2O2; thus, H2O2 is the major oxidant in the solution. Moreover, density functional theory calculations were performed to study the interactions between H2O2 and hydrated pyrite (100) surface. The H2O2 molecule tended to react with the pyrite surface to generate one S=O bond and an H2O molecule. The possible binding models of O2 molecules on the pyrite (100) surface were also studied for comparison. The O2 dissociation on the pyrite surface was more favorable than the adsorption of O2 as a whole. In addition, the orbital interaction in the S=O bond raised from the reaction of H2O2/O2 with the pyrite surface was also investigated by the density states analysis. These results provide some insights into the oxidizing effect of H2O2 in pyrite flotation.

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Section: Depressing Behavior Of H2o2 For Pyrite Flotationmentioning

confidence: 44%

Section: Introductionmentioning

confidence: 99%

New insights into pyrite-hydrogen peroxide interactions during froth flotation: experimental and DFT study

Cao¹,

Yan²,

Liu³

et al. 2022

Physicochem. Probl. Miner. Process.

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“…where θ is a set of hyperparameters, and x, x ′ ϵ X are random variables. t(x) is shown in Equation (15).…”

Section: Gaussian Process Regression Algorithmmentioning

confidence: 99%

“…Froth flotation has seen remarkable widespread applications in the mineral industry for different highly valuable commodities (e.g., copper, gold, zinc, and rare earth elements) [14][15][16][17][18][19][20][21]. The interdependence of the process variables extends performance challenges to the flotation process where a change in feed mineralogy requires a corresponding change in the other flotation variables for an optimal outcome [22][23][24][25][26][27][28][29][30][31].…”

Section: Introductionmentioning

confidence: 99%

Prediction and Optimisation of Copper Recovery in the Rougher Flotation Circuit

Amankwaa-Kyeremeh,

McCamley,

Zanin

et al. 2023

Minerals

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In this work, the prediction and optimisation of copper flotation has been conducted in the rougher flotation circuit. The copper-recovery prediction involved the application of support vector machine (SVM), Gaussian process regression (GPR), multi-layer perceptron artificial neural network (ANN), linear regression (LR), and random forest (RF) algorithms on 15 rougher flotation variables at the BHP Olympic Dam. The predictive models’ performance was assessed using linear correlation (r), root mean square error (RMSE), mean absolute percentage error (MAPE), and variance accounted for (VAF). A simulated annealing (SA) optimisation algorithm, particle swarm optimisation (PSO) algorithm, surrogate optimisation (SO) algorithm, and genetic algorithm (GA) were investigated, using the GPR predictive function, to determine the optimal operating condition for maximising copper recovery. The predictive function of the best-performing model was extracted and used in optimising the flotation circuit. The results showed that the GPR model developed with the matern 3/2 kernel function makes the most precise copper-recovery prediction as compared to the other investigated predictive models, obtaining r values > 0.96, RMSE values < 0.42, MAPE values < 0.25%, and VAF values > 94%. A hypothetical optimisation solution assessment showed that SA provides the best set of solutions for the maximisation of rougher copper recovery, obtaining a throughput of 638.02 t/h and a total net gain percentage of 14%–15.5% over the other optimisation algorithms with a maximum copper recovery of 94.76%. The operational benefits of implementing these algorithms have been highlighted.

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“…Dixanthogens are dimers formed from two xanthate anions, and they are readily formed on the surfaces of some minerals, such as pyrite and arsenopyrite, during the flotation process. It has been studied that on the surface of oxidized pyrite, the adsorption of xanthate occurs through oxidation of xanthate ions to dixanthogen [ 14 ]. This oxidation is coupled with the reduction of Fe(III) species released from the mineral surface [ 15 ].…”

Section: Introductionmentioning

confidence: 99%

The effect of experimental conditions on the formation of dixanthogen by triiodide oxidation in the determination of ethyl xanthate by HPLC–ICP-MS/MS

et al. 2022

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The rising concern over the environmental impact of xanthates, especially in the arctic region, has increased the need to study these traditional flotation reagents in greater detail. The environmental concern relates mostly to the formation of carbon disulfide (CS2) and the heavy metal complexes of xanthates. Due to the unstable nature and multiple reaction mechanisms of xanthates, their reliable determination at low concentration levels is difficult. In this study, a xanthate pretreatment method was optimized and applied for the determination of ethyl xanthate (EX−) by high performance liquid chromatography–inductively coupled plasma tandem mass spectrometry (HPLC–ICP-MS/MS). Ethyl xanthate was oxidized to diethyl dixanthogen ((EX)2) by triiodide (I3−) in aqueous solution and the formed (EX)2 was extracted into n-hexane. Important experimental parameters, including pH, I3− amount, and oxidation time, were optimized and the detection limit of 0.29 mg L−1 for potassium ethyl xanthate was obtained. During the optimization experiments, it was found that the oxidation reaction resulted in multiple products, decreasing the efficiency of (EX)2 formation and, therefore, the sensitivity of the method. The proposed method was applied to wastewater samples with recoveries of 105–106%. This study provides a selective method for the determination of ethyl xanthate and introduces novel information on the parameters affecting the oxidation of xanthates. Graphical abstract

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Differential flotation of pyrite and arsenopyrite: Effect of hydrogen peroxide and collector type

Cited by 33 publications

References 45 publications

New insights into pyrite-hydrogen peroxide interactions during froth flotation: experimental and DFT study

New insights into pyrite-hydrogen peroxide interactions during froth flotation: experimental and DFT study

Prediction and Optimisation of Copper Recovery in the Rougher Flotation Circuit

The effect of experimental conditions on the formation of dixanthogen by triiodide oxidation in the determination of ethyl xanthate by HPLC–ICP-MS/MS

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