Cyanide Leaching Process Research Articles

Silver adsorption from gold leaching cyanide wastewater by a green functionalized magnetic graphene oxide Nano-adsorbent

A nanoadsorbent made of magnetic graphene oxide that was functionalized by glutathione (GSH/Fe3O4@GO NPs) was synthetized. Various characterization methods were employed to clarify the adsorbent's morphology and structure. The results confirmed the formation of nanosheets of graphene oxide with the homogenous coating of Fe3O4 nanoparticles and well conjugated glutathione (GSH) on its surface. This adsorbent was utilized to adsorb silver ion from synthetic AgCN solutions at pH = 10.5. A central composite design (CCD) was used to investigate the impact of silver and cyanide concentration. The significance of the concentration of cyanide and its interaction with silver concentration was confirmed. When the concentrations of silver and cyanide were 128 mg/L and 528 mg/L, respectively, the maximum adsorption capacity achieved was 586 mg/g. The successful fitting of the Freundlich isotherm explains the multilayer adsorption on the heterogeneous surface of the adsorbent. This adsorbent also showed significant efficiency in silver adsorption from a real cyanide wastewater sample as was predicted by the statistical model. The silver adsorption capacity of 123 mg/g were obtained from a gold cyanide leaching process wastewater (24.8 mg/L). The GSH/Fe3O4@GO NPs were found to be an effective adsorbent for extracting and separating silver ions from cyanide solutions.

Operating performance assessment based on stacked performance‐relevant enhanced denoising auto‐encoder for industrial processes

AbstractAs an effective way to ensure the economic benefits of enterprises, process operating performance assessment has attracted more and more attention from industry and academia in recent years. In this paper, a stacked performance‐relevant enhanced denoising autoencoder (SPEDAE) network is designed for the operating performance assessment of industrial processes. Compared to the original denoising auto‐encoder (DAE), each performance‐relevant enhanced denoising auto‐encoder (PEDAE) not only reconstructs the input features in the output layer, but also strives to reconstruct the original input data and the performance grade labels simultaneously. Then the SPEDAE is formed by stacking multiple PEDAEs layer by layer. Through this improved training strategy, SPEDAE can avoid accumulated information loss during the deep feature extraction process, improve the robustness of the network, and extract features closely related to the operating performance, thereby better completing the assessment task. The effectiveness of the proposed assessment method is validated on the case of gold cyanide leaching process. Compared with several methods, the proposed SPEDAE has the highest accuracy and reaches 99.85%, which demonstrates its superiority in operating performance assessment.

Process mineralogy characteristics of a very fine disseminated refractory gold deposit

The grade, recovery rate, or leaching rate of gold concentrate obtained by the flotation process or cyanide leaching process of gold ore is low, which is typical refractory gold ore. In order to fully understand the properties of the gold ore and optimize the gold recovery process and indicators, the process mineralogy of the ore was systematically studied by means of chemical multi-element analysis, optical microscope, scanning electron microscope (SEM), X-ray energy spectrometer, automatic mineral parameter analysis system (BPMA), and other test methods. The results show that the average grade of valuable element gold in the ore is 2.98g/t, and the contents of harmful elements mercury and carbon are 0.50% and 0.32% respectively; The main gold ore is natural gold, with a small amount of silver gold and tellurium gold; The main metal minerals are pyrite, pyrrhotite, magnetite, hematite, etc; The main gangue minerals include quartz, feldspar, kaolinite, mica, calcite, etc. Under the condition that the grinding fineness is -0.074mm, accounting for 90%, the distribution rates of single gold and bare gold in the ore are 3.15% and 57.66% respectively, and the distribution rates of gold with pyrite and quartz crystals are 5.77%, and the total distribution rates of the three are 66.58%, that is, the maximum theoretical flotation recovery rate of gold under the grinding fineness, but the particle size and fineness of gold minerals are both 5 μ Below m, the particle size of some gold ores is less than 0.5 μ m. It exists in the form of fine particles, micro gold, or ultra-micro gold, and it is difficult to recover gold by the flotation process, so it is recommended to adopt the whole slime cyanidation leaching process.

Potential of Shewanella Oneidensis as bioleaching agent in reducing Fe (III) to Fe (II) for gold extraction

Conventional method for gold extraction using cyanide is not environmentally friendly and harmful to the environment. Thus, we investigate the potential of Shewanella oneidensis as bioleaching agent for gold extraction to replace the cyanide leaching process. The concentration of Fe (II) was determined via Ferrozine Assay method using Spectrophotometer, while the concentration of gold (Au) was determined using Inductively Coupled Plasma Optical Emission Spectrometry (ICP-OES). Some minerals such as pyrite, arsenopyrite, hematite, magnetite, and quartz were detected in the ore samples using XRD. The results show, S. oneidensis MR-1 was able to reduce Fe (III) to Fe (II) that can increase gold concentration. Gold concentrations were increased from 19 ppb to 28.5 ppb with 50% of percentage yield increased. In addition, the result shows hematite and magnetite in the samples was also reduced after bioleaching which might lead to the increasing amount of gold concentration. As a conclusion, S. oneidensis MR-1 was shown to be effective for bioleaching to improve gold extraction process.

Cyanide Release Characteristics of Solid Waste in Gold Smelting Process

To explore the relationship between total cyanide and easily liberatable cyanide in cyanide tailings and its impact on the environment, the leaching and release characteristics of total cyanide and easily liberatable cyanide in a tailings pond were studied using a dynamic leaching experiment, and a dynamic model was established. The results show that the release concentration of total cyanide in cyanide tailings is higher than that of easily liberatable cyanide. With the increase in leaching time, the release of cyanide is more sensitive to leaching intensity. The first-order kinetic, second-order kinetic, modified Elovich, double constant, and parabolic diffusion equations were used to fit the cumulative release of cyanide. According to the kinetic results of cyanide cumulative release, in addition to the first-order kinetic equation, the other four equations revealed good fitting for the cyanide leaching process, which shows that cyanide released under simulated rainwater leaching was not simply via surface diffusion, but controlled by multiple factors.

A Few Pt Single Atoms Are Responsible for the Overall Co‐Catalytic Activity in Pt/TiO2 Photocatalytic H2 Generation

The use of single atoms (SAs) has become a highly investigated topic in heterogeneous catalysis, electrocatalysis, and most recently also in photocatalysis. In the field of photocatalysis, Pt SAs on TiO2 have been reported to be a highly efficient co‐catalyst in solar H2 production. Herein, the deposition of Pt SAs and nanoparticles on titania nanosheets is investigated. In particular, the Pt species responsible for the high co‐catalytic activity using a cyanide leaching process is elucidated. It is shown that neither Pt0 species nor the majority of Pt SAs do significantly contribute to the co‐catalytic activity of platinum on TiO2. In fact, >90% of the Pt of a standard deposition are non‐active and can be removed by cyanide leaching without activity loss—as a consequence, the remaining Pt SAs amount to a remarkable turnover frequency of 4.87 × 105 h−1 for H2 evolution.

Pore Evolution in Refractory Gold Ore Formed by Oxidation Roasting and the Effect on the Cyanide Leaching Process.

Refractory gold ore is usually affected by the associated carbonaceous matter through the preg-robbing effect, which is eliminated by oxidation roasting, followed by leaching, to achieve a satisfactory gold leaching efficiency. Roasting–leaching experiments, pore structure measurements, scanning electron microscopy (SEM), and X-ray diffraction are used to explore the structural evolution of pores on the surface and its effect on the leaching performance. Pores with optimal sizes were obtained by roasting at 650 °C for 2.0 h with a ventilation of 0.6 m3/h; approximately 92.55% gold could be recovered under these conditions. A porous structure observed by SEM became more compact as the temperature further increased to 850 °C. The formation of CaSiO3 and CaSO4 in pores led to pore shrinkage. The mechanism of oxidation roasting, followed by cyanide leaching, was schematically analyzed and revealed the effects of pore structural evolution and phase transformation on the leaching efficiency.

EFFECT OF PRESSURE ON GOLD CYANIDE LEACHING

Although the effect of high oxygen pressure on gold recoveries at elevated slurry temperatures was previously investigated, the sole effect of the pressure at ambient temperatures on cyanide leaching with the presence of nearly enough oxygen for the cyanide reactions to occur has not been found to be studied. This research work was carried out with the objective of investigating the effect of pressure on the recovery of gold from an oxide gold ore and flotation tailing (Carbon in leach (CIL) feed) samples during cyanide leaching process at room temperature. Pressure cyanidation experiments were run in a batch autoclave under different air and nitrogen gas pressures, and pH conditions. Atmospheric bottle roll leach tests for 24 and 8 hours resulted in 90.5% and 66.4% gold recoveries, respectively, whereas 8 hours batch autoclave leach tests under 90 psi air pressure resulted in 88.8% gold recovery from oxide ore samples. Flotation tailing samples leached under atmospheric and under 90 psi air pressure for 8 hours resulted in 16.8% and 34.5% gold recoveries, respectively.

Experimental study on thiosulfate leaching of gold from a high copper gold concentrate

The conventional cyanide leaching process is used to extract gold from a high copper gold concentrate. Because the copper associated minerals consume sodium cyanide in large quantities, the cost of the reagents is high and the economic benefit is not ideal. At the same time, a large number of cyanide tail slag are produced, which brings a series of environmental problems. In order to solve the environmental problems caused by excessive sodium cyanide consumption and cyanogen slag, the feasibility of leaching gold by thiosulfate in copper ammonia system was studied. The gold leaching rate of thiosulfate was increased to more than 90% by using the direct thiosulfate leaching process and pretreatment thiosulfate leaching process, which was close to the gold leaching index of sodium cyanide at the production site.

Multi‐stage economic model predictive control for a gold cyanidation leaching process under uncertainty

ABSTRACTIn order to dynamically operate the gold cyanidation leaching process (GCLP) under uncertainty, a multi‐stage economic model predictive control (EMPC) is proposed for GCLP for the transient and steady‐state economic optimization. The proposed multi‐stage EMPC is composed of two steps. In the first step, the unmeasurable uncertain parameters are estimated by using Tikhonov regularization based method, so as to avoid amplification and propagation of the noise measurements into the estimation. Based on the estimated results, the scenario tree for multi‐stage EMPC is generated from the historical data using a data‐driven approach, and the control inputs are obtained from solving the resulting large nonlinear programming problem (NLP) at each sampling point. The resulting uncertainty model and the probability of each scenario are more consistent with the actual industrial GCLP, and the solutions are less conservative. The efficiency of the proposed multi‐stage EMPC is verified through a simulated industrial GCLP. Compared with other EMPC methods, including classic EMPC and multi‐stage EMPC with box uncertainty region, the proposed method can reduce the economic cost while accounting for the constraints at the same time.

Multimode Process Mode Identification With Coexistence of Quantitative Information and Qualitative Information

The mode division and identification of the multimode process is to classify the normal production data according to the changes in process information and then to identify the corresponding process mode. The mode division and identification of the multimode process is the primary prerequisite for multimode process monitoring, evaluation, modeling, quality prediction, and process optimization. In the multimode complex industrial process, it usually contains both qualitative information and quantitative information, which makes the mode division and identification much more difficult. To deal with this problem, a new mode division and identification method is proposed in this article. First, the mode of the production process is roughly divided by the mode indicator variables that contain the initial production conditions with more qualitative variables. Then, the mode refinement is performed by using the process variables that contain a large amount of quantitative information. Therefore, the whole process is divided into multiple stable modes and transitional modes. At the end, the efficiency of the proposed method is illustrated with a case of the cyanide leaching process of gold hydrometallurgy. Note to Practitioners —From the practical application point of view, a new method of cross-referencing quantitative information model and qualitative information model is proposed in this article to divide the multimode production process into multiple stable modes and transitional modes. Then, feature models are established for different mode data online for process mode-type identification. The effective mode division and identification of multimode processes is the key to realize multimode process monitoring, evaluation, modeling, quality prediction, and process optimization. Although the validity of the proposed method is verified only in a gold hydrometallurgical cyanide leaching process, the method is equally applicable to other multimode complex industrial processes with the qualitative information and quantitative information coexistence characteristics.

Comparison of Alternative Strategies Estimating the Kinetic Reaction Rate of the Gold Cyanidation Leaching Process.

It is very important to establish an accurate process model for implementing further control and optimization of the gold cyanidation leaching process. Unfortunately, the important kinetic reaction rates affecting process operation are unmeasurable, and moreover, their estimation is an ill-posed inverse problem due to the fact that the noise in concentration measurements is easy to be amplified and propagated into the rate estimates by derivative operation. In this paper, the alternative strategies (finite difference, polynomial fitting, Savitzky–Golay filter, wavelet decomposition, and Tikhonov regularization) estimating the kinetic reaction rate of the gold cyanidation leaching process are investigated in detail. The simulation results show that the direct finite difference leads to poor estimating results for the noisy case and the other strategies are capable of avoiding the noise amplification and improving the estimating results to some extent. In all of the investigated strategies, the Tikhonov regularization leads to the satisfactory and acceptable estimating results in both the noiseless and noisy cases, which will lay an important foundation for the subsequent model identification, production index prediction, and operation optimization.

A Data-Driven Iterative Optimization Compensation Method Based on PJIT-PLS for Gold Cyanidation Leaching Process

Gold cyanidation leaching process (GCLP) as the central unit operation in hydrometallurgy, which suffers from the problem of the optimal setting point based-model is difficult to reach the optimal working point in actual GCLP due to model error, which leads to lower economic benefit. Meanwhile, the process data contains noise and uncertainty on account of the fluctuation of raw material properties. Therefore, how to take the most of that data to make the production process run in the optimal state of economic benefit under the premise that the quality index meets the production requirements is an urgent problem to be solved. In this paper, a data-driven iterative optimization compensation strategy is proposed to solve aforementioned problems. Firstly, probabilistic principle component analysis (PPCA) method is used to preprocess process data for eliminating the effect of noise and uncertainty; Secondly, two relevant models are established between the operating variable increment and the economic benefit increment, the quality index increment based on just in time (JIT) and partial least squares (PLS) method; Finally, the optimal operating variable increment that maximizes the economic benefit increment can be optimized under the condition of quality index satisfies the production requirements and iterated at the new working point, which is constantly close to the optimal working point to improve the economic benefit. Simulation studies have verified the validity of proposed method.

Gold Recovery Modeling Based on Interval Prediction for a Gold Cyanidation Leaching Plant

The production index of gold cyanidation leaching process has an important influence on the economic benefits of the plant-wide hydrometallurgical process. In the actual leaching production process, due to the fluctuations of the previous procedure, the leaching process is often affected by the uncertainty and process disturbance. And hence, the prediction accuracy of the traditional point prediction models (such as ANN: Artificial Neural Network) decreases seriously and cannot provide any quantified information about the uncertainty or process disturbance. To solve the above problem, the interval prediction technique based on Radial Basis Function (RBF) ANN is proposed and used to model a gold cyanidation leaching plant encountering uncertainty and process disturbances in this paper. The objective function trained in the interval prediction model is not based on the prediction error, but the comprehensive measure index, namely, the coverage width criteria, which consists of the prediction interval coverage probability and the prediction interval normalized averaged width. Compared to the traditional point prediction, when the process uncertainty and disturbances are present, the interval prediction model will provide more helpful process information to the operators or process designers for determining further optimization and control strategies. The simulation and practical application results show that most of the real values of gold recovery can be covered between the upper and lower bounds with a predefined probability, which indicates the effectiveness and reliability of the interval prediction model, thus laying an important foundation for plant-wide optimization and control.

Process Feature Change Recognition Based on Model Performance Monitoring and Adaptive Model Correction for the Gold Cyanidation Leaching Process

The gold cyanidation leaching process (GCLP) is the central unit operation in hydrometallurgy, and satisfactory gold recovery is highly significant in practice. However, GCLP faces the challenge of an irregular slow time-varying feature (STVF), which seriously affects gold recovery, and blind treatment for STVF also has drawbacks, which results in the need for the recognition of STVF for purposeful, rather than blind, treatment. Meanwhile, it also faces the problem of change of working condition (COWC) due to the variability of mineral resources. Both STVF and COWC may cause degradation of the soft-measuring model, which presents the need for model correction. Therefore, a coping strategy is proposed to solve these existing problems. First, an improved model-based principal component analysis monitoring is proposed to detect model mismatch and monitor the change of process feature. Next, a support vector machine-based process feature change recognition method is presented to recognize change type, which not only provides guidance in treating STVF but also makes it possible to implement targeted model correction for STVF and COWC. Finally, an adaptive model correction strategy that combines case-based correction and just-in-time learning-based correction is proposed. The simulation studies have verified the validity of the proposed coping strategy.

Au(CN)2]—Adsorption on a Graphite (0001) Surface: A First Principles Study

Gold is mainly present in the form of [Au(CN)2]− during the cyanide leaching process, and this [Au(CN)2]− can be adsorbed by graphite in carbonaceous gold ore resulting in preg-robbing gold. In order to clarify the adsorption mechanism between the [Au(CN)2]− and graphite, the interaction between the [Au(CN)2]− and graphite (0001) surface was studied using density functional theory (DFT). The distance between [Au(CN)2]− and graphite (0001) decreased from (4.298–4.440 Å) to (3.123–3.343 Å) after optimization, and the shape of [Au(CN)2]− and graphite (0001) obviously changed from straight to curved, which indicated that the [Au(CN)2]− had been adsorbed on the graphite (0001) surface. A partial densities of state (PDOS) analysis revealed that there was little change in the delocalization and locality of the PDOS on the graphite (0001) surface after adsorption. However, the valence bands of the Au 5d orbital, C 2p orbital, and N 2p orbital near the Fermi level moved slightly towards lower energy levels; therefore, the adsorption configuration was stable. An analysis of the Mulliken charge population indicated that the Au, N, and C in [Au(CN)2]− obtained 0.26, 0.18, 0.04 electrons after adsorption, respectively, while C(surf) lost 0.03 electrons. [Au(CN)2]− changed to a conductor from an insulator after adsorption. Taking into account the surface electrical properties of [Au(CN)2]− and graphite (0001), there was still a slight electrostatic adsorption between them. The analysis of adsorption energy, electronic structure, PDOS, electron density, Mulliken charge population, and Mulliken bond population revealed that [Au(CN)2]− could be adsorbed to the graphite (0001) surface; the adsorption was a type of physical adsorption (including electrostatic adsorption) and mainly occurred on the two C≡N. These results contributed to the understanding of the mechanisms involved in preg-robbing gold formation by graphite and the optimization of this process during cyanide leaching.

A Novel Electrochemical Approach to Study the Interaction of Blinding Agents with Preg-Robbers in Carbonaceous Gold Systems

Preg-robbing usually refers to the adsorption of a gold cyanide complex, i.e. Au(CN)2 −, on the components of a gold ore including carbonaceous materials and other minerals during the gold leaching process (1-3). The adsorption of gold ions on carbonaceous materials is one of the most common phenomenon responsible for gold losses from the cyanide leaching process (1, 4). Depending on the carbon content of the ores, gold losses may reach 90 % of leachable gold due to preg-robbing during cyanidation (5). Chemical blinding agents have previously been investigated to passivate the surface of carbonaceous preg-robbers in the ores, thus reducing the extent of preg-robbing and allowing an increase in gold recovery (1, 3, 6, 7). However, the mechanism by which such agents suppress the ion-adsorption capability of the carbonaceous materials as well as their interactions with other components of the ore, including pyrite, and more importantly, gold, are yet to be fundamentally investigated. The latter process could severely affect final gold recovery if the surface of the gold becomes passivated. This study investigates the effect of various blinding agents on the main components of a gold-containing concentrate: carbon, gold and pyrite. A novel electrochemical approach is employed, i.e. double-layer capacitance measurements combined with electro-oxidation/reduction peaks obtained from cyclic voltammetry tests. Our group is the first to employ the electric double-layer theory to study the preg-robbing capacity of carbonaceous ores with total carbonaceous matter (TCM) contents as low as 0.3 % by weight. Figure 1 shows a comparison between the blinding activity, and durability, of various surfactants and chemical reagents, at different concentrations, on the surface of activated carbon particles over a 24-hour contact period. The capacitance is an indication of how well the chemical reagents have been adsorbed on the activated carbon particles with the lowest capacitance values showing the best surface adsorption. The study reveals that kerosene, Lecithin and Polymax 30 are among the best blinding agents for the activated carbon surfaces in terms of adsorption and durability. Further cyclic voltammetry studies on gold surfaces in alkaline cyanide solutions (with the added blinding agents) have shown that kerosene is the least detrimental to the gold cyanide leaching process, i.e. the electrochemical oxidation reaction for the formation of AuCN complex. Figure 1. A comparative study for the effect of various chemical reagents, i.e. Aristonate H and L, Lecithin, Sodium dodecyl sulfate (SDS), kerosene and Polymax 30, on the ion adsorption capability of the activated carbon particles over 24 hours.

New insights into the extraction of invisible gold in a low-grade high-sulfur Carlin-type gold concentrate by bio-pretreatment

To extract gold from a low-grade (13.43 g/t) and high-sulfur (39.94wt% sulfide sulfur) Carlin-type gold concentrate from the Nibao deposit, Guizhou, a bio-pretreatment followed by carbon-in-pulp (CIP) cyanide leaching process was used. Various methods were used to detect the low-grade gold in the concentrate; however, only time-of-flight secondary-ion mass spectrometry (TOF-SIMS) was successful. With bio-pretreatment, the gold recovery rate increased by approximately 70.16% compared with that obtained by direct cyanide leaching of the concentrate. Various attempts were made to increase the final gold recovery rate. However, approximately 20wt% of the gold was non-extractable. To determine the nature of this non-extractable gold, mineralogy liberation analysis (MLA), formation of secondary product during the bio-pretreatment, and the preg-robbing capacity of the carbonaceous matter in the ore were investigated. The results indicated that at least four factors affected the gold recovery rate: gold occurrence, tight junctions of gold-bearing pyrite with gangue minerals, jarosite coating of the ore, and the carbonaceous matter content.

Real-Time Optimization of Gold Cyanidation Leaching Process in a Two-Layer Control Architecture Integrating Self-Optimizing Control and Modifier Adaptation

The gold cyanidation leaching process (GCLP) has been prevalent in the hydrometallurgical industry. To better control and optimize the plant operation, mechanistic models have been established which capture the physical behaviors of the GCLP. However, due to various disturbances and uncertainties, an optimized operation based on the nominal model is practically suboptimal. To perform real-time optimization (RTO) of the GCLP, this paper proposes a two-layer control architecture integrating the self-optimizing control (SOC) and modifier adaptation (MA), both of which are useful RTO approaches with distinct advantages. In the lower layer of the proposed control system, the SOC is implemented with measurement combinations as the controlled variables that are tracked at optimally insensitive setpoints to account for parametric disturbances. In the upper layer, the setpoints of self-optimizing controlled variables are further optimized in a tailored MA framework, such that the structural plant–model mismatch is...

A selective process for extracting antimony from refractory gold ore

To avoid the adverse effects of antimony on the cyanide leaching process used for the recovery of gold from refractory gold ore, a cleaner production process was proposed that would selectively remove antimony as sodium pyroantimonate. The process included three steps: 1) leaching of antimony from the refractory gold ore with sodium sulfide solution; 2) pressure oxidation of the leaching solution containing sodium thioantimonite, transforming it to sodium pyroantimonate; and 3) concentration/crystallization to recover the sodium thiosulfate byproduct from the oxidized solution. The leaching recoveries of antimony, gold, and arsenic in the first step were 96.64%, 1.44%, and 0.41%, respectively. The precipitation ratio of antimony exceeded 99.80% during the second step. The synthesized sodium pyroantimonate product exhibited a regular tetragonal morphology. The purity of the sodium thiosulfate byproduct obtained during the third step reached 98.0%.