Insight into Aluminum Leaching with Microwave from Peat Clay: A Comparative Kinetic Study of SC and BIC Models

Aluminum oxide in peat clay has the potential to be used as a catalyst, coagulant, and adsorbent for the water treatment process. The usefulness of aluminum oxide in peat clay is enhanced by the leaching process. Aluminum was leached from peat clay in a variety of microwave power, HCl concentrations, and particle size. The effect of the microwave leaching parameters on the aluminum leaching rate was observed. The shrinking core (SC) model used in microwave-assisted leaching was assumed a pseudo steady state with chemical reactions. Effective diffusivity (De), mass transfer coefficient (kc), and reaction rate constants (k) are used as fitting parameters. The best fitting parameters De, kc , and k obtained 0.0049 cm2/s, 2.49 cm/s, and 10.5 cm/s, respectively. The comparison of experimental data and model calculations shown that the SC model can describe experimental data well for all microwave-assisted leaching conditions. Precious information on the results of this research can be given for the goal of the scaling-up and design of the microwave assisted leaching process.

This study was aimed to increase granite's silica content using the leaching process with HCl concentration variation. The granite used in this study came from Lematang, South Lampung. This study aims to determine the effect of variations in HCl concentration, particle size, and rotational speed on the crystalline phase and chemical elements formed in the silica product produced from granite. The HCl concentration variations were 6.0 M, 7.2 M, 8.4 M, and 9.6 M, the variation in particle size used was 270 and 400 mesh. Variations in rotational speed during leaching were 500 and 750 rpm. Granite powder was calcined at 1000 ºC for 2 hours. Characterization was performed using X-Ray Fluorescence (XRF), X-Ray Diffraction (XRD), and Inductively Coupled Plasma-Optical Emission Spectroscopy (ICP- OES). The results showed that the silica content increased with increasing HCl concentration, the finer the particle size, and the higher the rotational speed. XRF analysis showed that the silica with the highest purity was leached with 9.6 HCl with a particle size of 400 mesh and a rotational speed of of 750 rpm, which was 73.49%. Based on the results above, by leaching using HCl, the Si content can increase from before. The XRD diffractogram showed that the granite powder formed the Quartz phase.

Aim: This study investigates the dissolution of tantalite mineral from granitic pegmatite in Okpella, Northern Edo State, Nigeria. Study Design: Elemental and mineral composition analysis of tantalite ore sample from Okpella was carried out using X-ray fluorescence and X-ray diffraction. Response Surface Methodology (RSM) and the shrinking core model were used in designing the study while the effects of temperature, stirring speed, particle diameter, and mixed acids concentrations were investigated in the dissolution rates of the mineral. Duration of Study: 50 experimental runs were designed using RSM Central Composite Design (CCD) to optimize variables including HF concentration (1-8 M), H2SO4 concentration (0.5-3 M), temperature (32-82°C), stirring speed (0-500 rpm), and particle size (0.1-0.3 mm), with a constant contact time of 240 minutes. Methodology: Pulverized tantalite samples (0.1-0.3 mm) were reacted with varying concentrations of hydrofluoric and sulphuric acids (1-8 M and 0.5-3.0 M, respectively) for 240 minutes, with stirring speeds between 0-500 rpm and temperatures from 32 to 82°C. The mixture was stirred in a water bath with 50 ml of mixed acids solution and 2 g of ore. After the reaction, the solution was decanted, and the residual ore was washed, dried at 60 °C, and weighed. The difference between the initial and final weights indicated the amount of undissolved tantalite ore. Results: Ore characterization results revealed high concentration of tantalum (34.17%), iron (12.55%), niobium (8.38%), and titanium (6.01%), with other elements present in smaller amounts. Optimal conditions were found to be 8 M HF, 0.5 M H2SO4, 82°C, 500 rpm stirring speed, and 0.1 mm particle size, resulting in 97.28% dissolution of tantalite ore. Regression analysis demonstrated model robustness with an F-value of 16.70 and a P-value of 0.0001, indicating HF concentration and stirring speed as the most impactful factors. The model’s R² value of 0.9201 and adjusted R² of 0.8650 confirm its predictive accuracy. Analysis using the shrinking sphere model showed that film diffusion control is the primary limiting step with t/τ=0.999, while reaction control resulted in slightly lower conversion with t/τ=0.973, highlighting film diffusion as the main constraint but with high conversion efficiency. Conclusion: The findings from this investigation not only reveal the dissolution of tantalite ore through a detailed experimental approach, identifying optimal conditions -8 M HF, 0.5 M H2SO4, 82 oC, 500 rpm stirring speed and 0.1 mm particle size- that achieve a 97.28% dissolution, but they also enhance our understanding of mineral processing. These understanding are crucial for mineral dissolution up scaling technologies in industrial applications, which will potentially leads to a more efficient extraction method that could significantly reduce costs and environmental impacts in the mining sector. This research could drive advancements in sustainable resource recovery and contribute to sourcing of critical minerals.

Nickel laterite ore contains oxide of iron, aluminum or both with nickel, cobalt and chromium which can be leached out using hydrometallurgical process. For the purpose of meeting the world’s increasing demand of nickel, there is a need to invent environmentally friendly process to efficiently leach nickel. This experiment used nickel laterite ore obtained from Pomalaa, South Sulawesi. The leaching agent is metabolic citric acid produced by Aspergillus niger under optimum condition. Leaching process was done in three-necked flask in atmospheric temperature and constant stirring speed of 200 rpm. The variable examined in the experiment was pulp density and particle size of nickel laterite ore. Samples were taken at 3, 7, 10, 14, and 17 minutes and then filtered and diluted to be analyzed using ICP-AES. The result of the experiment showed the maximum recovery of metals increase with the decrease of the pulp density. The maximum recovery for varying pulp density were at 5% solid/liquid ratio and the recovery were Ni at 1.63%, Al at 0.47%, Fe at 0.23% and Mg at 1.09%. The effect of particle size on leaching process showed that the leaching process follows the shrinking core model. The maximum recovery of metals at particle size were at 100-120 mesh with Ni at 1.37%, Fe at 0.10%, Al at 0.72% and Mg at 0.62%.

Minerals containing TiO2 are common in Indonesia, such as ilmenite in iron sand deposits scattered along the country's coasts. Ilmenite is an important source of titanium. One method for making TiO2 from ilmenite is by solubilizing both the Fe and Ti elements in HCl and then immediately hydrolyze the Ti. The leaching of low-grade ilmenite (ground to 0.177-0.149 mm) is studied kinetically by HCl in a stirred reactor. The research was conducted using the caustic fusion method followed by HCl leaching. The leaching reaction kinetics at the optimum conditions are analyzed using response surface methodology (RSM) with a second-order polynomial equation model and SSE with the shrinking core model (SCM). The results showed that HCl concentration and leaching time were directly proportional to the leached titanium concentration. In contrast, the leaching temperature was inversely proportional. The optimum operating conditions were obtained at a temperature of 30 °C, 9 M HCl, and 120 min of leaching time. The shrinking core model is a better representation of the kinetics than RSM with a second-order polynomial equation model. Based on SCM, the rate of the leaching reaction of titanium from low-grade ilmenite is controlled by diffusion through the ash layer.

Most of kinetics studies related to leaching process used shrinking core model to describe physical phenomena of the process. Generally, the model was developed in connection with transport and/or reaction of reactant components. In this study, commonly used internal diffusion controlled shrinking core model was evaluated for leaching process of Pomalaa nickel laterite using citric acid as leachant. Particle size was varied at 60-70, 100-120, -200 meshes, while the operating temperature was kept constant at 358 K, citric acid concentration at 0.1 M, pulp density at 20% w/v and the leaching time was for 120 minutes. Simulation results showed that the shrinking core model was inadequate to closely approach the experimental data. Meanwhile, the experimental data indicated that the leaching process was determined by the mobility of product molecules in the ash layer pores. In case of leaching resulting large product molecules, a mathematical model involving steps of reaction and product diffusion might be appropriate to develop.

Dissolution behavior and kinetics of copper slag under oxidative conditions

Considering the recent focus of the Nigeria Government to grow and develop the nation’s economy through the solid minerals sector reform, this study has been devoted to the kinetics of a Nigerian goethite ore by hydrochloric acid leaching for improved iron and steel industries applications. This study was performed in three different phases. In the first phase, acidic leaching of iron from a goethite ore was examined and the influence of the operating variables including: HCl concentration, leaching temperature, stirring speed and particle sizes was examined experimentally. The optimum condition was found to be HCl concentration of 1.81M, temperature of 80°C, 200 rpm stirring speed and particle size 0.09 μm for iron in the range of investigated parameters. Under those conditions, the highest iron recovery was obtained to be 95.67 %. In the second phase, the dissolution kinetics of iron was evaluated by the shrinking core models. The finding reveals that diffusion through the fluid was the leaching kinetics rate controlling step of the iron. The activation energy (Ea) was found to be 14.54 kJmol-1 for iron. Equation representing the leaching kinetic of iron was achieved to be 1−2/3α - (1 − x)2/3 = 0.7272 × e−38.29/8.314×T × t. The final stage of the experiment was carried out by characterizing the leached residues by X-ray diffractometer (XRD) and scanning electron microscopy (SEM), the result showed majorly the presence of rutile (TiO2), anglesite (PbSO4), and traces of iron-silicate face like pyrite (FeS), quartz (SiO2).
 Keywords: kinetics modelling, leaching, low-grade, recovery, shrinking core

The aluminum (Al) leaching kinetics from peat clay was investigated using various acid concentrations 1 M to 6 M, particle sizes +70-120 mesh to +200-325 mesh and temperatures 30 °C to 90 °C. They all have significant effects on aluminum leaching process. The Al leaching recovery was best found to be 91.3 % at 4 M hydrochloric acid (HCl), using a particle size of +200-325 mesh with solid/liquid of 0.02 g·ml-1. Leaching kinetic study was applied to the two rate equations proposed that is acid diffusion via product layer and surface chemical reaction using the shrinking core (SC) model to analyze the leaching data. The product layer diffusion is controlling Al leaching process for one-stage model, while for two-stage model, it was controlled by surface chemical reaction. The activation energy in the two rate controlling step was 82.79 kJ mol-1 and 27.08 kJ mol-1, respectively.

The recovery of metals from discarded mobile phones has been of interest due to its environmental and economic benefits. This work presents a simple and effective approach for leaching copper (Cu) from the printed circuit boards of discarded mobile phones by combining ultrasound and ozone approaches. The X-ray diffraction (XRD) technique and Fourier-transform infrared spectroscopy (FT-IR) were used to characterize the solid phases, and inductively coupled plasma optical emission spectrometry (ICP-OES) was utilized to determine the concentration of metals in the liquid phases. The effects of several influential parameters, including ultrasound, ozone dose, HCl concentration, liquid/solid ratio, temperature, and reaction time on the leaching efficiency were investigated. The results showed that the optimal conditions for Cu leaching included an ozone dose of 700 mg/h, HCl concentration of 3.0 M, liquid/solid ratio of 8, and temperature of 333 K. Under optimal conditions, about 99% of Cu was leached after 180 min. The shrinking core model was used to analyze the kinetics of the Cu leaching process, and the results showed that the surface chemical reaction governs this process. The activation energy of the leaching reaction, calculated using Two-Point form of the Arrhenius equation, was 10.852 kJ mol−1.

First stage of the hydrometallurgical production of antimony is leaching of the raw material that contains antimonybearing mineral.The raw material can be ore or concentrate.Leaching can be carried out either in alkaline (Na 2 S+NaOH; NaOH) or acid (HCl; H 2 SO 4 ; HF) solutions.In order to achieve good antimony recovery it is essential to leach the raw material under optimum conditions.Kinetics of the reaction between particulate stibnite and mixed Na 2 S + NaOH solutions were studied.The effects of concentrations of Na 2 S and NaOH, temperature, particle size and liquid-to-solid ratio were investigated.It was observed that the rate of leaching of stibnite: a) increased with an increase in both Na 2 S and NaOH concentration (from 0.5 wt.% to 2.0 wt.%), and temperature (from 292 K to 327 K); b) reached its maximum at Na 2 S: NaOH weight ratio equal to 1:1; c) decreased with an increase in particle size (from 40 μm to 500 μm) and L/S ratio (from 10 to 100).The results are presented in terms of the shrinking (nonreacted) core model and shrinking porous-particle model.Apparent activation energy is approximately 44 kJ mol -1 and the apparent reaction order for Na 2 S varies from 1.4 to 1.7.Calculated values of the kinetic parameters indicate that the leaching process is controlled by both intrinsic chemical reaction between Sb 2 S 3 and Na 2 S at the liquid/solid interface, and pore diffusion.

Kinetic mechanism of aluminum removal from diamond wire saw powder in HCl solution.

The leaching laboratory experiment uses the artificial neural network (ANN) to predict and evaluate copper and cobalt recovery. This study aimed to evaluate the efficacy of using the shrinking core model in conjunction with an artificial neural network (ANN) as part of a machine learning strategy to improve the leaching process of cobalt (II) and copper (II). The numerous factors in the leaching process, such as acid concentration, leaching time, temperature, soil-to-solution ratio, and stirring speed, are adjusted using an ANN with several layers, feed-forward, and back-propagation learning methods. These variables are in charge of the high cobalt recovery during the reduced sulfuric acid leaching procedure. The ANN algorithm has 10 hidden layers, 5 input variables describing the leaching parameters, and two neurons as output layers corresponding to copper and cobalt leaching recovery. The optimum conditions were found to be acid concentration of 100 g/L, leaching duration 120 min, temperature 55 °C, soil-to-solution ratio of 1:40 g/mL, and stirring speed 300 rpm. The optimized trained neural networks tested, trained, and validated steps are represented by R 2 values of 0.94, 0.99, 0.97, and 0.97, respectively, equating to 97.5% copper recovery and 95.4% cobalt recovery.

Based on physical evidence and observation of the acid dependency of the leaching process, a shrinking core model seems to be an appropriate model for cement stabilized waste. It is argued that for cement stabilized wastes, the bulk diffusion model is likely to be in error. Recent findings will be used to support the concept of a shrinking core model. To be able to deal with varying acidities in the leachant, the concept of exposure will be introduced. The model will be derived for a flat surface to illustrate that, as in the ANS 16.1 model, a parabolic leaching behavior can be obtained. Some other characteristics of the model are indicated. It is shown that the shrinking core model, using the concept of exposure, adequately takes into account the physical observations as well as adequately correlates the leaching data for a model specimen contaminated with lead. The findings indicate that kinetic factors may play a role in the release of metals. Their relevance for the interpretation of TCLP results is indicated.

The dissolution kinetics of hemimorphite with low sulfuric acid solution was investigated at high temperature. The dissolution rate of zinc was obtained as a function of dissolution time under the experimental conditions where the effects of sulfuric acid concentration, temperature, and particle size were studied. The results showed that zinc extraction increased with an increase in temperature and sulfuric acid concentration and with a decrease in particle size. A mathematical model able to describe the process kinetics was developed from the shrinking core model, considering the change of the sulfuric acid concentration during dissolution. It was found that the dissolution process followed a shrinking core model with “ash” layer diffusion as the main rate-controlling step. This finding was supported with a linear relationship between the apparent rate constant and the reciprocal of squared particle radius. The reaction order with respect to sulfuric acid concentration was determined to be 0.7993. The apparent activation energy for the dissolution process was determined to be 44.9 kJ/mol in the temperature range of 373 K to 413 K (100 °C to 140 °C). Based on the shrinking core model, the following equation was established: $$ 1.21\ln \left( {1 - 0.83x} \right) - \left[ {1.02\ln \frac{{0.35 + \left( {1 - x} \right)^{{{2 \mathord{\left/ {\vphantom {2 3}} \right. \kern-0pt} 3}}} - 0.59\left( {1 - x} \right)^{{{1 \mathord{\left/ {\vphantom {1 3}} \right. \kern-0pt} 3}}} }}{{0.35 + \left( {1 - x} \right)^{{{2 \mathord{\left/ {\vphantom {2 3}} \right. \kern-0pt} 3}}} + 1.18\left( {1 - x} \right)^{{{1 \mathord{\left/ {\vphantom {1 3}} \right. \kern-0pt} 3}}} }} + 3.52\arctan \left( {1.96\left( {1 - x} \right)^{{{1 \mathord{\left/ {\vphantom {1 3}} \right. \kern-0pt} 3}}} - 0.58} \right)} \right] + 2.06 = 42,192.59{\text{e}}^{{ - \frac{44,900}{{{\text{R}}T}}}} t. $$