Modeling of Co-Cu elution from clinoptilolite using neural network

The elution process for the removal of Co and Cu from clinoptilolite as an ion-exchanger was investigated using three parameters: bed volume, pH and contact time. The present paper study has shown quantitatively that acid concentration has a significant effect on the elution process..

Examination of flotation reagents suitable for nickel concentrator plant

Examination of flotation reagents suitable for a nickel concentrator plant was investigated using nickel sulphide ore. A number of different new reagents were examined for the best suit for the nickel concentrator plant. It was found that more nickel was found on the magnetic particles, which were assumed to be mostly pyrrhotite. A dosage of 50 g/t was found to be a suitable dose for the collector Betacol 380 AC and gave the best results, however, it was found to be expensive. Betacol 380 AB was found to be suitable at a dose of 75% g/t. There was no flotation improvement when depressants were used in conjunction with Betacol 380 AC. An activator (copper sulphate) was found to improve the grade of copper, nickel and iron meaning it activated pentlandite. The ions improved the flotability of sulfides at the normal process pH after grinding in steel mill

Thermodynamics of Cu (II) adsorption onto South African clinoptilolite from synthetic solution by ion exchange process.

The adsorption of Cu (II) ions from aqueous solution onto clinoptilolite from synthetic solutions by ion exchange was investigated. The effects of solution pH and temperature were examined. The Langmuir isotherm model was employed to calculate the different thermodynamics parameters. Thermodynamics studies revealed that the adsorption behavior of Cu (II) ions onto clinoptilolite was a spontaneous and endothermic process, resulting in higher adsorption capacities at higher temperatures

Kinetics study of ammonia removal from synthetic waste water

The aim of this study was to investigate ammonium exchange capacity of natural and activated clinoptilolite from Kwazulu-Natal Province, South Africa. X-ray fluorescence (XRF) analysis showed that the clinoptilolite contained exchangeable ions of sodium, potassium, calcium and magnesium. This analysis also confirmed that the zeolite sample had a high silicon composition compared to aluminium. Batch equilibrium studies were performed in an orbital shaker and the data fitted the Langmuir isotherm very well. The ammonium exchange capacity was found to increase with pH and temperature. Clinoptilolite functionalization with hydrochloric acid increased its ammonia uptake ability

The effect of leaching time and ammonia concentration on the atmospheric leaching of copper

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The effect of leaching time and ammonia concentration on the atmospheric leaching of copper

The effects of ammonia concentration and leaching time were investigated to determine the optimum leaching conditions. The experiments were conducted in a leaching cell submerged in a water bath, with ammonia concentrations of 1.5 M, 2.0 M, 2.5 M and 3.0 M and varying leaching time from 0 to 300 min. Ni-Cu matte containing 23% by mass Cu was used in this experimental study. Increase in the concentration of the lixiviant was found to increase recovery when leaching for 130 minutes, with a recovery of 32.86% Cu using 3 M solution of ammonia. An increase in the leaching time resulted in more copper being leached for all lixiviant concentrations. However, leaching with 2 M ammonia solution gave a higher yield of copper compared to higher concentrations. This anomaly could be a result of cementation; Cu is displaced by Ni as Ni is a more electronegative metal than Cu .It was found that at higher concentrations more nickel was extracted

Heavy metal ions removal from oil wastewater using highly enhanced Chitosan membrane technology: a response surface methodology study

This paper investigates the removal of heavy metal ions from oily wastewater using enhanced Chitosan Membrane. Cellulose and gelatin have been used successfully to modify chitosan. Fourier Transform Infrared (FTIR), Scanning Electron Microscopy (SEM), and X - Ray Diffraction (XRD) were used to characterize chitosan. We looked at the impacts of pH solution and conductivity. To eliminate the heavy metals, adsorption study was conducted. Results showed removal percentages higher than 90% especially when the initial pH is 7.50 and the volume of Hexane is 12 mL. Conductivities of wastewater were positive and negative depending on whether the medium is acidic and basic respectively and values higher than +260 mV and lower than –340 mV were observed. Experiments were designed employing Central Composite Design (CCD) of the Response Surface Methodology to examine the effects of experimental conditions (RSM). R2 values for analysis of variances of Cu2+, Fe2+, and Pb2+ were all almost the same at 0.99. The quadratic models appeared significant and adequate in evaluating the experimental results. The differences in experimental and projected % Removal values were negligible for all models. The 3D response surface plots that resulted permitted paired analysis of variable impacts on each response model

Neural Network for Modeling the Mechanical Properties of Gelatin-Cellulose Nanocrystals Hydrogel Membrane for Heavy Metal ions Removal from Wastewater

The mechanical properties of Gelatin-cellulose nanocrystals hydrogel membrane were investigated for the removal of heavy metal ions from wastewater. The membrane was characterized using Scanning Electron Microscopy (SEM) and Fourier Transform Infrared Spectroscopy (FTIR) analysis. Neural Network (NN) model was developed to predict the mechanical properties such as Young’s modulus, tensile strength, and elongation. The NN predicted results are very close to the experimental results with R2 = 0.99315. The predicted values were found to be in excellent agreement with the experimental data and the current model has a good learning precision and generalization. The results revealed that the developed model is very accurate

Steam extraction of essential oils : investigation of process parameters

M.Tech.Essential oils are volatile oils, generally odorous, which occur in certain plants or specified parts of plants, and are recovered by accepted procedures, such that the nature and composition of the product is, as nearly as practicable, unchanged by such procedures (ISO, 1968). The principal uses are as: flavouring agent, medicinal and aromatherapy application. Today, the essential oils are sought-after for innumerable applications starting from markers for plant identifications to bases for semi-synthesis of highly complex molecules. The extraction of highly delicate essential oils from plants remains a crucial step in all these applications. By using steam to mediate the extraction, it is possible to maintain mild conditions and effect superior extraction. In the current work, an integrated procedure for steam extraction followed by volatiles sampling and analysis from the leaves of the Eucalyptus tree was explored. There are two problems to overcome in the extraction from solid plant materials: that of releasing the essential oils from solid matrix and letting it diffuse out successfully in a manner that can be scaled-up to industrial volumes. Towards this end, the effect of different parameters, such as temperature, pressure and extraction time on the extraction yield was investigated and the experimental results show that all of these temperatures (90 °C, 97°C, and 99°C), were significant parameters affecting yield. Increase in yield was observed as pressure was increased and the use of high pressure (150 kPa) in steam extraction units permits much more rapid and complete distillation of essential oils over atmospheric pressure. The yield was calculated from the relation between the essential oil mass extracted and the raw material mass used in the extraction. The volatiles, Eucalyptus oil in vapour form released from the leaves were condensed and analyzed using Gas chromatography, and eight major components were found to be contained in this species. A mathematical model based on diffusion of essential oil from the leaves was developed. Using a numerical method, the best diffusion coefficient was established for different operating conditions by comparing the model concentration of oil remaining in the leaves with the experimental amount of oil recovered; hence minimizing the sum of squared errors. It was found that one cannot simply assume that the oil leached and recovered was the same as that originally present in the leaves. The initial mass of oil was determined by fitting the diffusion model to the data. An Arrhenius model was used to account for the effect of temperature. The resulting expression for the diffusion coefficient as a function of temperature can now be used to model the large scale extraction of the essential oils from Eucalyptus leaves

Application of neural network techniques to the ion-exchange process and prediction of abrasiveness characteristics of thermal coal

Abstract: The construction of a model for the prediction of process outputs is a valuable tool in the field of engineering. The models play an important role in the simulation and optimization of systems leading to the design of efficient and economical processes. Since 1943 neural network (NN) techniques have been considered as promising tools for use in simulation, prediction and modelling because of their simplicity. In this thesis a feed-forward neural network (FFNN) with back-propagation (BP) is used to test its effectiveness in modelling the ion-exchange process. The ion-exchange process has been widely employed in the removal of heavy metals from industrial wastewater. This process is a complex non-linear process involving many factors influencing the chemical process which is not well understood (the ions uptake mechanisms from the pregnant solution, the subsequent step being the elution). In order to improve the performance of the ion-exchange process, optimization and analysis of the process should be accomplished. Modelling and simulation are tools which can be used to achieve the objectives. The experimental design using analysis of variance (ANOVA) was chosen to compare to the NN techniques and for optimizing the effective input parameters (pH, temperature and initial concentration). The FFNN successfully tracked the non-linear behaviour of the ion-exchange process versus the input parameters with a mean square error (MSE), correlation coefficient (R) and mean square relative error (MSRE) of 0.102, 0.998 and 0.004, respectively. The results showed that the FFNN modelling techniques could effectively predict and simulate the highly complex system and non-linear process such as the ion exchange using activated zeolite...D.Tech. (Chemical Engineering