Current Physical Chemistry - Volume 10, Issue 2, 2020

Background: Being by-products of non-ferrous metallurgy, slags contain fayalite (Fe2SiO4) as the major component. Since hydrometallurgical methods are considered as the most promising for processing such material to obtain valuable metals, increasing the leachability of fayalite in sulfuric acid as a widely used leaching agent is an important task. Objective: The present work was devoted to increasing the reactivity of fayalite by using mechanical activation. Method: Fayalite, synthesized with the use of powders of metallic Fe, Fe2O3, and SiO2, was subjected to mechanical activation in the planetary ball mill at 400 rpm with a ball/powder ratio of 5 for 45 minutes. Then, activated and non-activated fayalite samples were subjected to sulfuric acid leaching. Before leaching, solid samples were characterized by XRD and Dynamic Light Scattering (DLS). Quantitative analysis of Fe and Si in the leachate was determined by Inductively Coupled Plasma-Atomic Emission Spectroscopy. Results: Mechanical activation led to partial amorphization of the initial fayalite sample. It was found that the leaching rate constants of the treated samples in sulfuric acid solution (50-80 gxL-1) at 298, 338, and 368 K increased and the activation energy of the leaching process decreased, i.e. mechanical activation enhances the reactivity of fayalite in H2SO4 solution. Conclusion: Mechanical activation can be applied to improve fayalite leachability in sulfuric acid solution. The results obtained can be used in the development of methods for leaching slag of non-ferrous metallurgy, in particular, copper smelter slags, the major component of which is fayalite.

Background: Turkey is approximately 72% of the world’s boron sources. Colemanite, tincal, ulexite and pandermite are among the most significant in Turkey. Boron compounds and minerals are widely used in many industrial fields. Objective: The main purpose of this study was to investigate the control of impurities in the boric acid production process using colemanite by carrying out the reaction with a mixture of CO2 and SO2 - water, and determining the appropriate process conditions to develop a new process as an alternative to the use of sulfuric acid. Due to worrying environmental problems, intensive studies are being carried out globally to reduce the amount of CO2 and SO2 gases released to the atmosphere. Methods: The Taguchi method is an experimental design method that minimizes the product and process variability by selecting the most appropriate combination of the levels of controllable factors compared to uncontrollable factors. Results: It was evaluated the effects of parameters such as reaction temperature, solid-to liquid ratio, SO2/CO2 gas flow rate, particle size, stirring speed and reaction time. The optimum conditions determined to be reaction temperature of 45°C; a solid–liquid ratio of 0.083 g.mL−1; an SO2/CO2 ratio of 2/2 mL.s−1; a particle size of -0.354+0 .210 mm; a mixing speed of 750 rpm and a reaction time of 20 min. Conclusion: Under optimum operating conditions, 96.8% of colemanite was dissolved. It is thought that the industrial application of this study will have positive effects on the greenhouse effect by contributing to the reduction of CO2 and SO2 emissions that cause global warming.

Background: Olivine is an important industrial raw material especially for metallurgical applications like foundry sand, refractory, slag conditioning, etc. Loss On Ignition (LOI) value (>1%) is the main specification of olivine ore/concentrate for those areas together with the chemical specifications. Objective: This flotation study was conducted in natural pH condition with Na-oleate as collector to clarify the effect of frother (MIBC) dosage on the LOI value of olivine concentrate. Methods: Characterization of ore sample for this study was made by XRD, XRF and petrographic analyses. Lizardite, a serpentine group mineral, was found to be a hydrated soft fraction of ore sample in addition to hard olivine and pyroxene minerals constituting ore. Results: Finely ground soft lizardite adversely affected the olivine flotation in a way of entraining mechanically into concentrate. LOI value of concentrate was observed mainly to be froth volume depended issue, and therefore, mainly water recovery dependent. LOI value increased proportionally with water recovery at longer flotation time and MIBC dosages indicating the entrainment of lizardite as the suspending hydrophilic component of water phase. Certain rate of the hydrated lizardite mineral was thought to be recovered via hydrophobization, which was clearly seen especially at the initial stages of flotation period in the presence of excess frother. This experimental finding was attributed to similar chemical composition of minerals constituting ore, and accidental activation of lizardite. Conclusion: Lizardite recovery in froth was explained with accidental activation and/or weak attachment of locked particles onto froth bubble although main recovery mechanism was determined to be mechanical entrainment. Olivine concentrate obeying the specifications of metallurgical applications could be obtained at suitable MIBC dosage and flotation time.

Aims: In this study, microwave interaction of magnetite ore concentrate which was mixed with carbonized biomass waste and divided into different grain sizes, was studied. Materials and Methods: The mixture consisting of magnetite concentrate and carbonized product was pelletized by the addition of molasses and jelly as binders. The pellets prepared with various particle size powders were subjected to microwave treatment at different times. Results: Temperature of the pellet produced with powders between -212 +150 μm grain sizes and -45 μm were measured as 837.5°C at 304th second and 945.9°C at 210th second respectively. Conclusion: Although there was a large temperature difference between the core and the surface of the pellet, a high degree of metallization was observed in these samples.

Aim: In this work, the effect of milling time on the mechanical alloying of the mixture containing the magnetite concentrate and biomass waste was investigated. Materials and Methods: The ore’s grade consisting of hematite and magnetite minerals was increased from 49.87% Fe to 67.29% Fe using the low intensity wet magnetic separator. Biomass waste which was supplied from ÇAYKUR black tea facilities, used as a carbon source was subjected to carbonization processes at 800°C for 1440 min. After the carbonization process, the carbon and sulphur contents of the biomass were measured as 94.68% and 0.03%, respectively. For the mechanical alloying process, a mixture consisting of magnetite concentrate with a grain size of -45 μm and biomass which was added two times the amount of carbon required for the reduction of magnetite to metallic iron was used. Result: After the mechanical alloying process which was carried out at different times, it was observed in the particle size analysis that the particle size of 90% of the mixture was reduced to about 4 μm. In SEM (Scanning Electron Microscopy) images, cube-like particles along with the spherical particles were observed depending on the mechanical alloying times. After 45 minutes of alloying, it was observed that the carbonized product milled together with magnetite concentrate was partially integrated into the crystal structure. Conclusion: The carbonized tea plant waste milled together with magnetite concentrate was partially integrated into the crystal structure. And the mechanical alloying provide to increase in the specific surface area in parallel with the grain size decrease in the study. Thus, in the later stage of the study, the milled powder acquired more ability to react.

Background: Gypsum plaster is one of the most important building materials. The use of gypsum plasters is very common due to their many advantages. The drying process is an important stage in the production of gypsum materials and applications. Modelling of drying phenomenon can benefit drying technology. Recently, Particle Swarm Optimization (PSO) technique has been used to obtain optimum model equations for drying processes. Objective: The aim of this study was to determine a new modeling approach to infrared drying of machine plaster by using PSO. Methods: Experimental studies supplied by previous work in the literature have been performed by a laboratory scale infrared dryer in the temperature range of 50-70°C and at atmospheric conditions. Experimental moisture ratio values were compared with various mathematical model equations developed for the drying process by using Particle Swarm Optimization (PSO) technique. Results: Fitting tests indicate that the results obtained from the PSO technique are better than those of the previous study because of lower χ2, RMSE, and RSS values. The best model equation was the model equation based on the Newton drying equation existing in the previous study. However, the model equation derived by Modified Page has been determined as the most compatible model with the experimental data. Conclusion: It can be said that PSO is successively and reliably used to predict or optimize the experimental data of drying phenomena.

Background: Hydroxyapatite, which is naturally and synthetically available, is often used as a biomaterial because of its similarity to bone. Aim: In this study, Natural hydroxyapatite powder, synthesized from sheep bone, and synthetic hydroxyapatite were used as matrix. Materials and Methods: Hybrid bio-ceramic composites were obtained by adding 5 wt. % expanded perlite-TiO2-ZrO2-MgO-P2O5 to both matrixes. The bio-ceramic materials which were mixed with mechanical mixer for 30 minutes were pressed with hydraulic press under 25 MPa pressure and sintered at 900°C for 1 hour. Density, micro-hardness, X-Ray Diffraction (XRD), Scanning Electron Microscope (SEM) and Energy Dispersive Spectroscopy (EDS) analysis were performed to determine characteristics of the samples. Result: As a result, it was identified that the micro-hardness of natural hydroxyapatite was higher. In addition, the increase in micro-hardness values of ZrO2-reinforced samples was higher than the TiO2-reinforced samples. Conclusion: Hydroxyapatite, calcium silicate, calcium phosphate structures were observed in XRD analysis. Micro-pores were observed in TiO2-reinforced samples while more dense structures were observed in ZrO2-reinforced samples.

Objective: In this study, the extraction of oil from Pistacia terebinthus L’s seeds grown in Elazig-TURKEY and called menengic in domestic region was investigated. Crude oil content of the seeds obtained from this region was determined as approximately 47% (w/w). Method: Effects of the parameters such as extraction time, temperature, seeds/solvent ratio (dosage), the particle size of seeds and type of solvent were examined on the oil extraction yield. In this context, it has concluded that up to a certain point, the extraction time has increased the yield of oil extracted. But the extraction temperature showed activity as depending on the solvent type. Results: As expected, it has been observed that the yield of oil has decreased depending on the increase in particle size and dosage as well. The mathematical model obtained by solving Fick's second law under the appropriate boundary and initial conditions were used to calculate diffusion coefficients for the extraction process. Diffusion coefficients for the seeds with a particle size of 0.55 mm were found to be between 1.15x10-11 and 1.86x10-11 m2s-1. To compare the extraction yield of Pistacia terebinthus L’s seeds with that of sunflower at the same conditions, the diffusion coefficients of sunflower seeds were calculated in the range of 9.11x10-12 and 1.13x10-11 m2s-1. Conclusion: These figures show that the diffusion coefficients calculated for both oily seeds are nearly equivalent to each other. The fatty acid composition of extracted oil from Pistacia terebinthus L’s seeds was determined by GC-FID. The GC-FID results showed that oleic, linoleic (ω-6) and palmitic acid were main fatty acids in the oil obtained from menengic seeds.

Background: The calorific value is the most important and effective factors of lignites in terms of energy resources. Humidity, ash content, volatile matter and sulfur content are the main factors affecting lignite's calorific values. Objective: Determination of calorific value is a process that takes time and cost for businesses. Therefore, estimating the calorific value from the developed models by using other parameters will benefit enterprises in term of time, cost and labor. Method: In this study calorific values were estimated by using artificial neural network and multiple regression models by using lignite data of 30 different regions. As input parameters, humidity, ash content and volatile matter values are used. In addition, the mean absolute percentage error and the significance coefficient values were determined. Results: Mean absolute percentage error values were found to be below 10%. There is a strong relationship between calorific values and other properties (R2> 90). Conclusion: As a result, artificial neural network and multiple regression models proposed in this study was shown to successfully estimate the calorific value of lignites without performing laboratory analyses.