Current Physical Chemistry

It is a pleasure for me to launch this special issue entitled “Contribution of Mining, Chemical and Metallurgical Engineering to Science” for Current Physical Chemistry. It is also my honor to become the Guest Editor again for the special issue of the prestigious Journal Current Physical Chemistry and thanks to the publisher along with all the reviewers and the Editorial Board Members for their contributions and a well-done job. The first study regarding the effect of mechanical activation on the leachability of fayalite in sulfuric acid solution by Nadirov and Mussapyrova [1] represents how activation energy requirement is decreasing after mechanical activation of fayalite that occurs in slag. The second study of this special issue is on the statistical evaluation of colemanite dissolution conducted by Ekinci et al. In this study, Taguchi method was used statistically for an orthogonal array consisting of six factors in five levels for the optimization of dissolution parameters such as reaction temperature, solid-to liquid ratio, SO2/CO2 gas flow rate, particle size, stirring speed and reaction time [2]. The third paper by Güler and Polat presents the Effect of MIBC Dosage on the Mitigation of Lizardite Recovery. 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 chemical specifications. This flotation study was conducted on natural pH conditions with Na-oleate as a collector to clarify the effect of frother (MIBC) dosage on the LOI value of olivine concentrate [3]. In the next study, microwave interaction of magnetite ore concentrate which was mixed with the carbonized biomass waste and divided into different grain sizes, was studied by Öztürk et al. The study put forth the effect that how different particle sizes of magnetite concentrate aim at reduction in microwave oven at the laboratory scale [4]. The fifth study by the same authors represents mechanical alloying of magnetite concentrate in the presence of biochar used as a reducer. In this study, biomass waste was used as a source of carbon for the reduction of magnetite to metallic iron under mechanical conditions. Authors noticed that after 45 minutes of alloying, the carbonized product milled together with magnetite concentrate was partially integrated into the crystal structure [5]. The sixth study gives information regarding a new modeling approach to infrared drying of machine plaster by Kalender et al. The best model equation was the model 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 [6]. The next study represents the Characterization of Hybrid Bio-ceramic Hydroxyapatites Reinforced by Expanded Perlite-TiO2-ZrO2-MgO-P2O5 by Karip and Muratoğlu. In this study, hydroxyapatite, which is naturally and synthetically available, is often used as a biomaterial because of its similarity to the bone. In this study, Natural hydroxyapatite powder, synthesized from sheep bone, and synthetic hydroxyapatite were used as matrix. Hydroxyapatite, calcium silicate, calcium phosphate structures were observed in XRD analysis. Micro-pores were observed in TiO2-reinforced samples while denser structures were observed in ZrO2-reinforced samples [7]. The eighth study included is by Kaya and Özer. In this study, the extraction of oil from Pistacia terebinthus L’s seeds grown in Elazig-Turkey and called menengiç in the domestic region was investigated. 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. Mathematical model obtained by solving Fick's second law under the appropriate boundary and initial conditions was used to calculate diffusion coefficients for the extraction process. Also, the diffusion coefficients calculated for both oily seeds were nearly equivalent to each other [8]. In the last study, the estimation of calorific values of some Turkish Lignites by artificial neural network and multiple regressions was investigated by Özdemir and Sarıcı. Calorific values were estimated by using artificial neural network and multiple regression model employing lignite data of 30 different regions. As input parameters, humidity, ash content and volatile matter values were used. In addition, the Mean Absolute Percentage Error (MAPE) and the significance coefficient (R2) values were determined. MAPE values were found to be below 10% [9]. I hope these studies will be useful for researchers.