By developing technologies, spent lithium-ion batteries (LIBs) are considered a great source of nickel-cobalt ions to fabricate metal sulfide nanoparticles. However, the presence of unnecessary ions such as manganese and lithium may hamper the formation of pure metal sulfide nanostructures where the utilization of proper ligand(s) can be very critical. For this reason, the present study initially introduces a promising and cost-effective acidic leaching followed by precipitation and thermal treatment (~250 °C, 1 h) processes to fabricate pure NiS nanopowders from the LIBs, while considering potassium amyl xanthate as the precipitating agent. The produced nanoparticle’s size and structure were characterized by commonly used and advanced analytical techniques such as X-ray diffraction (XRD), scanning electron microscopy (SEM), transmission electron microscopy (TEM) and photon correlation spectroscopy (PCS), and inductively coupled plasma optical emission spectrometry (ICP-OES). The elemental distributions and functional groups were analyzed through energy dispersive X-ray spectroscopy (EDS) and Fourier-transform infrared spectroscopy (FTIR) methods. The characteristic analyses of the spherical-like NiS particles showed a mean particle size of 61 ± 2 nm (by TEM) and 64 nm (through the PCS method) with high purities approved via XRD and EDS analyses. Moreover, comparing the obtained XRD data with the standard ones showed a perfect match with the hexagonal structure of the NiS phase. We finally concluded that such a presented approach is very practical and efficient for converting the LIBs to an extremely valuable product. Future studies are suggested for the fundamental conceptualization of the processes.

In open-pit mines, the blast operation should be effectively optimized, leading to minimization of production costs through the application of specific technical specifications. However, there is inadequate information in the literature to link blasting to comminution stages. To this end, the effective parameters for the performance of mining unit operations were scrutinized in this work. In this regard, the rock fragmentation distribution (RFD) caused by blasting was considered the main determinative criterion for providing the optimum conditions for the blasting operation at Sarcheshmeh copper mine. By carrying out a statistical analysis of the experimental data, operational parameters affecting the blasting were optimized. The relationship between parameters was obtained using the technique of regression and in accordance with the evaluation criterion under which correlation coefficient (R²) was used to determine the best fitting model. A high correlation coefficient of the loading cycle of the machine’s bucket $\left({\mathrm{C}}_{\mathrm{l}}\right)$ with the independent variables showed that the C₁ was more affected by the RFD, as well as the dimensions of the blast block. Because of the wide variations in the nature and structure of rock mass in different mines, in each case, sufficient data should be collected, and these relationships should be analyzed statistically for each individual mine showing wide ranges of fractures and cracks. Therefore, due to these wide variations of ore characteristics, with the current data it seems very difficult to quickly find a significant operational relationship between downstream processes such as crushing efficiency and blasting operations. Therefore, the focus of this research was limited to the effective parameters for blast efficiency. According to the analysis of the data obtained from 20 blasts under different operating conditions, the diameter of the hole was 241.3 mm (such as blast number 20), the ratio of length to width of the explosive block was about 6 (average blasts with high fragmentation efficiency), and the best index of mining operations was 0.22 (such as blast number 20).

The dominant challenge of current copper beneficiation plants is the low recoverability of oxide copper-bearing minerals associated with sulfide type ones. Furthermore, applying commonly used conventional methodologies does not allow the interactional effects of critical parameters in the flotation processes to be investigated, which is mostly overlooked in the literature. To tackle this issue, the present paper aimed at characterizing the behavior of five key effective factors and their interactions in a sulfidized copper ore. In this context, dosage of collector (sodium di-ethydithiophosphate, 60–100 g/t), depressant (sodium silicate, 80–120 g/t) and frother (methyl isobutyl carbinol (MIBC), 6–10 g/t), pulp pH (7–11) and agitation rate (900–1300 rpm) were examined and statistically analyzed using response surface methodology. Flotation experiments were conducted in a Denver type agitated flotation cell at the rougher stage. The experimental results showed that increasing the pH (from 8 to 10) at low agitation rate (1000 rpm) enhanced the recovery from 80.36% to 85.22%, while at high agitation rate (1200 rpm), a slight declination occurred in the recovery. Meanwhile, increasing the collector dosage at a lower frother value (7 g/t), caused a reduction of about 4.44% in copper recovery owing to the interactions between factors, whereas at a higher frother level (9 g/t), the recovery was almost unchanged. The optimization process was also performed using the goal function approach, and maximum copper recovery of 92.75% was obtained using ~70 g/t collector, 110 g/t depressant, 7 g/t frother, pulp pH of 10 and 1000 rpm agitation rate.

Numerous studies have addressed the role of ultrasonication on floatability of minerals macroscopically. However, the impact of acoustic waves on the mineral hydrophobicity and its physicochemical aspects were entirely overlooked in the literature. This paper mainly investigates the impact of ultrasonic power and its time on the wettability and floatability of chalcopyrite, pyrite and quartz. For this purpose, contact angle and collectorless microflotation tests were implemented on the ultrasonic-pretreated and non-treated chalcopyrite, pyrite and quartz minerals. The ultrasonic process was carried out by a probe-type ultrasound (Sonopuls, 20 kHz and 60 W) at various ultrasonication time (0.5–30 min) and power (0–180 W) while the dissolved oxygen (DO), liquid temperature, conductivity (CD) and pH were continuously monitored. Comparative assessment of wettabilities in the presence of a constant low-powered (60 W) acoustic pre-treatment uncovered that surface of all three minerals became relatively hydrophilic. Meanwhile, increasing sonication intensity enhanced their hydrophilicities to some extent except for quartz at the highest power-level. This was mainly related to generation of hydroxyl radicals, iron-deficient chalcopyrite and elemental sulfur (for chalcopyrite), formation of OH and H radicals together with H₂O₂ (for pyrite) and creation of SiOH (silanol) groups and hydrogen bond with water dipoles (for quartz). Finally, it was also found that increasing sonication time led to enhancement of liquid temperature and conductivity but diminished pH and degree of dissolved oxygen, which indirectly influenced the mineral wettabilities and floatabilities. Although quartz and pyrite ultrasound-treated micro-flotation recoveries were lower than that of conventional ones, an optimum power-level of 60–90 W was identified for maximizing chalcopyrite recovery.

Coal beneficiation processes are often based on gravitational enrichment techniques. Therefore, various types of jigs are often used in this area. A number of factors determine the quality of the final product. Therefore, proper and systematic monitoring of such a process is necessary. The present work examined the effect of the hutch water amount and the amount of processed coal (system capacity) on the yield and ash grade in individual density–size fractions. A statistical method in the form of the Kruskal–Wallis test and the Friedman test was used to evaluate the process. These tests were proposed as universal and reliable alternatives to classical analysis of variance (ANOVA) analysis. The performed analysis allowed for the determination of what process conditions should be selected in order to obtain certain effects. Therefore, it allowed us to apply certain combinations of hutch water amount, system capacity and particle characteristics to maximize the expected effects. The application of statistical analysis methods in the form of Kruskal–Wallis and Friedman tests to evaluate process efficiency creates new possibilities to monitor and optimize the jigging process in both context of amount and quality of final product and is very important not only for mining enterprise but also from an environmental point of view.

This work aims at presenting an advanced simulation approach for a novel rhamnolipidic-based bioflotation process to remove chromium from wastewater. For this purpose, the significance of key influential operating variables including initial solution pH (2, 4, 6, 8, 10 and 12), rhamnolipid to chromium ratio (RL:Cr = 0.010, 0.025, 0.050, 0.075 and 0.100), reductant (Fe) to chromium ratio (Fe:Cr of 0.5, 1.0, 1.5, 2.0, 2.5, 3.0), and air flowrate (50, 100, 150, 200 and 250 mL/min) were investigated and evaluated using Analysis of Variance (ANOVA) method. The RL as both collector and frother was produced using a pure strain of Pseudomonas aeruginosa MA01 under specific conditions. The bioflotation tests were carried out within a bubbly regimed column cell with the dimensions of 60 × 5.70 × 0.1 cm. Four optimization techniques based on Artificial Neural Network (ANN) including Cuckoo, genetic, firefly and biogeography-based optimization algorithms were applied to 113 experiments to identify the optimum values of studied factors. The ANOVA results revealed that all four variables influence the bioflotation performance through a non-linear trend. Their influences, except for aeration rate, were found statistically significant (p-value < 0.05), and all parameters followed the normal distribution according to Anderson-Darlin (AD) criterion. Maximum chromium removal of about 98% was achieved at pH of 6, rhamnolipid to chromium ratio of 0.05, air flowrate of 150 mL/min, and Fe to Cr ratio of 1.0. Flotation kinetics study indicated that chromium bioflotation follows the first-order kinetic model with a rate of 0.023 sec⁻¹. According to the statistical assessment of the model accuracy, the firefly algorithm (FFA) with a structure of 4-9-1 yielded the highest level of reliability with the mean squared, root mean squared, percentage errors and correlation coefficient values of test-data of 0.0038, 0.0617, 3.08% and 96.92%, respectively. These values were evidences of the consistency of the well-structured ANN method to simulate the process.