Valorization of pyrolysis oils recycled from waste car tires as potential collector in coal flotation: Production, characterization, and collecting mechanism.

The present research study investigates the performance of pyrolysis oils recycled from waste tires as a collector in coal flotation. Three different types of pyrolysis oils (namely, POT1, POT2, and POT3) were produced through a two-step pressure pyrolysis method followed by an oil rolling process. The characteristics of POTs were adjusted using various oil-modifying additives such as mineral salts and organic solvents. The chemical structure of POTs was explored by employing necessary instrumental analysis techniques, including microwave-assisted acid digestion (MAD), inductively coupled plasma atomic emission spectroscopy (ICP-AES), Fourier-transform infrared spectroscopy (FT-IR), and gas chromatography-mass spectrometry (GC-MS). The collecting performance of POTs in coal flotation was evaluated using an experimental design based on Response Surface Methodology (RSM), considering the ash content and yield of the final concentrate. The effect of the type and dosage of POTs was evaluated in conjunction with other important operating variables, including the dosage of frother, dosage of depressant, and the type of coal. Results of POTs characterization revealed that the pyrolysis oils were a complex composition of light and heavy hydrocarbon molecules, including naphthalene, biphenyl, acenaphthylene, fluorene, and pyrene. Statistical analysis of experimental results showed that among different POTs, POT1 exhibited remarkable superiority, achieving not only a 15% higher coal recovery but also a 12% lower ash content. The outstanding performance of POT1 was attributed to its unique composition, which includes a concentrated presence of carbon chains within the optimal range for efficient flotation. Additionally, the FT-IR spectra of POT1 reveal specific functional groups, including aromatic and aliphatic compounds, greatly enhancing its interaction with coal surfaces, as confirmed by contact angle measurement. This research provides valuable insights into the specific carbon chains and functional groups that contribute to the effectiveness of POT as a collector, facilitating the optimization of coal flotation processes and underscoring the environmental advantages of employing pyrolysis oils as sustainable alternatives in the mining industry.

An environmentally friendly method for extraction of cobalt and molybdenum from spent catalysts using deep eutectic solvents (DESs).

There has been a substantially increasing demand for energy critical elements (ECEs) in recent years as energy-related technology has advanced rapidly. Spent catalysts are known as potential sources of ECCs such as Ni, Co, Mo, W, V, and rare earth elements. This study developed a novel environmentally friendly process for recovering cobalt and molybdenum from spent hydroprocessing catalysts using deep eutectic solvents (DESs). DESs based on p-toluenesulfonic acid achieved high metal extraction at 100 °C and a pulp density of 20 g/L for 48 h which 93% of cobalt and 87% of molybdenum were dissolved. FT-IR and H-NMR analyses were conducted to determine whether hydrogen bonds form between p-toluenesulfonic acid-based DES components. Leaching kinetic models were also developed for DES systems. The experimental results were well-matched with the shrinking core models. The leaching controlling step of DES-1 was determined to be the diffusion through the product layer based on kinetic studies, with an activation energy of 22.56 kJ/mol for Co and 29.34 kJ/mol for Mo in DES-1. Similarly, the mixed control reaction with an activation energy of 38.09 kJ/mol for Co and 31.48 kJ/mol for Mo in DES-2 was found to control the leaching kinetic mechanism of the DES-2 sample.

Genetic algorithm-assisted artificial neural network modelling for remediation and recovery of Pb (II) and Cr(VI) by manganese and cobalt spinel ferrite super nanoadsorbent.

MnFe2O4 and CoFe2O4 nanoparticles were hydrothermally synthesized to examine their capability in adsorption of Pb (II) and Cr (VI). The adsorbents exhibited a high rate of adsorption, reaching 90% of their adsorption capacity in less than 30 min. Furthermore, the adsorption capability of the Magnetic Nanoparticles (MNPs) was noticeably greater at initial pollutant concentrations smaller than 40 mg/L. Maximum adsorption capacity on MnFe2O4 and CoFe2O4 nanoparticles were 40 and 25.38 mg/g for Cr (VI) and 523.32 and 476.19 mg/g for Pb (II), respectively. A data-driven model of Artificial Neural Network was used for prediction of adsorption capacity at both equilibrium and non-equilibrium condition. The model parameters including the numbers of neuron (n = 7) and data portioning for training (49.5%), validation (40.5%), and testing (10%) were obtained using Genetic Algorithm. The results indicated that the model could predict the data with high accuracy (R2 = 0.998). The input parameters were initial concentration, time, pH, temperature, adsorbent dosage, and other parameters that is dependent to the physico-chemical properties of ions and adsorbents' surface (ε, α1, α2). The mechanism involved in Cr(VI) and Pb(II) adsorption are electrostatic physisorption and a combination of ion exchange chemisorption and electrostatic physisorption, respectively. Desorption capability and adsorbent reuse capability were also examined.

Intelligent modelling for the elimination of lanthanides (La3+, Ce3+, Nd3+ and Eu3+) from aqueous solution by magnetic CoFe2O4 and CoFe2O4-GO spinel ferrite nanocomposites.

In this research, a novel CoFe2O4-GO (Graphen Oxide) resulting from the combination of high applicable magnetic and organic base materials and synthesized with a simple and fast co-precipitation route was synthesized for the REEs (Rare Earth Elements) extraction. This adsorbent could remove the La3+, Ce3+, Nd3+ and Eu3+ by maximum adsorption capacity of 625, 626, 714.2, 1111.2 mg/g at optimized pH = 6, respectively. A data-driven model was obtained using Group Method of Data Handling (GMDH)-based Neural Network to estimate the adsorption capacity of these LREEs as a function of time, pH, temperature, adsorbent ζ (zeta)- potential, initial concentration of lanthanides ions, and ε which is defined by the physico-chemical properties of lanthanides. The results clearly indicated that the model estimate the experimental values with good deviation (mostly less than 10%) and it can be used for the prediction of the results from other similar researches with less than 25% deviation. The results of sensitivity analysis indicated that the adsorption capacity is more sensitive to pH of the solution, temperature, and ε. Finally, the desorption studies showed an excellent removal efficiency (97%) at least for three adsorption-desorption cycles. These results claimed that the CoFe2O4-GO is a highly efficient adsorbent for the REEs extraction.

Green extraction of nickel and valuable metals from pyrrhotite samples with different crystallographic structures through acidophilic bioleaching.

Nowadays, due to the strategic status of nickel in the global market, utilizing its disregarded resources like low-grade nickel containing pyrrhotite is of significant importance. A comprehensive set of experiments and analyses were performed to determine the bioleaching capability and mechanism for nickel extraction from hexagonal and monoclinic pyrrhotite. Over 95% Ni extraction was achieved from the hexagonal pyrrhotite sample. Ni extraction from the monoclinic sample reached its maximum value of 67% and 90% at 3% pulp density, with mixed mesophilic and moderately thermophilic cultures, respectively. Characterization analyses indicated that jarosite and elemental sulfur formation in mixed mesophilic bioleaching reduced the samples' bio-oxidation rate and metal dissolution. The kinetics study revealed that the controlling step in thermophilic bioleaching is the chemical reaction; however, the mixed control model was best fitted on mesophilic data. Electrochemistry studies confirmed bioleaching results and indicated that monoclinic pyrrhotite's oxidation rate under the operating conditions is faster than hexagonal pyrrhotite, and the temperature positively correlates with the oxidation rate. Toxicity assessment analysis showed that the final residues of both bioleached samples could be considered environmentally safe.

A cleaner approach for high-efficiency regeneration of base and precious metals from waste printed circuit boards through stepwise oxido-acidic and thiocyanate leaching.

This work evaluated a green route for developing an eco-friendly flowsheet to regenerate base and precious metals from waste printed circuits boards (WPCBs). Copper (as nanoparticles with an average diameter of 50 nm) and other base metals were extracted via oxidative acid leaching with high efficiency. Thiocyanate was employed for the first time as a green and economical reagent for the extraction of gold from pretreated WPCB. The effect of various parameters, including reagent dosage and temperature, was evaluated on the gold leaching rate, and 100% gold dissolution was achieved at the optimal condition. It was found that ferric iron concentration as the gold leaching oxidant has a notable effect on gold extraction. Also, at temperatures above room temperature, the recovery rate increases in a short period and then decreases continuously. The activation energy of the optimum gold thiocyanate leaching was found to be 42.84 kJ/mol, indicating chemical reaction to be the rate-controlling step. Gold extraction from the thiocyanate medium was carried out by employing activated carbon, where 100% gold adsorption was achieved in 2 h. Toxicity assessment of final residue revealed that it could be categorized as an environmentally safe waste with negligible risk.

Superadsorbent Fe3O4-coated carbon black nanocomposite for separation of light rare earth elements from aqueous solution: GMDH-based Neural Network and sensitivity analysis.

A series of nanocomposites adsorbents with different magnetite/carbon black ratios were synthesized by using the co-precipitation method and used for separation of LREEs (Ce, La, and Nd) from aqueous solution. The adsorption efficiency of nanocomposites is strongly dependent on both pH and the loading carbon on nanocomposite. The maximum adsorption capacity (370 mg/g) was reported by nanocomposite with 20% Fe3O4 and 80% carbon in pH 7 for LREE initial concentration of 250 ppm. Results revealed that the LREEs adsorption behavior of the optimal adsorbent fits well with Langmuir isotherm and pseudo-first-order kinetic model. Moreover, the average values of thermodynamic parameters suggest the endothermic and irreversible chemisorption mechanism. An empirical correlation was obtained by using GMDH (Group Method of Data Handling)-based Neural Network to predict the adsorption kinetics of LREEs as a function of ion's electronegativity, molecular weight, and initial concentration. The results showed that the correlation can predict the experimental data mostly lower than 12.5% and it can predict the results of other researches with similar conditions with up to 25% from the experimental values. Finally, the results of sensitivity analysis revealed that the adsorption of LREEs is more sensitive to ions electronegativity and molecular weight at equilibrium conditions.

Insights into the Effects of Pore Size Distribution on the Flowing Behavior of Carbonate Rocks: Linking a Nano-Based Enhanced Oil Recovery Method to Rock Typing.

As a fixed reservoir rock property, pore throat size distribution (PSD) is known to affect the distribution of reservoir fluid saturation strongly. This study aims to investigate the relations between the PSD and the oil-water relative permeabilities of reservoir rock with a focus on the efficiency of surfactant-nanofluid flooding as an enhanced oil recovery (EOR) technique. For this purpose, mercury injection capillary pressure (MICP) tests were conducted on two core plugs with similar rock types (in respect to their flow zone index (FZI) values), which were selected among more than 20 core plugs, to examine the effectiveness of a surfactant-nanoparticle EOR method for reducing the amount of oil left behind after secondary core flooding experiments. Thus, interfacial tension (IFT) and contact angle measurements were carried out to determine the optimum concentrations of an anionic surfactant and silica nanoparticles (NPs) for core flooding experiments. Results of relative permeability tests showed that the PSDs could significantly affect the endpoints of the relative permeability curves, and a large amount of unswept oil could be recovered by flooding a mixture of the alpha olefin sulfonate (AOS) surfactant + silica NPs as an EOR solution. Results of core flooding tests indicated that the injection of AOS + NPs solution in tertiary mode could increase the post-water flooding oil recovery by up to 2.5% and 8.6% for the carbonate core plugs with homogeneous and heterogeneous PSDs, respectively.

MnFe2O4-graphene oxide magnetic nanoparticles as a high-performance adsorbent for rare earth elements: Synthesis, isotherms, kinetics, thermodynamics and desorption.

In recent decades, considerable amounts of rare earth elements have been used and then released into industrial wastewater, which caused serious environmental problems. In this work, in order to recycle rare earth cations (La3+ and Ce3+) from aqueous solutions, MnFe2O4-Graphene oxide magnetic nanoparticles were synthesized and after characterization studies, their adsorption isotherms, kinetics, thermodynamics and desorption were comprehensively investigated. Characterized was performed using XRD, FE-SEM, FT-IR, Raman spectroscopy, VSM, BET and DLS. REE adsorption on MnFe2O4-GO was studied for the first time in the present work and the maximum adsorption capacity at the optimum condition (room temperature and pH = 7) for La3+ and Ce3+ were 1001 and 982 mg/g respectively, and the reactions were completed within 20 min. In addition, the adsorption data were well matched with the Langmuir model and the adsorption kinetics were fitted with the pseudo-second order model. The thermodynamic parameters were calculated and the reactions were found to be endothermic and spontaneous. Moreover, the Dubinin-Radushkevich model predicted chemical ion-exchange adsorption. Desorption studies also demonstrated that MnFe2O4-GO can be regenerated for multiple reuses. Overall, high adsorption capacity, chemical stability, reusability, fast kinetics, easy magnetic separation, and simple synthesis method indicated that MnFe2O4-GO is a high-performance adsorbent for REE.