Abstract Abstract
Research subject: Bioleaching of lithium has emerged as an innovative and sustainable approach for extracting this valuable metal from solid sources, including mineral ores, spent lithium-ion batteries, and other electronic waste. The increasing global demand for lithium-ion batteries, especially for consumer electronics and electric vehicles, has intensified the need for efficient lithium resource recovery. Given the environmental and economic challenges associated with traditional extraction methods, bioleaching has been proposed as an eco-friendly and cost-effective alternative.
Research approach: This study provides a comprehensive review of the scientific literature and research on lithium bioleaching. It begins with an overview of lithium resources and applications, followed by an evaluation of studies on the bioleaching of lithium-ion batteries and other solid sources. The mechanisms involved and commonly used microorganisms are analyzed. Additionally, key parameters influencing metal recovery efficiency—such as pH, temperature, medium composition, pulp density, and leaching time—are investigated. The study also explores innovative approaches, including the use of artificial intelligence, systems biology, and synthetic biology, to optimize bioleaching processes.
Main results: The findings demonstrate that bioleaching not only achieves efficient lithium recovery from solid sources but also significantly reduces environmental hazards. Spent lithium-ion batteries are identified as a rich and valuable source for lithium extraction. The use of microorganisms such as Aspergillus niger and Acidithiobacillus ferrooxidans has achieved lithium recovery rates of up to 100%. Studies indicate that optimizing microbial strains through synthetic and systems biology, along with refining cultivation conditions using modern AI-based techniques, can address industrial challenges in bioleaching. Furthermore, this research highlights the role of bioleaching in promoting a circular economy and presents a promising outlook for its industrial application in sustainable lithium resource recovery.

Abstract Research subject: Real-time analysis using digital tools requires receiving instantaneous data from various points in industrial chemical processes. Time delays in measurements of process variables can affect the effective performance of different control strategies, process stability, and operational efficiency, making it impossible to analyze, extract information, and convert it into actionable decisions in real-time. The synthesis process of vinyl acetate monomer is recognized as a benchmark dynamic and nonlinear process in the chemical industry. In this process, the composition of water at the bottom of the azeotropic distillation column is one of the important variables measured by a gas chromatography (GC) analyzer, which has a significant time delay and high cost.
Research approach: Soft sensors primarily improve the real-time estimation of variables that are difficult or impossible to measure. Neural networks play an important role in the development of soft sensors due to their ability to learn nonlinear patterns and their suitable prediction speed. This study focuses on the development of a soft sensor based on a feedforward neural network model for real-time estimation of the composition of water at the bottom of an azeotropic distillation column in the vinyl acetate monomer synthesis process.
Main results: Additionally, the model was adaptively implemented under various fault conditions and accurately estimates the GC analyzer behavior instantaneously, achieving a mean squared error (MSE) of 1.1 × 10-5. Maintaining prediction accuracy in the adaptive implementation of soft sensors in the presence of various process faults demonstrates the effective adaptability of these sensors. Therefore, this study demonstrates the capability of soft sensors as an efficient and cost-effective alternative for real-time monitoring of complex chemical processes.

Abstract Research subject: In this study, glucosamine-functionalized core–shell nanoparticles were synthesized. Subsequently, the nanoparticle synthesis was confirmed using various characterization techniques, and the synthesized nanoparticles were applied for heavy metal separation. To this end, Fe₃O₄@SiO₂ magnetic core–shell nanoparticles were synthesized via co-precipitation and Stöber methods. The core–shell nanoparticles were subsequently functionalized with cyanuric chloride and glucosamine. Glucosamine-functionalized nanoparticles were used as effective adsorbents for the removal of cadmium ions from aqueous solutions via solid-phase extraction.
Research approach: Morphological, structural, and magnetic properties, as well as particle size of the nanoparticles during synthesis, were investigated using transmission electron microscopy (TEM), field emission scanning electron microscopy (FE-SEM), dynamic light scattering (DLS), and X-ray diffraction (XRD). Additional analyses included Fourier-transform infrared spectroscopy (FT-IR), thermogravimetric analysis (TGA), energy-dispersive X-ray spectroscopy (EDX), and vibrating sample magnetometry (VSM). Subsequently, the effects of various parameters—including adsorbent dosage, contact time, and solution pH—on adsorption performance were investigated. Main results: The results indicated that the maximum cadmium adsorption capacity (145 mg/g) was achieved when 15 mg of adsorbent was added to 50 mL of solution with an initial concentration of 0.4 mmol/L over 18 minutes at pH 7. In addition, the synthetic nanoadsorbent was recycled and reused for six consecutive adsorption–desorption cycles using a magnet, without significant loss in adsorption performance. Glucosamine-functionalized core–shell nanoparticles are proposed as a promising technology for water and wastewater treatment, owing to their high adsorption capacity and reusability in sequential adsorption–desorption cycles.

Abstract Research subject: In this study, Fe₃O₄ nanoparticles were synthesized using the co-precipitation method. Subsequently, core–shell Fe₃O₄@SiO₂ nanoparticles were prepared via the Stöber method using tetraethoxysilane as the silica source. In the next step, the core–shell nanoparticles were functionalized with theophylline molecules. Finally, these nanoparticles were employed as an adsorbent for the removal of nickel ions from aqueous solutions using the solid-phase extraction method.
Research approach: The structural, crystalline, thermal, magnetic, morphological, and size-related properties of the nanoparticles were investigated using X-ray diffraction, Fourier transform infrared spectroscopy, thermogravimetric analysis, vibrating sample magnetometry, transmission electron microscopy, and scanning electron microscopy. The key parameters affecting solid-phase extraction were then optimized following confirmation of the successful synthesis of the proposed nanostructure. For this purpose, the effects of adsorbent dosage, contact time, pH, and initial nickel ion concentration on adsorption capacity were systematically studied.
Main results: The results showed that using 27 mg of adsorbent in 75 mL of nickel ion solution with an initial concentration of 0.45 mmol/L achieved a maximum adsorption capacity of 94% at pH 7 within 28 minutes at ambient temperature. Furthermore, the recyclability and reusability of the nanoadsorbent were examined through sequential adsorption–desorption cycles using an external magnet. The results demonstrated excellent performance in removing divalent nickel ions from aqueous solutions. Moreover, the synthetic nanoadsorbent could be recovered and reused across successive adsorption–desorption cycles without any loss of functional activity.

Abstract Research Subject: Modeling the Pressure Swing Adsorption (PSA) process in Kavian Petrochemical, which is used for hydrogen purification
 Research Approach: In this research, PSA process and structural optimizations on hydrogen quality using process modeling by the Rung-kutta gill method using MATLAB software were innovatively carried out for the first time in Iran for the Kavian Petrochemical Olefin Unit, and for the first time, process optimization was simulated to increase production efficiency.
Main Results: In order to investigate the effect of pressure on this process, the pressure of the adsorption stage was changed from 20 to 40 bar. The results showed that by increasing the pressure from 20 to 25 bar, the hydrogen purity increased by 0.53% and then decreased by 0.29% with further increase in pressure to 40 bar. Pressure changes also affected hydrogen recovery and productivity, with an increase in pressure from 20 to 40 bar resulting in a 51.27% decrease in hydrogen recovery and a 51.28% decrease in hydrogen productivity. Based on the simulation results, if high hydrogen purity is desired, the optimal pressure was determined to be 25 bar. However, if recovery and productivity are important, it is better to keep the pressure as low as possible because a 0.53% increase in hydrogen purity with increasing pressure means a decrease in hydrogen production of approximately 5 tons per ton of adsorbent per year. In order to validate the model, the modeling results were compared with industrial data. The results of this comparison show that the error between the modeling results and industrial data is very small, about one percent.
 

Abstract Today, different filament cross-sectional shapes of spinneret are used in the production of synthetic multifilament yarns to create various applications and properties. This research aimed to investigate the effect of round and rectangular cross-sectional shapes of polyethylene terephthalate (PET) multifilament yarn on the physical and crimp properties of melt-spun and draw-textured yarn with partially oriented yarns (POY) produced by an industrial melt spinning machine and then draw textured yarns (DTY) was produced by an industrial frictional false twist texturizing machine under the same conditions. All yarn samples with two round and rectangular cross-sectional shapes, linear density, thermal shrinkage, degree of crystallinity, and tensile properties (strength, elongation at break, and initial modulus) were analyzed. Also, for DTY yarns, in addition to the mentioned tests, the crimp properties (crimp shrinkage, crimp modulus, and crimp stability), the amount of resiliency, and the ratio of tension after twisting zone to tension before twisting zone (T2/T1) were also investigated. In addition, to know the microstructural condition of fibers, an X-ray diffraction test was performed for textured yarn samples. According to the results, it was found that the difference in tensile properties and thermal shrinkage of POY yarns of both cross-sections is small, despite the statistical significance. However, these variations are greater for two round and rectangular cross-sectional shapes in DTY yarns. In comparing the resiliency values of DTY yarns, the yarn with a rectangular cross-sectional shape showed a higher resiliency value than the round cross-sectional shape. In addition, the crimp properties of DTY yarn with a round cross-sectional shape were better than a rectangular cross-sectional surface, which can be attributed to its higher crystallinity and consequently, softness and texturability compared to a round cross-sectional shape.