Beneficiation of Low-Grade Hematite Iron Ore Fines by Magnetizing Roasting and Magnetic Separation.

Present investigation includes the magnetizing roasting of low-grade iron ore fines followed by grinding and beneficiation using magnetic separation. The hematite iron ore used in the investigation contains 53.17% T Fe, 10.7% SiO2, and 4.5% Al2O3. Powdered bituminous coal of 210 µm size with an ash content of 12.5% and fixed carbon of 54.25% was used as reductant during magnetizing roasting. Optical microstructures have shown where iron and silicate minerals are found and how they are interconnected. Hematite is the most abundant material in the specimen and is found in fine- and medium-sized grains. Hematite emerged as the predominant iron-bearing mineral, accompanied by magnetite and goethite phases in smaller proportions according to XRD analyses. The primary gangue mineral identified by scanning electron microscopy is quartz, with gibbsite, feldspar, and pyrolusite present in lesser levels. The effects of iron/coal ratio, roasting time, and roasting temperature were considered as variable parameters. Hematite ore's magnetic characteristics were significantly impacted by magnetizing roasting. By selectively magnetizing roasting, hematite is transformed into magnetite. With an Fe grade of 65.25% at a recovery value of 72.5% in the concentrate, magnetic separation produced the greatest result for Fe. The performance of magnetization and therefore the magnetic separation process were shown to be significantly impacted by temperature, reductant %, and roasting duration in this investigation.

Distribution of Carbon Nanotubes in an Aluminum Matrix by a Solution-Mixing Process.

In order to overcome the limitations of standard ball-mill mixing processes to fabricate a uniformly dispersed carbon nanotube (CNT) reinforcement composite without damaging CNTs in matrix powder, a unique and easy solution-mixing process was developed. The present study aims to synthesize Al-0.5 wt % CNT composites using ball-milling and solution-mixing processes and compares their CNT dispersion and structural and thermal properties. Compared with the ball-milling process, the solution-mixing process was simple and effective for the uniform distribution of CNTs without structural damage. Various methods were utilized to examine the structural characteristics of the composite powder. These techniques included high-resolution transmission electron microscopy (HRTEM), X-ray diffraction (XRD), field emission scanning electron microscopy (FESEM), Raman spectroscopy, and particle size analysis. Raman spectroscopy observes an increase of defects in ball-milled composites, and the particle size analyzer confirms the structural deformation, resulting in the degradation of composite powder mechanical properties. In the solution-mixing process, aluminum particles and the structure of CNTs are well-preserved even after mixing. Thermogravimetric analysis (TGA) was used to research the thermal stability of the composite materials. The results validated the impact of CNTs on thermal characteristics enhancement (improved thermal resistance) when compared with pure aluminum, suggesting potential uses in the aerospace industry, transport, and construction sectors.

Assessing the Mechanical Properties of a New High Strength Aluminum Hybrid MMC Based on the ANN Approach for Automotive Application.

Aluminum-based composites with characteristics such as low density and high strength to weight ratio have been identified to be one of the best-emerging alternatives. The lightweight composite is gaining popularity, particularly in the automotive industry. The composite's qualities make it a prospective material to replace significant materials that are now used in the automobile industry. For lightweight products, various weight reduction solutions were proposed. In the present work, one such lightweight composite was fabricated by using a stir casting process, which includes reinforcement powders viz. carbon nanotube and fly ash to pure aluminum. The use of fly ash helps in reducing the overall associated cost of the material as well as provides low density. The work aims to identify the amount of fly ash (by weight %) suitable to avail good mechanical properties. In concern with the mechanical properties, density, yield strength, ultimate tensile strength, and wear resistance of the composite specimen were examined. Moreover, the artificial neural network was adopted to identify minimum volumetric wear for a given set of conditions. From the results, it was perceived that with the increase in fly ash content, the volumetric wear of the fabricated composite decreases. However, with the increase in load and speed, the volumetric wear rate increases.