Shatrughan Soren

In the modern era, two-dimensional MXenes—commonly known as transition metal carbides, nitrides, and carbonitrides—have emerged as a new class of competitive materials for developing composites across various applications. As a 2D material, MXene-reinforced composites represent an emerging field with significant potential due to their remarkable optical, mechanical, electrical, and electrochemical properties. Additionally, their stability at high temperatures highlights their uniqueness in composite materials. Consequently, MXenes are regarded as revolutionary materials for functional and structural composite applications, offering tunable electrical, thermochemical, and physicomechanical properties. This review examines recent advancements in the use of MXenes as reinforcing elements in metal matrix composites (MMCs) and polymer matrix composites (PMCs), while providing insights for future research in this area.

In powder metallurgy, the sintering process is a high-power consuming and critical process for better mechanical properties of composites due to proper diffusion of atoms. In this context, different sintering processes were investigated along with their sintering condition. The present work focused on optimizing conventional sintering process parameters for carbon nanotubes (CNTs) reinforced aluminum composites using Taguchi optimization methods. The Taguchi L9 orthogonal array (OA) experiment was considered for the investigation. CNT’s wt.%, sintering temperature, and time were chosen as process parameters in the sintering process, while macro-hardness and relative density were evaluated as performance evaluation characteristics. The signal-to-noise ratio (S/N) and ANOVA statistical procedures were utilized to evaluate the effect of sintering parameters/levels on the micro-hardness and relative density of the Al/CNTs composite sintered. ANOVA statistical analyses revealed that the CNTs wt.% significantly influences relative density (83.58%), followed by temperature (14.58%), whereas CNTs wt.% significantly influenced micro-hardness (77.75%), followed by temperature (13.64%). The sintering of Al/CNTs composites using these optimum conditions is recommended to reduce power consumption and enhance the quality of the sintered composite.

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.

The aluminum nanocomposite is fabricated through squeeze stir casting method where CNT, SiC/B₄C powder has been used as a reinforcement in an aluminum matrix. Squeeze action in stir casting opted due to proper reinforcement of 2 vol% of CNT in the matrix. The boron carbide and silicon carbide have been added by 8 and 12 vol% in the matrix. Uniform distribution of reinforcement and phase analysis has been shown by scanning electron microscopy (SEM) and XRD analysis. The formation of intermetallic compounds like Al₃BC and Al₄C₃, dislocation forests, and the interaction of the reinforcement with the matrix are all confirmed by transmission electron microscopy (TEM). The micro-mechanical behavior of aluminum nanocomposites was investigated using nano indentation. The nano hardness, Vickers hardness, and Young's modulus of 12 vol% B₄C compared with 12 vol% of SiC are increased by 12%, 23%, and 16%, respectively, and the same trend has been observed for the 8 vol% B₄C reinforced composite. The model analysis for Young's modulus has been done and the experimental value for the modulus of elasticity of the composite are validated and not find such differences significantly. The surface topography was determined, furrow scratches and wear scars, and it was discovered that B₄C reinforced composites have reduced stripping pits inside the wear marks, as well as lower wear width and depth. Wear analysis is essential because abrasive encounters result in substantial damage owing to larger pits and bigger wear scars.

The present work aims at performing prediction validation for the physical properties of coke layered and nonlayered hybrid pelletized sinter (HPS) using artificial neural networks (ANNs). Physical property analyses were experimentally performed on the two HPS products. The ANN model was then trained to obtain the best prediction results with the grid-search hyper-parameter tuning method. The learning rate, momentum constant, and the number of neurons varied over specified ranges. The binary variable conversion was utilized to assess the two sintering processes. The nonlayered HPS product of 4 mm micropellets at basicity 1.75 and using 8% coke shows a good combination of physical properties, whereas HPS of 4 mm micropellets at 1.5 basicity using 4% coke as fuel and 2% coke as layering gives a radical improvement in physical properties. The yield of the HPS product is 96.07%, with the shatter index (SI), tumbler index (TI), and abrasion index (AI) values being 86.12, 79.60, and 5.74%, respectively. Hence, HPS can be preferred by implementing the layering of coke powder. The prediction analyses showed that the multilayer perceptron model (MLP) network with a 4-29-5 structure showed prediction accuracies of over 99.99% and a mean squared error (MSE) of 2.87 × 10^-4. It verifies the accuracy and prediction effectiveness of the hyper-parameter-tuned ANN model.

In India, during mining and ore processing, ore fine generation is a common phenomenon, in which more than 60% of process ore becomes discarded material. To explore the alternative of high-grade ores, mutual replacement with the utility of dump ore fines is the best way. With this perspective, Kiruburu iron ore mine (Iron Ore No.1) and Meghataburu iron ore mine (Iron Ore No.2) dumped fines were chosen for a Blaine no. investigation, in the connection of firing temperatures, to get optimum desirable physical properties, Cold Compression Strength (C.C.S.),and Apparent Porosity (A.P.), with physico-chemical properties, Reducibility Degradation Index (R.D.I.), and Reducibility Index (R.I.). To characterize pellet properties with input variables, a microstructure phase study has been conducted using a scanning electron microscope (S.E.M.), energy dispersive spectroscopy (EDS), and X-ray diffraction analysis (XRD). The Iron Ore No.1 and 2 fine pellets survey showed good, desirable properties, at the Blaine no., of 1678 cm²/g and 2311 cm²/g (corresponding to 200 mesh size), and the best results are attained at a firing temperature of 1300 °C. Thermal kinetic analysis of the heating of pellets has been done to knowthe activation energy of different ore characteristics. The results showed that Iron Ore No.2 pellets have high activation energy.