Transactions of The Indian Institute of Metals最新文献

Effect of load ratio (R) on the interface microstructure and phase stability was investigated in mild steel/Grade-2 Ti explosive clads using experimental and JMatPro® computations. At low-impact-energy conditions (i.e., R = 1.07), the interface exhibited a symmetrical wavy morphology with molten metal entrapped in isolated regions within the vortices of the waves, while at high-impact loading conditions (R = 3) the interface had complex weld solidification structure consisting of planar interface, columnar and equiaxed dendrites. Based on the study, it was concluded that under high-impact loading conditions, the interface microstructure of the explosive clads will resemble fusion welded joints, but with relatively lower thickness of the interaction zones.

The research work focuses on a novel post-processing sequence to improve the surface integrity and residual stress characteristics of as-printed Inconel718 (IN718) samples. The as-printed IN718 samples are subjected to solution treatment at 1050 °C, two-step precipitation hardening (@ 720 °C for 8 h and @ 620 °C for 8 h), and low plasticity burnishing. Two different sequences were attempted. Sequence-1 involves solutionizing → low plasticity burnishing followed by precipitation hardening, and sequence-2 includes solutionizing → precipitation hardening followed by low plasticity burnishing. The experimental observations and detailed investigations revealed that the samples processed via sequence 2 exhibited a better surface finish. The microhardness of the samples of sequence 2 is 10% higher than their counterparts in sequence 1. The maximum residual stress of −1375.33 MPa is obtained in sequence 1 as compared to the residual stress of −1100.67 MPa in sequence 2. The influence of the processing sequences on the surface properties has been discussed in detail using the XRD and microstructural characterization supported with EBSD analysis.

Graphic Abstract

The present study investigates the effect of in situ reinforced TiC on the microstructure, density, and tensile properties of austenitic low-density steel. Low-density steels with compositions of Fe-18.93%Mn-6.20%Al-0.76%C (Steel A) and composition of steel A, with the addition of 2.5 %Ti and 0.5 %C are melted via induction melting and cast into copper mold to get austenite in steel A and austenite plus in-situ formation of 4.5 vol% TiC in Steel B, respectively. Both the homogenized steels are subjected to hot rolling followed by solutionizing and quenching in water. The austenitic Steel A reports low density and Young’s modulus of 6.99 g/cc and 169 GPa, respectively. The presence of 4.5 vol% TiC in austenitic Steel B reduces density to 6.84 g/cc but increases Young’s modulus to 176 GPa, yield strength to 578 MPa, and tensile strength to 920 MPa. In situ formation of TiC increases grain boundary strengthening due to refinement in austenite size and dislocation strengthening significantly even though solid solution strengthening is the dominating one. Formation of TiC reduces the product of strength and elongation (PCE) to 32.5 GPa% due to a decrease in ductility. Both steels exhibit Ludwigson flow behavior, characterized by two distinct slopes of easy glide and cross-slip, respectively, in true stress–true strain plots.

Nickel-PolyTetraFluoroEthylene (Ni-PTFE) composite coatings were prepared from a watts-type nickel plating bath by varying process parameters in this study. The considered input process variables were current density, potential of hydrogen range, bath temperature, PTFE bath concentration, and stirrer speed. Experiments systematically analyzed their effects on outcomes. The responses measured in the experiments included the surface roughness, mass of deposit, and coating thickness of the coated samples. Scanning electron microscope and microstructure examinations analyzed Ni-PTFE deposition in specimens from mild steel plates. Additionally, an adaptive neural fuzzy inference system model was developed to predict the surface roughness, mass of deposit, and coating thickness of the coated samples. The model showed high accuracy in predicting parameters, closely matching experimental data.

This study investigates the effect of adding boron as a ternary addition to binary FeCo alloys. Fe–Co–B ternary alloys with varying boron concentrations between 0 and 2 wt% were synthesized through mechanical alloying. The study aims to analyze the structural, morphological, and magnetic properties of the Fe–Co alloy matrix with the inclusion of boron. The XRD results showed a single solid solution phase of Fe–bcc structure for all alloys, regardless of the boron concentration. It was seen that the low solubility of boron in Fe–Co caused the formation of hard structures at the grain boundaries, resulting in an increase in hardness with an increase in boron concentration. On the other hand, a decreasing trend was observed in coercivity, which is ascribed to the formation of FeB at the grain boundaries, as proved from XRD analysis. An increase in boron concentration did not seem to significantly affect the saturation magnetization, which remained in the range of 190 ± 10 emu/g for all Fe–Co–B alloys. The experimental data was cross checked and further insights were gained; DFT calculations were performed using Vienna Ab Initio Simulation Package.

In the current study, NiAl–TiB₂ nanocomposite was produced by mechanical alloying and subsequent heat treatment. For this purpose, mixtures of pure Ni, Al, Ti, and B powders were milled in a ball mill for 20 h to produce NiAl-TiB₂ nanocomposites containing 10, 20, and 30 at% TiB₂. The heat treatment temperature was selected at 850 °C for 30 min which was determined by differential thermal analysis. X-ray diffractometer (XRD) was used to identify the existing phases. The XRD results showed the completion of alloying after heat treatment. Furthermore, the morphology of the powders and microstructure of the sintered samples were investigated by optical microscopy and field emission scanning electron microscopy. Results showed that the NiAl-20% TiB₂ sample had the most homogeneous morphology. Then the powder mixture was hot pressed at 800 °C under 300 MPa. The density of the sample reached 95% after hot pressing. The sample containing 20% TiB₂ was subjected to wear test under 5, 7, 10, and 13N loads by pin on disk method. Examination of the morphology of the worn surface and wear debris showed that spalling was the dominant wear mechanism.

Transverse corner cracks are among the most common defects in high carbon and high carbon micro-alloyed grade slab casting. Calculation and analysis were done to minimize the negative strip time of mold oscillation, which is responsible for reducing the depth of the oscillation mark formed on the slab surface. The value of negative strip time decreases with an increase in the frequency of mold oscillation. Based on the trial results, it was suggested that the oscillation proportionality be adjusted from 1.2 to either 1.25 or 1.3. This adjustment will reduce the depth of oscillation marks and the tendency to form transverse cracks. The transverse crack on the narrow face of the slab was examined for crack analysis and compositional analysis. Microstructural analysis revealed that the crack has no branching and consists of an iron scale inside it. Furthermore, it is observed that the crack propagates across the allotriomorphic ferrite grains.

This study designs new Fe-amorphous/Al-12Si piston composite materials. The effect and synergistic mechanism of the addition of Fe-amorphous and bionic microtexture laser surface on the high-temperature friction performance of Al-12Si piston material under mixed lubrication conditions of B30 biodiesel and engine lubricating oil have been studied. The results indicate that the frictional properties of the untextured surface of the Fe-amorphous/Al-12Si composite material depend primarily on the amount of Fe-amorphous added. The 10 wt% Fe-amorphous/Al-12Si composite exhibits a dense, void-free microstructure with optimum anti-friction and anti-wear performance. It is noteworthy that the interaction between the “anchoring” effect caused by the Fe-amorphous addition and the synergistic effect of the bionic microtexture providing a stable lubricating environment further enhances the high-temperature friction properties of Al-12Si.

Ti-6Al-4 V alloy is widely used in medical implants, particularly in orthopedics application. Additive manufacturing (AM), specifically selective laser melting (SLM) is useful for porous scaffolds fabrication where complex passages facilitaes bone re-growth. This study focused on the modeling, manufacture, and testing of microstructure and mechanical characteristics of seven different scaffolds (Diamond, Cross, Grid, Vinties, Tesseract, Star, and Octet) of 15 mm cube with 65% porosity. Average pore area and strut thickness of scaffolds are measured using Stereo microscope. All these fabricated scaffolds are experimentally tested under compressive loads in INSTRON testing machine. The compressive test results are also compared with the numerical simulation results generated using finite element analysis (ANSYS) software. Maximum load cell capacity of ± 25 kNis used during compression testing in INSTRON. The Grid type scaffold shows maximum ultimate compressive strength of 101.39 MPa and an effective elastic moduli of 10.33 GPa with an average pore area of 2,417,618.517 µm² and strut thickness of 740.249 µm. This variant of the scaffold will be more compatible with the human bone’s elasticity, and it can also mitigate stress-shielding effects during healing.

The primary aim of this study is to predict the hardness of high entropy alloys and identify optimal alloy compositions with superior hardness through machine learning techniques. To enhance the accuracy of predictions, a dual-layer algorithmic machine learning model was employed and augmented with Shapley Additive Explanations (SHAP) analysis to increase the model’s interpretability. During model development, multiple machine learning algorithms were evaluated, and innovatively, a combination of the three most optimal model outcomes was incorporated into the prediction process, thus improving the accuracy of hardness predictions. Furthermore, using the Al–Co–Cr–Fe–Ni system as an example, an HEA with a predicted hardness of 776HV was identified from 820,000 datasets. This sample was fabricated using two different preparation techniques and subsequently validated through experimental testing.