Key Engineering Materials Vol. 1018

Abstract: The Ti-13Nb-1.5Mo-3Ta alloy is a recently developed biocompatible metastable β-Ti alloy designed for biomedical application. In this present work, the influence of cold rolling and subsequent annealing heat treatment on grain refinement of Ti-13Nb-1.5Mo-3Ta alloy was investigated. The alloy was cold rolled (CR) to 60% and 90% thickness reductions at room temperature followed by recrystallization annealing at different temperature (800°C-900°C) and time (1.5mins-10mins) before ice-water quenching. X-ray diffraction (XRD) and optical microscopy (OM) were used to characterize the alloy, and microhardness tests were carried out using the Vickers microhardness tester. The results revealed that the annealed alloys exhibited a fully β-phase, while those subjected to cold rolling displayed introduction of stress induced martensite (SIM) α′′-phase along with β-phase. The microhardness of the 60% and 90%CR samples increased significantly to 253 and 283 Vickers hardness (HV), respectively, from an initial value of 198 HV. Annealed samples exhibited a recrystallized microstructure containing fine equiaxed grains with average size of 10-50μm for 60%CR and 8-34μm for 90%CR. The grain refinement mechanisms are probably attributed to the reversal of the SIM α′′-phase back to the more stable β-phase and the recrystallization of the deformed β-phase.

Abstract: In Al-Si alloy roll casting, the thickness of the foil and strip decreases as Si content decreases below 2 mass%, contrary to the expectation that the latent heat decreases as Si content decreases. This phenomenon was investigated experimentally using a melt spinning single roll caster, melt drag single roll caster, and vertical type high-speed twin roll cater. The results demonstrate that the peeling of the solidification layer influences the thickness of the foil and strip. The relationship between casting conditions and adhesion of the solidification layers was also investigated.

Abstract: High-speed roll casting of AC2A aluminum alloys for casting was performed at speeds from 20 to 40 m/min using an unequal-diameter twin-roll caster to investigate the improvement of ductility and sheet forming with roll-cast strips. The width of the cast strips was 100 mm. The roll-cast strips were homogenized and cold rolled to a thickness of 1 mm, and the resulting cold-rolled strips were then annealed before tensile testing, deep drawing, V-bending, and three-roll bending. Tensile testing was also performed for a T6 heat-treated test piece. The microstructure was observed using optical microscopy.

Abstract: By replacing the interface with sharp change properties with a functionally graded material with a gradually changing composition, a stable interface can be formed for mechanical and functional properties. In this study, the final goal is to functionally grade the interface between aluminum and alumina (Al₂O₃)/aluminum (Al) composites. First, the segmentation velocity of Al₂O₃ particles under gravity was measured to clarify the possibility of functional grading. The starting materials used were A356.0 Al alloy and α-type Al₂O₃ particles. The segmentation velocity obtained by the experiment was much faster than the theoretical velocity obtained by Stokes' law. It seems Stokes' law assumes that the particles are spherical and there is no interaction between particles, but the actual particle velocity was affected by the actual particle shape and interaction between particles. These factors affect the change in the segmentation velocity. The height of the mold was set to 40 mm, and an Al₂O₃ particle/Al composite with a particle size of 6.7 μm was placed on the top and an Al alloy was placed on the bottom in the mold, melted, and rapidly solidified after 12 sec., and an Al₂O₃ particle-dispersed Al alloy functionally graded composite was obtained under gravity.

Abstract: 17-4 Precipitation hardenable (PH) stainless steel (SS) is useful for applications that require a combination of high strength and corrosion resistance. However, when produced through selective laser melting (SLM), it has a distinct microstructure with significant composition and phase variations based on the process parameters and post processing heat treatment conditions. Therefore, the present study examines how process parameters, such as scanning speed and hatch distance, affect the microstructural, and corrosion characteristics of additively manufactured (AM) 17-4 PH stainless steel samples. Post-processing heat treatment resulted in a uniform and reproducible microstructure in SLM samples. Heat-treated AM samples were assessed in a 3.5 wt. % NaCl solution using electrochemical impedance spectroscopy (EIS). The specimen with an energy density of 39.06 J/mm³ exhibited the lowest open circuit potential value, indicating a favorable tendency to form a passive film. The sample with 66.96 J/mm³ exhibits enhanced corrosion resistance attributed to robust protective performance facilitated by a dense network of precipitates and finer grain size. This heightened resistance is further supported by the sample's highest corrosion layer resistance and charge transfer resistance.

Abstract: The study focuses on the stress-strain behavior of 3D-printed infill patterns with two different infill densities, which are 15% and 30%, to analyze their performance. The stress-strain behavior of a material describes how it deforms and reacts under different stress levels. The stress will be calculated in MPa and the strain in [%]; an example is the stress of gyroid in fill was 19.167 MPa while the average strain was 2.7833 % at 15% infill density. Using a tensile test machine with an optical extensometer, we would like to find out how infilled densities and parameters affect stress and strain. An Anycubic Kobra 3D printer with PLA filament from Anycubic was used for each sample. All the infills in the Ultimaker Cura software are being used.Additive manufacturing techniques are still in a process where further testing is required until we can perfectly control the results through specific instructions in the software. These tests can lead to forces of the required stress and strain, high quality where required, and products that use lower amounts of infills but still have high stress/strain. The main purpose is to further understand the forces we observe with every infill and independently analyze the stress and strain outputs. This will also lead to lower material usage in the FDM printing technology when a product is prepared.Two tests are designed to support the results and decision process, the tests have different properties such as layer height, wall layer counts, infill density, and top and bottom layer thickness. The tests with different properties were analyzed to check the best results and find the most suitable material effect and force difference due to material densities, wall thickness, and other properties. These properties show large differences in results, such as a 20% strain increase in the Quarter cubic infill. The highest strain was observed in concentric infill with 30% infill.

Abstract: Nowadays, there is a spike in 3D printing and additive manufacturing technology all over the world. Starting from the prototype state to the final production process, a high demand is noticed due to the fact that this technology is rapid, economical and good-fit for finding out the mechanical behavior of the material and the structure. Thermoplastic polyurethane (TPU) is widely used in automotive industry, sport industry, medical industry, even in footwear industry. High abrasion resistance, shear strength, elasticity with low-temperature performance make TPU widely used and so important. In this study, we focused on the effect of infill pattern and density in mechanical behavior of 3D printed TPU part. We controlled the density and pattern both resulting in changing mechanical properties, helping us reduce the use of material, cost and production time accordingly. It is necessary to prepare a database on the test results, which can help us to understand the parameters related to internal structure or infill pattern of the material.

Abstract: Today's computational capacity enables the use of advanced statistical algorithms to identify relationships between features in high-dimensional data. Additive manufacturing methods are typically complex processes with many variables in both printing parameters and material properties. Consequently, machine learning offers opportunities for process optimization, quality assurance, and innovation in both Material Extrusion and Powder Bed Fusion technologies. The paper reviews the recent findings in machine learning applications for these additive manufacturing techniques, focusing on areas like defect detection, process control, and material property prediction. Key trends reveal that, while machine learning offers promising enhancements for additive manufacturing, challenges remain in data scarcity, model generalization, real-time adaptability. Our findings underscore the potential of machine learning to improve the overall quality of additive manufacturing processes by predicting optimal manufacturing parameters.

Abstract: Generative design (GD) and topology optimization (TO) are two advanced methods that make it possible to design lightweight and high-performance structures for industrial and mechanical needs. This study offers an approach that combines generative design and topology optimization to reach the best possible balance of material efficiency and manufacturability in complex components. By utilizing GD's capacity to provide several design options within predetermined parameters and TO's material distribution methodology, the suggested approach minimizes weight while maximizing structural integrity. To validate the methodology, a case study involving optimization of performance, weight, and manufacturability of a motorcycle triple clamp is discussed in the paper. The study uses ANSYS for TO to create a preliminary efficient design, it then uses Fusion 360's Generative Design tools to develop the design and investigate various manufacturable configurations (additive and subtractive manufacturing). The final design is confirmed by finite element analysis (FEA), which evaluates each alternative's mechanical performance, manufacturability, with significant weight reduction—up to 35%—while preserving manufacturing viability and structural integrity.