High strength and low elastic modulus α/β cp-Ti/Ti–33Nb–33Zr multilayered in-situ heterostructure produced by accumulative roll bonding
Source abstract
Abstract
Developing and improving new alloys, primarily Ti-based systems, have been investigated to replace, repair, or reconstruct lost or damaged tissues while balancing relative cost, mechanical properties, corrosion resistance, and biological response. In this context, the main objective of this study was to evaluate the feasibility of producing heterostructured materials (HM) by accumulative roll bonding (ARB) based on two Ti alloys: α-Ti (grade 2) and multi-principal element alloy (MEA) β-Ti Ti-33Nb-33Zr (wt.%), with a combination of high strength and low elastic modulus for implant applications. The main results indicated that producing such heterostructured sheets with up to 7 ARB cycles at 500 °C is feasible. A continuous increase in hardness and a reduction in the elastic modulus were simultaneously observed with the increasing ARB cycles. In both cases, the rule-of-mixtures (considering 1:1 proportion) was not followed, resulting in higher-than-expected hardness and lower-than-expected elastic modulus. Microstructural characterization revealed significant grain refinement and a remarkable increase in dislocation density, which were identified as the primary drivers for the enhanced hardness. The reduction in elastic modulus was attributed to nanograined structure and interdiffusion at the interfaces, as confirmed by TEM analysis. The process successfully produced multilayered composite sheets with a high hardness of over 300 HV and a favorably reduced elastic modulus in the range of 65-89 GPa. Based on these findings, ARB is a very promising technique for producing Ti-based HM for biomedical purposes.
Source: openalex_inverted_index · Quality: baseline
Research context
OpenAlex topics: Titanium Alloys Microstructure and Properties · Microstructure and mechanical properties · Magnesium Alloys: Properties and Applications
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
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