This is the authors' abstract. We don't add key points for this paper.
BackgroundBio-inspired high-entropy alloys (Bio-HEAs) are emerging as materials for orthopedic implants because of their high strength, corrosion resistance, compositional flexibility, and biocompatibility. Their tunable mechanical properties may reduce elastic mismatch with bone and mitigate stress shielding and implant loosening.ObjectiveThis review evaluates Bio-HEAs for orthopedic applications, emphasizing elastic modulus tailoring, stress-shielding mitigation, microstructural control, biological response, and mathematical modeling.MethodsLiterature on Bio-HEAs for biomedical applications was reviewed, focusing on composition-structure-property relationships, elastic modulus, phase stability, biological response, and computational approaches. Experimental findings were considered alongside molecular dynamics (MD), continuum elasticity, partial differential equation (PDE)-based approaches, and finite element method (FEM) simulations.ResultsReported Bio-HEAs exhibit elastic moduli ranging approximately from 10 to 30 GPa, providing opportunities to reduce mechanical mismatch with cortical bone. Atomic size mismatch, lattice distortion, phase constitution, and microstructural features influence elastic behavior. MD, continuum models, and FEM provide complementary insights across length scales, while integrated multiscale approaches can improve implant-level predictions and support patient-specific design.ConclusionBio-HEAs offer potential for mechanically compatible orthopedic implants. Integrating materials design with multiscale mathematical modeling may enable improved control of elastic behavior, stress distribution, and implant performance, although experimental validation and clinically relevant modeling are required.
Answers are grounded in this paper and cite their sources.
No takes yet. Share an insight, caveat, or question.
Zeeshan et al. (2026) studied this question.
Synapse has enriched 10 related papers. Consider them for comparative context: