Harnessing Superelasticity for Efficient Load Transfer in NiTi–Graphene Composites

Abstract Conventional metal–graphene composites cannot fully utilize the high elastic limit of graphene, because metal matrices deform plastically below 1% strain, whereas graphene remains elastic up to 30%. Shape memory alloys such as NiTi accommodate recoverable strains of 8–10% through a stress-induced martensitic transformation, making them well-suited matrices for graphene reinforcement. A ternary second nearest neighbor modified embedded-atom method (2NN MEAM) potential for the Ni–Ti–C system is developed and applied in molecular dynamics simulations of NiTi–graphene composites. The simulations show that the martensitic transformation is preserved and that graphene reinforcement increases the transformation stress in both single-crystal and polycrystalline NiTi. Higher graphene content improves strength but introduces a residual strain that accumulates on cycling. Atomistic analysis shows that this residual strain arises not from a large untransformed matrix fraction, but from irreversible graphene microcracking at peak load, selective matrix intrusion into the crack openings, and localized interfacial martensite trapping. Local transformation stretch tensor analysis shows that reinforcement preserves the B2-to-B19′ path, forming a 50:50 ratio of a (001) compound twin pair continuous across the sheets, with the coherent interfaces showing no preference as nucleation sites. Overall, lattice strain matching enables efficient load transfer to the graphene, enhancing strength while retaining recoverable deformation.