Breaking the Intrinsic Strength-Ductility Tradeoff in Graphene-Metal Composites

Small carbon materials, such as graphene, offer excellent mechanical strength. Micro/nano carbon materials are often dispersed into a metal matrix to form bulk composites with mechanical enhancement. Despite technical progress, such composites intrinsically suffer from a trade-off condition between strength and ductility because the load transfer path forms between mechanically strong yet chemically inert micro/nano carbon materials or between the carbon-metal interfaces. In other words, conventional carbon and metal composites become stronger with increasing carbon contents, but the weak interfaces also increase, leading to premature failure. In this regard, crucial advances are presented toward breaking the strength-ductility trade-off condition by utilizing Axially bi-Continuous Graphene-Nickel (ACGN) wires. This innovative ACGN achieves excellent combined strength and ductility-the highest among the current Ni-, Al-, and Cu-based carbon-enhanced metal matrix composites. For example, the ultimate strength and failure strain of 25-mu m-diameter ACGN wires are improved by 71.76% and 58.24%, compared to their counterparts. The experimental and theoretical analyses indicate that the graphene-nickel interplay via their axially bi-continuous structure is the main underlying mechanism for the superb mechanical behavior. In specific, the continuous graphene, in addition to effective load-sharing, passivates the free surface of fine wire, forming dislocation pileups along the graphene-nickel interface and, therefore, hindering localized necking. The Axially bi-Continuous Graphene-coated Nickel (ACGN) wires, synthesized via the chemical vapor deposition process, show enhanced mechanical properties (up to 71.76% and 58.24% higher ultimate tensile strength and failure strain, respectively) and break the intrinsic strength-ductility trade-off in conventional carbon-metal composites. This study has discussed the detailed strengthening mechanisms. image