Emerging carbon-based spintronic materials: A comprehensive review

Abstract

Spintronics has emerged as a new frontier that unlocks the possibilities beyond charge-based electronics by exploiting both charge and spin of the electron. The realization of spintronic functionalities depends upon the design and optimization of spintronic materials. This comprehensive review critically analyses the evolution of spintronic materials from traditional magnetic heavy metals to promising quantum compatible low dimensional carbon-based platforms. Early spintronics was primarily based on ferromagnetic metals, viz., Iron and Cobalt, enabling giant and tunnel magnetoresistance devices. Later on, quantum materials, such as topological insulators and magnetic semiconductors, have been introduced, exhibiting spin-momentum locking, strong spin-orbit effect, and tunable spin-charge coupling. Despite a solid foundation for spin-dependent transport and spin-orbit phenomena, these spintronic materials face challenges, including short spin diffusion lengths (< 1 µm), energy dissipation, and low temperature magnetic stability. To overcome the above constraints, the carbon-based materials, particularly graphene and graphene nanoribbons (GNRs), have emerged as promising alternatives. Incidentally, graphene exhibits exceptional carrier mobility (~2×105 cm2/Vs), long spin diffusion lengths exceeding 10 μm, and weak intrinsic spin-orbit coupling, offering coherent and efficient transport in ultrafast spin architectures. In addition, GNRs also provide finite band gaps and spin-polarized edge states, enabling tunable spin-logic functionalities. Furthermore, in GNR based systems, the coherent spin manipulation can be achieved by integrating structural tunability, chemical functionalization, and field modulation for designing spin qubits in quantum computing devices. The emergence of carbon-based materials triggers a major paradigm shift in spintronics, showing the pathway towards the next generation scalable, non-volatile, and low power information processing technologies.