Spin memristors are a class of materials that can store memories through the control of spins, potentially leading to novel technologies that address the constraints of standard silicon electronics, thereby facilitating the advancement of more intelligent and energy-efficient computing systems. In this work, we present a spin memristor based on antiferromagnetic materials that exhibit nonlinear Hall memristance. Moreover, the nonlinear Edelstein effect gives rise to memory through the accumulation of magnetic moments associated with the spin of the electrons. We provide a generic symmetry-based analysis that supports the viability of the effect. To achieve a concrete realization of these ideas, we focus on CuMnAs, an antiferromagnetic material which has attracted attention due to its nonlinear response capabilities.

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• Electrical properties
• 2-dimensional systems
• Memristors
• Mean field theory
• Tight-binding model