HfO 2 -based memristive synapses with asymmetrically extended p-n heterointerfaces for highly energy-efficient neuromorphic hardware

, a large built-in potential, and extremely low saturation current density under reverse bias. Ultralow conductance modulation is controlled by tuning p-n heterointerface's energy-barrier height through electro-ionic charge migration. This materials-engineering strategy addresses energy consumption and variability in existing memristors, opening a pathway toward energy-efficient neuromorphic computing systems.