Stress-engineered 0.34 nm graphene memristors for low-power probabilistic computing
Memristors are promising for neuromorphic computing electronics, yet scaling is hindered by the difficulty of fabricating ordered nanoscale electrodes. Here, we report an angstrom-scale graphene-edge memristor with a geometrically defined 0.34 × 0.34 nm2 crossed-electrode area. Key to this achievement is our stress-dis...
Yanming Liu, Jinzhu Li, Zhoujie Pan et al.
· Nature Communications · 0 citations