Reconfigurable volatile/nonvolatile neuromorphic devices integrate brain-like rapid learning with stable memory, providing a critical pathway toward edge-intelligent systems. The integration of reconfigurable devices and light-emitting functionality transforms the display from a passive output terminal into an integral hub of the intelligent system. However, integrating reconfigurable volatile/nonvolatile memory and light-emitting functionality within a single device remains a major challenge because of the inherent conflicts among multiple functions and the constraints of conventional two-terminal control. Here, for the first time, we present a three-terminal reconfigurable volatile/nonvolatile light-emitting memristor. The three-terminal configuration provides control of the emission region and memory states, enabling seamless transition between volatile, nonvolatile, and light-emission operations. By enabling spatial reconfigurability and temporal multiplexing of emission, the device improves scalability and simplifies system architecture and control, achieving a 69.23% reduction in data-transfer volume and a 40% reduction in system component count compared with separated architectures. In addition, it offers direct visual feedback while facilitating continuous learning in neuromorphic computing systems. Finally, we implement an anomaly-detection visualization system based on the reconfigurable volatile/nonvolatile light-emitting memristor, demonstrating its ability to produce direct visual output while processing information, thus enabling an integrated memory-compute-display architecture for next-generation edge-intelligent display systems.
Yang et al. (Fri,) studied this question.