Ultra‐Low‐Power and Reconfigurable Optoelectronic Memtransistor Based on Vertical Nb‐WSe 2 /Te van der Waals Heterostructure

ABSTRACT The development of high‐performance neuromorphic computing hardware is a key pathway to overcome the Von Neumann architecture's energy efficiency bottleneck. Among these hardware solutions, reconfigurable and low‐power synaptic memtransistors are regarded as promising candidates for building high‐energy‐efficiency brain‐like systems. Here, we fabricated an ultra‐low‐power, reconfigurable optoelectronic memtransistor using a vertical Nb‐doped WSe 2 (Nb‐WSe 2 )/Te van der Waals (vdW) heterostructure. Under optical stimulation, the device can reproducibly emulate paired‐pulse facilitation, short‐term plasticity, and long‐term plasticity, offering programmable AND/OR logic via combined photoelectronic control. Critically, the single‐pulse energy consumption can decrease below 1 aJ, demonstrating excellent energy efficiency for optoelectronic synapses (about 4 orders of magnitude lower than that of the biological synapse). Utilizing wavelength‐selective light pulses, we further emulate Pavlovian associative learning, highlighting the device's capability for multimodal synaptic conditioning. Finally, when used as the building block of a convolutional neural network (CNN), the memtransistor array achieves 92.32% accuracy on the CIFAR‐10 benchmark. It retains 72.75% accuracy under multilevel noise, demonstrating strong classification performance and robustness. These results indicate that Nb‐WSe 2 /Te vdW memtransistors are a promising candidate for constructing ultra‐low‐power, reconfigurable neuromorphic and brain‐inspired computing hardware.