2026/07/16 by An Gui, Yutao Song, T F Li +7 · 1 voice
Computer Science · Engineering · Materials Science · #2D Materials and Applications #Advanced Memory and Neural Computing #Neural Networks and Reservoir Computing
paper · pdf · doi:10.1002/smm2.70096
openalex publication_date 2026/07/16 · openalex created_date 2026/07/17 · openalex updated_date 2026/07/18
ABSTRACT Machine vision systems in real‐world applications require devices capable of adapting to multiple operational modes, including high‐sensitivity photodetection, neuromorphic synaptic behavior, and optical memory. However, integrating these distinct optoelectronic functionalities into a single device presents a challenge due to their conflicting requirements for photoresponse time and retention. Here, a gate‐programmable multifunctional transistor based on a MoS 2 /MAPbBr 3 van der Waals (vdW) heterostructure is fabricated. By using the gate field to tune the interfacial electric field and trapping/release kinetics associated with shallow‐ and deep‐level states, the device can be programmed to operate as a photodetector, synaptic transistor, and gate‐bias‐assisted multilevel optical memory. Under a positive gate voltage ( V G ), a pronounced photogating effect enables photodetection with responsivity ( R ) of ∼2397 A/W. At V G = –20 V, the device switches to synaptic mode. At a more negative gate bias, the device enters a gate‐bias‐assisted optical‐memory mode under sustained gate bias. To illustrate the utility of this programmable multifunctionality, frequency‐encoded image recognition is demonstrated with 96.4% accuracy. In addition, a device‐enabled reservoir‐computing (RC) scheme with software‐assisted readout improves classification accuracy by ~20% through deep delay‐based processing. This work demonstrates a multimodal transistor architecture that integrates multiple optoelectronic functions in a single device and suggests a compact hardware route toward adaptive in‐sensor optical information processing.