Atomik Defekt Aracılı Yük Hapsi, Sensör İçi Nöromorfik Vizyon İçin Van Der Waals Heteroyapılarda Çok Modlu Plastisiteyi Mümkün Kılıyor

Özet (abstract)

Abstract Neuromorphic hardware that unifies sensing, memory, and learning at the device level remains challenging due to limited optoelectronic comodulation and rigid architectures. Here, we report a flexible, van der Waals (vdW)-integrated MoS2/hexagonal boron nitride (h-BN)/graphene memtransistor in which defect-mediated interfacial charge trapping enables gate-tunable, multimodal synaptic plasticity under combined optical and electrical stimuli. The device reproduces short- and long-term plasticity, multilevel optical memory, and Pavlovian associative learning via repeated optical–electrical stimulus pairing. It exhibits an on/off ratio exceeding 108, low-energy optical switching (138.6 pJ per event), and stable operation after 1000 bending cycles (<1.4% variation). Implemented in a hybrid optoelectronic neural network, the device achieves 96.03% accuracy on the MNIST benchmark, closely approaching ideal software performance. These results establish defect-mediated charge trapping in vdW heterostructures as a scalable route to flexible, in-sensor neuromorphic vision, where perception, memory, and learning converge for next-generation adaptive sensing systems.

Yazarların özeti; kaynağından alınmıştır. Nano Letters, 2026 · DOI ↗