Artificial visual sensors (AVSs) with bio-inspired sensing and neuromorphic signal processing are essential for next-generation intelligent systems. Conventional optoelectronic devices employed in AVSs operate discretely in terms of sensing, processing, and memorization, and not ideal for applications necessitating shape deformation to achieve wide fields-of-view and deep depths-of-field. Here, we present stretchable artificial visual sensors (S-AVS) capable of concurrently sensing and processing optical signals while adapting to shape deformations. Specifically, these S-AVSs use a stretchable transistor structure with a meticulously engineered photosensitive semiconductor layer, comprising an organic semiconductor, thermoplastic elastomer, and cesium lead bromide quantum dots (CsPbBr₃ QDs). They exhibit synaptic behaviors such as excitatory postsynaptic current (EPSC) and paired-pulse facilitation (PPF) under optical signals, maintaining functionality under 30% strain and repeated stretching. The nonlinear response and fading memory effect support in-sensor reservoir computing, achieving image recognition accuracies of 97.46% and 97.1% at 0% and 30% strain, respectively.

Artificial synaptic devices hold great potential in building neuromorphic computers. Due to the unique morphological features, two-dimensional organic semiconductors at the monolayer limit show interesting properties when acting as the active layers for organic field-effect transistors. Here, organic synaptic transistors are prepared with 1,4-bis ((5’-hexyl-2,2’-bithiophen-5-yl) ethyl) benzene (HTEB) monolayer molecular crystals. Functions similar to biological synapses, including excitatory postsynaptic current (EPSC), pair-pulse facilitation, and short/long-term memory, have been realized. The synaptic device achieves the minimum power consumption of 4.29 fJ at low drain voltage of −0.01 V. Moreover, the HTEB synaptic device exhibits excellent long-term memory with 10⁹ s EPSC estimated retention time. Brain-like functions such as dynamic learning-forgetting process and visual noise reduction are demonstrated by nine devices. The unique morphological features of the monolayer molecular semiconductors help to reveal the device working mechanism, and the synaptic behaviors of the devices can be attributed to oxygen induced energy level. This work shows the potential of artificial neuroelectronic devices based on organic monolayer molecular crystals.

Artificial synaptic devices with the functions of emulating important biological synaptic behaviors are playing an increasingly important role in the development of neuromorphic computing systems. Single-walled carbon nanotubes (SWCNTs) with excellent electrical properties and high stability have been studied as active materials for synaptic devices. However, the performance of optical synaptic devices (OSDs) based on pure SWCNTs is limited by the weak light absorption property. Herein, bismuth triiodide (BiI₃), an environmentally stable and friendly optoelectronic material, is firstly combined with SWCNTs to fabricate OSDs with decent properties of perceiving and memorizing optical information. The OSDs can exhibit typical synaptic behaviors including excitatory postsynaptic current, paired-pulse facilitation, and short/long-term memory. Distinctively, the photo-response of the OSD is independent of pulse light wavelength in the range of 365 to 650 nm, different from most of the previously reported OSDs, which usually have wavelength-dependent photo-response. Temperature- dependent photo-response behaviors of the devices are investigated. Importantly, the OSD without encapsulation holds good excitatory post-synaptic current (EPSC) behavior after being stored in the ambient environment for 170 days, indicating reliable environmental stability. Furthermore, an OSD array with nine synaptic devices is employed to mimic the human visual perception and memory functions. These results suggest the feasibility of BiI₃/SWCNTs-based OSDs for the simulation of human visual memory.