Bioinspired Artificial Mechanoreceptors With Builtin Synaptic Functions For Intelligent Tactile Skin Seok Ju Hong Yu Rim Lee Atanu Bag Hyo Soo Kim Tran Quang Trung M Junaid Sultan Dongbin Moon Naeeung Lee by Seok Ju Hong & Yu Rim Lee & Atanu Bag & Hyo Soo Kim & Tran Quang Trung & M. Junaid Sultan & Dong-bin Moon & Nae-eung Lee 101038/S4156302502204Y instant download after payment.

Tactile perception involves the preprocessing of signals from slowly adapting and fast-adapting aferent neurons, which exhibit synapse-like interactions between mechanoreceptors and their dendrites or terminals, transmitting signals to the brain. Emulating these adaptation and sensory memory functions is crucial for artifcial tactile sensing systems. Here, inspired by human tactile aferent systems, we present an array of artifcial synaptic mechanoreceptors with built-in synaptic functions by vertically integrating synaptic transistors with a reduced graphene oxide channel, an ionogel gate dielectric and an elastomeric fngerprint-like receptive layer in an all-in-one platform. Triboelectric-capacitive gating between the receptive layer and gate dielectric in response to tactile stimulation governs excitatory post-synaptic current patterns, enabling slowly adapting and fast-adapting characteristics for signal preprocessing. The artifcial synaptic mechanoreceptor array demonstrated handwriting style, surface pattern and texture discrimination via machine learning using fused slowly adapting and fast-adapting post-synaptic values, ofering high data efciency and potential for intelligent skin.