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A research team led by Professor Nae-Eung Lee from the Department of Advanced Materials Science and Engineering at Sungkyunkwan University (President: Juy-Beom Yoo) has developed an intelligent artificial tactile receptor^* array^*, inspired by the human tactile perception system and mimicking the function and structure of biological synapses. Based on this achievement, the team has also implemented a new intelligent sensor platform.

* Tactile receptor: A sensory component that detects external stimuli (such as pressure, vibration, or temperature) and converts them into action potentials to be transmitted to the brain.

* Array: A structure composed of multiple elements designed to operate collectively, rather than as a single unit.

The importance and role of artificial intelligence (AI) have recently garnered attention across all industrial sectors. In particular, Physical AI is emerging as a core foundational technology for autonomous systems in future industries. In Physical AI, data input begins with sensors, and accordingly, active research is underway on intelligent sensor technologies that mimic the high-performance signal processing mechanisms of the human somatosensory system, enabling efficient processing of sensor data.

This study focused on how the human sensory system initially processes information - specifically, on the "synapse-like structure" between sensory receptors and nerve endings. Inspired by both slowly adapting (Merkel) and fast adapting (Pacinian) tactile receptors in human skin, the research team developed an integrated platform that combines 16 sensory array and synaptic transistors, incorporating both types of adaptive responses.

This platform integrates a triboelectric sensor layer, designed to resemble a human fingerprint, with synaptic transistors that can memorize and respond to stimuli as all-in-one structure. It is capable of simultaneously recognizing both slow and fast stimuli.

Experimental results demonstrated that the sensor naturally modulates synaptic weights in response to variations in the intensity, frequency, and type of mechanical stimuli. Notably, the system was able to recognize textures and surface patterns with over 90% accuracy using less than 10% of the total data, indicating significantly higher data processing efficiency compared to conventional technologies.

Such sensors, which incorporate AI functionality directly into the sensing mechanism itself, are characterized by ultra-low voltage and ultra-low power operation with high efficiency. They open new technological possibilities across various fields, including intelligent robotics, neuromorphic sensory systems, and wearable electronic skin. In particular, their ability to process environmental data at the sensor level positions them as a key enabling technology for the future development of high-speed, energy-efficient autonomous AI systems.

This research was supported by the Ministry of Science and ICT through the Mid-career Researcher Program and the Nano and Material Technology Development Program, as well as by the Ministry of Education through the Basic Research Infrastructure Support Program (Focused Research Institute Support Project). The study was conducted by Seokju Hong (integrated M.S.-Ph.D. student), Dr. Yurim Lee, and Dr. Atanu Bag as co-first authors, under the supervision of Professor Nae-Eung Lee as the corresponding author.

The results of this research were published on April 28, 2025, in Nature Materials, the world’s leading journal in the field of materials science.

※Title: Bio-inspired artificial mechanoreceptors with built-in synaptic functions for intelligent tactile skin

※Journal: Nature Materials

※Authors: Nae-Eung Lee(Corresponding author), Seokju Hong, Yurim Lee, Atanu Bag (co-first authors), Hyosoo Kim, Trang Quang Trung, M Junaid Sultan, Dong-bin Moon (co authors)

Development of Ultra-high Efficiency, Ultra-low Power, Intelligent Artificial Tactile Receptors Mimicking Slowly and Fast Adapting Tactile Receptors

(from left) Nae-Eung Lee(Corresponding author), Seokju Hong, Yurim Lee, Atanu Bag