Maskless Femtosecond‐Laser‐Processed Ionotronic Double‐Gate Transistor Array for Pattern Adaptation Emulation

Author:

Zhang Yi1,Pei Jiaqing1,Huang Zhuohui1,Jiang Leyong2,Yin Kai1,Jiang Jie1ORCID

Affiliation:

1. Hunan Key Laboratory of Nanophotonics and Devices Hunan Key Laboratory of Super Microstructure and Ultrafast Process School of Physics Central South University Changsha Hunan 410083 China

2. School of Physics and Electronics Hunan Normal University Changsha Hunan 410081 China

Abstract

AbstractSensory adaptation is a very important function of the biological nervous system to maintain survival. It helps us to better perceive, understand, and adapt to the environment. Therefore, building artificial sensory adaptation systems through neuromorphic devices is a goal that humans have been continuously pursuing. Unfortunately, current research has either based on individual adaptive devices or employed complex processes. At present, a facile fabrication of adaptive device arrays is still a great challenge. Herein, a maskless ionotronic double‐gate oxide transistor array with pattern adaptation function is demonstrated using femtosecond laser process. Such process is a maskless patterning technology and free of chemical contamination, enabling a facile integration of device arrays. The as‐fabricated transistor exhibits a low subthreshold swing of 265 mV dec−1 and a reasonable current switching ratio of ≈103 under a low operating voltage of 1 V. Interestingly, it can achieve a transition from nonadaptive to adaptive behavior by the other gate terminal. Moreover, the desensitization behavior after adaptation can be realized for mimicking the self‐protection capability of biological sensory systems. Finally, a 2 × 2 transistor array is demonstrated for emulating the experience‐dependent pattern adaptation ability in the human brain. Therefore, this adaptive device array using femtosecond laser process may provide a good opportunity for the artificial sensory adaptation systems and the next‐generation bionic robots.

Funder

National Natural Science Foundation of China

National Key Research and Development Program of China

Science Fund for Distinguished Young Scholars of Hunan Province

Publisher

Wiley

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