Paraffin‐Enabled Superlattice Customization for a Photostimulated Gradient‐Responsive Artificial Reflex Arc

Author:

Zhang Weifeng1,Wu Mengwei2,Zhang Yan1,Yan Hongyi3,Lee Yangjin45,Zhao Zihan1,Hao He1,Shi Xiaohu1,Zhang Zhaoxian6,Kim Kwanpyo45,Liu Nan1ORCID

Affiliation:

1. Beijing Key Laboratory of Energy Conversion and Storage Materials College of Chemistry Beijing Normal University Beijing 100875 P. R. China

2. College of Engineering Peking University Beijing 100871 China

3. Department of Physics Beijing Normal University Beijing 100875 P. R. China

4. Center for Nanomedicine Institute for Basic Science Seoul 03722 South Korea

5. Department of Physics Yonsei University Seoul 03722 South Korea

6. College of Design and Engineering National University of Singapore 9 Engineering Drive 1, #07‐26, EA Singapore 117575 Singapore

Abstract

AbstractThe development of photostimulated‐motion artificial reflex arcs — a neural circuit inspired by light‐driven motion reflexes — holds significant promises for advancements in robotic perception, navigation, and motion control. However, the fabrication of such systems, especially those that accommodate multiple actions and exhibit gradient responses, remains challenging. Here, a gradient‐responsive photostimulated‐motion artificial reflex arc is developed by integrating a programmable and tunable photoreceptor based on folded MoS2 at different twist angles. The twisted folded bilayer MoS2 used as photoreceptors can be customized via the transfer technique using patternable paraffin, where the twist angle and fold‐line could be controlled. The photoluminescence (PL) intensity is 3.7 times higher at a twist angle of 29° compared to that at 0°, showing a monotonically decreasing indirect bandgap. Through tunable interlayer carrier transport, photoreceptors fabricated using folded bilayer MoS2 at different twist angles demonstrate gradient response time, enabling the photostimulated‐motion artificial reflex arc for multiaction responses. They are transformed to digital command flow and studied via machine learning to control the gestures of a robotic hand, showing a prototype of photostimulated gradient‐responsive artificial reflex arcs for the first time. This work provides a unique idea for developing intelligent soft robots and next‐generation human–computer interfaces.

Funder

Natural Science Foundation of Beijing Municipality

National Natural Science Foundation of China

Thousand Young Talents Program of China

Fundamental Research Funds for the Central Universities

National Research Foundation of Korea

Institute for Basic Science

Innovative Research Group Project of the National Natural Science Foundation of China

Publisher

Wiley

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