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Light-Controlled Mechanical Self-Assembly for Programmable Surface Micro-Nano Patterning

delete2025-05-15
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PRE
AI
Z
Zhi‐Qi Dong
X
Xiang, Rui-Jia
Z
Zhao, Tian-Yu
Z
Zhou, Jun-Feng
Y
Yang, Fan
M
Meng, Guang
Z
Zhang, Wen-Ming
DOI:10.1002/smtd.202500319delete
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Abstract

Abstract

En 中文
Mechanical self-assembly is a novel manufacturing principle for programmable surface micro-nano patterning, which can be accurately triggered by interface stress mismatch-induced surface instability and regulated by high-precision boundary constraints. However, existing mechanical self-assembly fabrication strategies for micro-nano surface patterns face challenges in microfabrication compatibility and industrial repeatability. Here, a microfabrication-compatible light-controlled mechanical self-assembly is proposed for programmable and industrially standardized micro-nano surface patterning. By introducing light-controlled high spatial resolution soft-constraint boundaries and surface instability-induced mechanical self-assembly into film/substrate systems, a develop-free and industrially standardized manufacturing process with microfabrication compatibility is demonstrated. Moreover, trans-scale patterns spanning from 5 to 1000 mu m, 2D highly-ordered patterns, and dynamic patterns mimicking Chinese pandas eating bamboo are achieved. Design criteria for programmablely fabricating trans-scale patterns and the mechanical mechanism of orderliness evolutions in 2D self-assembly under arbitrary exposure angles are explained. Furthermore, by applying the highly-ordered micro-nano patterns, a new self-adaptive wideband gas detection system based on tunable micro-gratings is developed and methane is detected. This study can advance strategies for programmable surface micro-nano patterns and lay the foundation for the applications of surface functional devices.
Keywords:
light-controlled mechanical self-assembly
mechanical mechanism of orderliness evolutions in 2D self-assembly
programmable surface micro-nano patterning
self-adaptive wideband gas detection system

Journal

Small Methods cover
Small Methods
IF:
9.1
Papers:
4.3K
Citations:
2.2W

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