Stiff Shape Memory Polymers for High-Resolution Reconfigurable Nanophotonics

Autor:	Wang Zhang, Hao Wang, Alvin T. L. Tan, Anupama Sargur Ranganath, Biao Zhang, Hongtao Wang, John You En Chan, Qifeng Ruan, Hailong Liu, Son Tung Ha, Dong Wang, Venkat K. Ravikumar, Hong Yee Low, Joel K. W. Yang
Rok vydání:	2022
Předmět:	Photons Smart Materials Polymers Mechanical Engineering Printing General Materials Science Bioengineering General Chemistry Condensed Matter Physics Nanostructures
Zdroj:	Nano Letters. 22:8917-8924
ISSN:	1530-6992 1530-6984
DOI:	10.1021/acs.nanolett.2c03007
Popis:	Reconfigurable metamaterials require constituent nanostructures to demonstrate switching of shapes with external stimuli. Yet, a longstanding challenge is in overcoming stiction caused by van der Waals forces in the deformed configuration, which impedes shape recovery. Here, we introduce stiff shape memory polymers. This designer material has a storage modulus of ∼5.2 GPa at room temperature and ∼90 MPa in the rubbery state at 150 °C, 1 order of magnitude higher than those in previous reports. Nanopillars with diameters of ∼400 nm and an aspect ratio as high as ∼10 were printed by two-photon lithography. Experimentally, we observe shape recovery as collapsed and touching structures overcome stiction to stand back up. We develop a theoretical model to explain the recoverability of these sub-micrometer structures. Reconfigurable structural color prints with a resolution of 21150 dots per inch and holograms are demonstrated, indicating potential applications of the stiff shape memory polymers in high-resolution reconfigurable nanophotonics.
Databáze:	OpenAIRE
Externí odkaz:	https://explore.openaire.eu/search/publication?articleId=doi_dedup___::eb25cb1225499fd8fd93d3ba963816e0 https://doi.org/10.1021/acs.nanolett.2c03007 Zobrazit plný text záznamu