Super elastic and negative triboelectric polymer matrix for high performance mechanoluminescent platforms
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Mechanoluminescence platforms, combining phosphors with elastic polymer matrix, have emerged in smart wearable technology due to their superior elasticity and mechanically driven luminescent properties. However, their luminescence performance often deteriorates under extreme elastic conditions owing to a misinterpretation of polymer matrix behavior. Here, we unveil the role of the polymer matrices in mechanoluminescence through an interface-triboelectric effect driven by elasticity, achieving both high elasticity and brightness. By investigating interactions between elastic polymers and copper doped zinc sulfide microparticles, we reveal that elasticity significantly governed triboelectric effects for mechanoluminescence. In particular, high negative triboelectricity emerged as the key to overcoming poor triboelectric effect in extreme elastic conditions. This led to the discovery of polybutylene adipate-co-terephthalate silane and polycarbonate silane, achieving remarkable elasticity over 100% and a brightness of 139 cd/m2. These findings offer fundamental insights to select the optimal polymer matrix based on systematic parameters for various smart wearable applications.
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Acknowledgements: H.I.J. acknowledges support from the Institute of Information & Communications Technology Planning & Evaluation (IITP), funded by the Korean government (MSIT) (No. 2020-0-01373, Artificial Intelligence Graduate School Program, Hanyang University), and the research fund of Hanyang University (HY-2023). H.S.J., H.S., W.H.J., and H.C. acknowledge funding from the National Research Foundation of Korea (NRF) (Grant No. NRF-2023R1A2C1003824, NRF-2022R1A2C1002764, NRF-2021M3H4A1A02049634, and RS-2024-00436187). H.I.J., H.S.J., and H.C. acknowledge support from LG Display under the LGD-Hanyang University Incubation Program (Grant No. C2022008311). S.D.S. acknowledges funding from the Royal Society and Tata Group (Grant No. UF150033).
Funder: This work was partly supported by an Institute of Information & Communications Technology Planning & Evaluation (IITP) grant funded by the Korean government (MSIT) (No. 2020-0-01373, Artificial Intelligence Graduate School Program (Hanyang University)) and the research fund of Hanyang University (HY-2023).
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LG Display (C2022008311)
Royal Society (UF150033)

