Mechano-electro-optical conversion dynamics in mechanoluminescence and its application in remote human–robot interaction

Haoliang Cheng; Shuangqiang Fang; Yi Li; Qiangqiang Zhu; Yixi Zhuang; Rongjun Xie; Wei Yan; Ding Zhao; Min Qiu; Le Wang

doi:10.1186/s43074-025-00210-6

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Haoliang Cheng, Shuangqiang Fang, Yi Li, Qiangqiang Zhu, Yixi Zhuang, Rongjun Xie, Wei Yan, Ding Zhao, Min Qiu, Le Wang. Mechano-electro-optical conversion dynamics in mechanoluminescence and its application in remote human–robot interaction[J]. PhotoniX. doi: 10.1186/s43074-025-00210-6

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Mechano-electro-optical conversion dynamics in mechanoluminescence and its application in remote human–robot interaction

doi: 10.1186/s43074-025-00210-6

1.
College of Optics and Electronic Technology, China Jiliang University, Hangzhou, Zhejiang, 310000, China
2.
Fujian Key Laboratory of Surface and Interface Engineering for High Performance Materials, Xiamen University, Xiamen, Fujian, 361000, China
3.
Zhejiang Key Laboratory of 3D Micro/Nano Fabrication and Characterization, Department of Electronic and Information Engineering, School of Engineering, Westlake University, Hangzhou, Zhejiang, 310030, China
4.
Westlake Institute for Optoelectronics, Fuyang, Hangzhou, Zhejiang, 311421, China

Funds: This work was financially supported by National Natural Science Foundation of China (U24A20307; 12304460).

Received Date: 2025-07-11
Accepted Date: 2025-11-05
Rev Recd Date: 2025-10-13

Available Online: 2025-11-18

Abstract

Abstract

Mechanoluminescence (ML) is bringing a paradigm-shifting for next-generation light-based human–robot interaction. However, the overlooked character of ML temporal dynamic response remains a critical barrier to overcoming the limitation of mechano-optical conversion efficiency. Here, by resolving the dynamic interplay among stimuli rate, interfacial charge accumulation and ML performance of three typical materials, like ZnS:Cu²⁺, SrAl₂O₄:Eu²⁺,Dy³⁺, Y₃Al₅O₁₂:Ce³⁺, the cognition of ML has been deeply understand. Obviously, the ML performance is predominantly governed by the cross-coupling of stimuli rate and stimuli time rather than absolute stress magnitude. For the first time, the optimal stretching stimulation rate for commercial ZnS:Cu²⁺, SrAl₂O₄:Eu²⁺,Dy³⁺ and Y₃Al₅O₁₂:Ce³⁺ are respectively determined as ~ 10.3 Mpa/s, ~ 11.0 Mpa/s, ~ 31.9 Mpa/s, which is of great significance for obtaining high-performance ML behavior, and an ubiquitous ML hysteresis phenomenon is demonstrated originating from a time-consuming mechano-electro-optical conversion process even existing in trap-controlled SrAl₂O₄:Eu²⁺,Dy³⁺. Moreover, a qualitative relationship for ML brightness (MLB), stimuli rate (sr), stimuli time (st), inherent interfacial triboelectricity coefficient (iitre) and relative interfacial triboelectricity coefficient (ritre) is established as MLB = f(sr)*g(st)*p(iitre)*q(ritre) for guiding the design of ML elastomers. For instance, based on this equation, a topology-optimized Y₃Al₅O₁₂:Ce³⁺@polydimethylsiloxane (PDMS) elastomer is engineered, achieving unprecedented 693 times brighter emission, 78% lower stress threshold and 20% lighter weight, which is successfully applied in remote control (~ 450 m) of quadruped robot. Three main contributions of this work include: (i) demonstrating the influence law of temporal dynamic stimulation on ML performance. (ii) resolving long-standing mechano-optical asynchrony debates. (iii) establishing a universal guideline for designing high-performance ML platforms.
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- Mechanoluminescence')">" data-track="click" data-track-action="view keyword" data-track-label="link">Mechanoluminescence,
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- Mechano-electro-optical conversion')">" data-track="click" data-track-action="view keyword" data-track-label="link">Mechano-electro-optical conversion,
- Engineering",
- Temporal dynamic response')">" data-track="click" data-track-action="view keyword" data-track-label="link">Temporal dynamic response,
- Engineering",
- Remote human-robot interaction')">" data-track="click" data-track-action="view keyword" data-track-label="link">Remote human-robot interaction

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References(52)

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