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Mechanoluminescence under High Pressure: Summary and Prospects

ZHAO Tingting LI Mei Peng Shang ZHAO Bohao FENG Qi CHEN Yanlong YUAN Jun Han Yingxue AN Jiao WANG Hao JIANG Sheng LIN Chuanlong

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Mechanoluminescence under High Pressure: Summary and Prospects

ZHAO Tingting, LI Mei, Peng Shang, ZHAO Bohao, FENG Qi, CHEN Yanlong, YUAN Jun, Han Yingxue, AN Jiao, WANG Hao, JIANG Sheng, LIN Chuanlong
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  • Mechanoluminescence (ML) is a phenomenon in which photon emission is produced directly under mechanical stimulation. Owing to its high spatial selectivity, rapid response, and multimodal emission capabilities, ML exhibits great potential for applications in structural health monitoring, intelligent sensing, and optical anti-counterfeiting. However, due to the complexity of ML modes, categories, and underlying kinetic processes, the field still faces several challenges, including the lack of a well-established mechanism, the limited availability of high-performance ML materials, and the absence of standardized testing standards. Existing studies have demonstrated that crystal field strength, band structure, and lattice configuration play crucial roles in governing the ML properties. High-pressure, with its unique ability to tune these physical quantities, undoubtedly provides new pathways for advancing ML research. Recent breakthroughs in rapid loading techniques have further enabled the exploration of ML behaviors under high-pressure conditions. In the GPa pressure range, modulation of interatomic distances, electronic orbitals, and crystal structures has not only allowed effective control over emission intensity and color, but has also enabled the capture of ML kinetic processes over microsecond–second timescales, thereby supplying essential experimental data for revealing the microscopic mechanisms of ML. In this review, we first provide a brief overview of the historical development, classification, and mechanistic understanding of ML, together with commonly employed ML characterization methods under ambient and high-pressure conditions. We then summarize recent progress in the application of high-pressure techniques for optimizing ML performance and elucidating ML mechanisms, highlighting advances in enhancing emission intensity, modulating spectral characteristics, and uncovering dynamic processes. Finally, the future directions and challenges for high-pressure ML research are discussed.
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