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A Novel Technique for Generating and Observing Chemiluminescence in a Biological Setting
Published on: March 9, 2017
Research progress in ratiometric mechanoluminescent materials
Haojin Liu1, Yuan Yin1, Ziyi Guo1
1School of Physics and Opto-Electronic Technology, Collaborative Innovation Center of Rare-Earth Optical Functional Materials and Devices Development, Baoji University of Arts and Sciences, Baoji, Shaanxi 721016, P. R. China. yinyuan8008@126.com.
Dalton Transactions (Cambridge, England : 2003)
|July 20, 2026
Summary
Ratiometric mechanoluminescence (ML) offers reliable optical sensing by overcoming limitations of conventional methods. This review highlights advances in ratiometric ML materials for precise, self-referenced detection and monitoring applications.
Area of Science:
- Materials Science
- Optoelectronics
- Sensing Technology
Background:
- Optical sensing using luminescent materials is vital for detecting various parameters, but conventional methods suffer from reliability issues due to external fluctuations.
- Single-intensity optical sensing is prone to errors from excitation instability, device variations, and environmental interference, limiting quantitative accuracy.
Purpose of the Study:
- To review recent advancements in ratiometric mechanoluminescence (ML) materials and their underlying mechanisms.
- To explore strategies for developing self-referencing optical sensing technologies.
- To discuss applications and future perspectives of ratiometric ML.
Main Methods:
- Summarizing advances in ratiometric ML materials based on crystal-field regulation, trap-level engineering, physical structure design, and multimodal external-field assistance.
- Discussing mechanisms like stress-induced crystal-field modulation, valence-state-dependent emission, carrier dynamics, energy transfer, and triboelectric effects.
- Highlighting representative applications and future research directions.
Main Results:
- Ratiometric ML provides a self-referencing strategy using intensity ratios, lifetime ratios, or color variation, enhancing quantitative reliability.
- Various strategies have been developed to improve the performance and applicability of ratiometric ML materials.
- Applications span flexible electronics, anti-counterfeiting, industrial monitoring, and structural health diagnosis.
Conclusions:
- Ratiometric ML is a promising self-referencing approach for overcoming the limitations of conventional optical sensing.
- Continued research into material design, mechanism understanding, and device integration will drive the development of high-precision, intelligent ML sensing platforms.
- Addressing challenges in material universality, brightness, and standardization is crucial for widespread adoption.
