Related Experiment Video
Updated: Oct 18, 2026

High-resolution Thermal Micro-imaging Using Europium Chelate Luminescent Coatings
Published on: April 16, 2017
The Closer, the Better: Engineering RGB Thermometric Performance in Tb3+,Eu3+-Doped MOFs
Maja Szymczak1, Lam T K Giang2, Lukasz Marciniak1
1Institute of Low Temperature and Structure Research, Polish Academy of Sciences, Okólna 2, Wrocław50-422, Poland.
Abstract:
The effectiveness of luminescence thermometry, which exploits temperature-induced changes in the spectroscopic properties of phosphor materials for temperature sensing, has been extensively demonstrated. However, from a practical perspective, monitoring temperature-induced variations in the color of the emitted light offers a considerably more straightforward and user-friendly alternative to conventional spectral analysis. In this context, establishing a clear relationship between the thermal evolution of the emission color and the structure of the phosphor is essential for the rational design of visual luminescence thermometers. In this work, we investigate the correlation between the temperature-dependent emission color and the structural characteristics of Tb3+,Eu3+-co-doped metal-organic frameworks (MOFs), with particular emphasis on their potential for filter-free, camera-based thermal sensing. The obtained results demonstrate that, within the investigated series of materials, decreasing the interionic distance between Eu3+ and Tb3+ ions increases the probability of energy transfer and consequently enhances the thermal sensitivity of the camera-based readout derived from the ratio of luminescence intensities recorded in the blue and red channels. These findings establish a direct relationship between the structural characteristics of the luminescent material, the underlying energy-transfer processes, and its thermometric performance. More broadly, this study provides a foundation for the rational design of visual luminescence thermometers with predefined sensing characteristics, opening a pathway toward structure-guided optimization of filter-free, camera-based thermal sensing platforms.
