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High-resolution Thermal Micro-imaging Using Europium Chelate Luminescent Coatings

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Luminescence-enabled three-dimensional temperature bioimaging.

Liyan Ming^1,2,3, Anna Romelli⁴, José Lifante^1,2

¹Nanomaterials for Bioimaging Group (nanoBIG), Departamento de Física de Materiales, Facultad de Ciencias, Universidad Autónoma de Madrid, Madrid, Spain.

Nature Communications

|July 11, 2025

Summary

This summary is machine-generated.

Researchers developed a novel 3D luminescence thermometry method using Ag2S nanothermometers and machine learning. This breakthrough enables 3D thermal imaging, overcoming limitations of current 2D approaches for biological sensing.

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Area of Science:

Nanotechnology
Biophysics
Machine Learning

Background:

Luminescence thermometry offers remote, high-resolution thermal imaging.
Current methods are limited to 2D thermal imaging, hindering 3D heat diffusion analysis.
A robust 3D luminescence thermometry technique is needed for advanced biological studies.

Purpose of the Study:

To develop a credible method for extracting 3D thermal images using luminescence.
To combine Ag2S nanothermometers with machine learning for 3D thermal sensing.
To overcome the limitations of existing 2D luminescence thermometry.

Main Methods:

Utilized silver sulfide (Ag2S) nanothermometers for temperature sensing.
Employed machine learning algorithms, specifically optimized neural networks.
Leveraged spectral distortions caused by temperature and tissue photon extinction.

Main Results:

Successfully extracted 3D thermal images from complex nanothermometer patterns.
Demonstrated the method's efficacy for in vivo luminescence thermometry.
The algorithm accurately reconstructed 3D temperature distributions.

Conclusions:

The developed method provides the first credible approach for 3D luminescence thermometry.
This technique significantly advances 3D thermal imaging capabilities in biological systems.
Has broad implications for 3D sensing applications in biology and beyond.