Going Above and Beyond: A Tenfold Gain in the Performance of Luminescence Thermometers Joining Multiparametric Sensing and Multiple Regression


Luminescence thermometry has substantially progressed in the last decade, rapidly approaching the performance of concurrent technologies. Performance is usually assessed through the relative thermal sensitivity, S-r, and temperature uncertainty, delta T. Until now, the state-of-the-art values at ambient conditions do not exceed maximum S-r of 12.5% K-1 and minimum delta T of 0.1 K. Although these numbers are satisfactory for most applications, they are insufficient for fields that require lower thermal uncertainties, such as biomedicine. This has motivated the development of materials with an improved thermal response, many of them responding to the temperature through distinct photophysical properties. This paper demonstrates how the performance of multiparametric luminescent thermometers can be further improved by simply applying new analysis routes. The synergy between multiparametric readouts and multiple linear regression makes possible a tenfold improvement in S-r and delta T, reaching a world record of 50% K-1 and 0.05 K, respectively. This is achieved without requiring the development of new materials or upgrading the detection system as illustrated by using the green fluorescent protein and Ag2S nanoparticles. These results open a new era in biomedicine thanks to the development of new diagnosis tools based on the detection of super-small temperature fluctuations in living specimens.




Optics; Physics, Applied; Physics, Condensed Matter


Maturi, FE; Brites, CDS; Ximendes, EC; Mills, C; Olsen, B; Jaque, D; Ribeiro, SJL; Carlos, LD

nossos autores


This work was developed within the scope of the projects CICECO-Aveiro Institute of Materials (UIDB/50011/2020 and UIDP/50011/2020) and Shape of Water (PTDC/NAN-PRO/3881/2020) financed by Portuguese funds through the FCT/MEC and when appropriate co-financed by FEDER under the PT2020 Partnership Agreement. This project has received funding from the European Union's Horizon 2020 research and innovation programme under the Marie Sklodowska-Curie Grant Agreement No. 823941. The support of the European Union's Horizon 2020 FET Open program under Grant Agreement No. 801305 (NanoTBTech) is also acknowledged. F.E.M. acknowledges the financial support from the Brazilian agency FAPESP (Process No. 15/50382-2).

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