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Going Above and Beyond: A Tenfold Gain in the Performance of Luminescence Thermometers Joining Multiparametric Sensing and Multiple Regression
Author(s) -
Maturi Fernando E.,
Brites Carlos D. S.,
Ximendes Erving C.,
Mills Carolyn,
Olsen Bradley,
Jaque Daniel,
Ribeiro Sidney J. L.,
Carlos Luís D.
Publication year - 2021
Publication title -
laser and photonics reviews
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 3.778
H-Index - 116
eISSN - 1863-8899
pISSN - 1863-8880
DOI - 10.1002/lpor.202100301
Subject(s) - luminescence , biomedicine , thermal , computer science , materials science , nanoparticle , sensitivity (control systems) , nanotechnology , optoelectronics , statistics , mathematics , physics , thermodynamics , electronic engineering , bioinformatics , biology , engineering
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, δ 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 δ 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 δ 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 Ag 2 S 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.