A theoretical framework for optical thermometry based on excited-state absorption and lifetimes of Eu3+ compounds

Blois, Lucca; Neto, Albano N. Carneiro; Malta, O.L.; Brito, Hermi F.

doi:10.1016/j.jlumin.2022.119039

Cited by 7 publications

(2 citation statements)

References 31 publications

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“…Although new classes of thermographic phosphors have been reported, for example, covalent organic frameworks (COFs), [149,150] single-ion magnets, [151][152][153][154][155] and low-dimensional ns 2 metal halides, [156,157] we perceive a gradual shift in the emphasis on the technique. Research efforts are now focused on establishing comprehensive theoreti-cal backgrounds [158][159][160][161][162][163][164] and standardization procedures [44,165] (in measurement methodologies, data acquisition and processing, and classification, Table 1), discussing the reliability, repeatability, and reproducibility of the technique, [107,[166][167][168][169][170][171][172] employing artificial intelligence (AI) algorithms to improve data analysis, [173][174][175] and developing new applications (see Table 2 for selected examples).…”

Section: Energy Transfer Drivenmentioning

confidence: 99%

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Spotlight on Luminescence Thermometry: Basics, Challenges, and Cutting‐Edge Applications

et al. 2023

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Luminescence (nano)thermometry is a remote sensing technique that relies on the temperature dependency of the luminescence features (e.g., bandshape, peak energy or intensity, and excited state lifetimes and risetimes) of a phosphor to measure temperature. This technique provides precise thermal readouts with superior spatial resolution in short acquisition times. Although luminescence thermometry is just starting to become a more mature subject, it exhibits enormous potential in several areas, e.g., optoelectronics, photonics, micro‐ and nanofluidics, and nanomedicine. This work reviews the latest trends in the field, including the establishment of a comprehensive theoretical background and standardized practices. The reliability, repeatability, and reproducibility of the technique are also discussed, along with the use of multiparametric analysis and artificial‐intelligence algorithms to enhance thermal readouts. In addition, examples are provided to underscore the challenges that luminescence thermometry faces, alongside the need for a continuous search and design of new materials, experimental techniques, and analysis procedures to improve the competitiveness, accessibility, and popularity of the technology

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Section: Energy Transfer Drivenmentioning

confidence: 99%

“…is close to 100% if ∆E 21 ≫ k B T. There are, however, creative ways how to yet increase the relative sensitivity with a retained appreciable response by using more than two thermally coupled levels [159,163,238,239] or the application of multi-regression models (Section 5). [174,240]…”

Section: Ratiometric Readout Schemementioning

confidence: 99%