Suppressing Photothermal Artifacts in Flexible Fluorescent Fiber-Optic Sensors for Accurate and Precise In Situ Temperature Monitoring.

Sijie Su, Jinjian Yu, Pengyuan Dong, Xin Wang, Jing Lyu, Jiulin Gan, Enhai Song, Qinyuan Zhang

Abstract read

In one paragraph

Article in Advanced science (Weinheim, Baden-Wurttemberg, Germany), 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

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3 · Its place in the literature

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4 · The record

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5 · Who and what money

Authors and funding

8 authors.

Sijie SuState Key Laboratory of Luminescent Materials and Devices, Guangdong Provincial Key Laboratory of Fiber Laser Materials and Applied Techniques, South China University of Technology, Guangzhou, China.

Jinjian YuState Key Laboratory of Luminescent Materials and Devices, Guangdong Provincial Key Laboratory of Fiber Laser Materials and Applied Techniques, South China University of Technology, Guangzhou, China.

Pengyuan DongGuangdong Energy Group Science and Technology Research Institute Co., Ltd., Guangzhou, China.

Xin WangState Key Laboratory of Luminescent Materials and Devices, Guangdong Provincial Key Laboratory of Fiber Laser Materials and Applied Techniques, South China University of Technology, Guangzhou, China.

Jing LyuState Key Laboratory of Luminescent Materials and Devices, Guangdong Provincial Key Laboratory of Fiber Laser Materials and Applied Techniques, South China University of Technology, Guangzhou, China.

Jiulin GanSchool of Materials and Engineering, Guangdong Engineering Technology Research and Development Center of Special Optical Fiber Materials and Devices, South China University of Technology, Guangzhou, China.ORCID https://orcid.org/0000-0001-9842-0510

Enhai SongState Key Laboratory of Luminescent Materials and Devices, Guangdong Provincial Key Laboratory of Fiber Laser Materials and Applied Techniques, South China University of Technology, Guangzhou, China.ORCID https://orcid.org/0000-0003-1666-0532

Qinyuan ZhangState Key Laboratory of Luminescent Materials and Devices, Guangdong Provincial Key Laboratory of Fiber Laser Materials and Applied Techniques, South China University of Technology, Guangzhou, China.ORCID https://orcid.org/0000-0001-6544-4735

Funding

Distinguished Youth Foundation of Guangdong Scientific Committee 2023B1515020059National Natural Science Foundation of China 52322208

6 · The paper itself

Abstract

Ratiometric flexible fluorescent fiber-optic sensors, featuring self-calibration and precise spatial localization, are emerging as a robust platform for in situ thermal monitoring, advancing applications such as battery safety management and biomedical diagnostics. However, measurement artifacts induced by the inherent photothermal effect remain largely overlooked, posing a challenge to high-accuracy temperature sensing. Here, we propose a partial-inner-cladding optical fiber (PICOF) to suppress photothermal artifacts by isolating the sensing layer from the coupling interface and the fiber core, where self-heating predominantly occurs. Compared with conventional fiber structures, the PICOF extends the allowable excitation power from ≤ 15 to 61 mW and improves the luminescence signal-to-noise ratio from 36.6 to 42 dB, enabling high-fidelity readout with a relative standard deviation below 0.09% even under power fluctuations and deformation disturbances. Consequently, the LuVO

Indexed as

fiber‐optic sensorfluorescent thermometryin situ detectionphotothermal effectprecision temperature sensing

Identifiers

PMID42829937

DOI10.1002/advs.78130

PMCPMC13634573

What OpenQuestion holds

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.