Physics-based Models for photonic thermometers

Published

December 1, 2022

Author(s)

Zeeshan Ahmed

Abstract

Resistance thermometry, meticulously developed over the last century, provides a time-tested method for taking temperature measurements. However, fundamental limits to resistance-based approaches along with a desire to reduce the cost of sensor ownership, increase sensor stability and meet the growing needs of emerging economy has produced considerable interest in developing photonic temperature sensors. In this study we utilize Della- Corte-Varshni treatment for thermo-optic coefficient to derive models for temperature-wavelength relationships in ring resonators and Fiber Bragg gratings. Model evaluation is carried out using a Bayesian framework that selects models for superior outof- sample predictive accuracy whilst minimizing model complexity. Our work presents physics-based framework for photonic thermometry calibration functions, putting constraints on model complexity and parameter bounds, pointing the way towards a reference function that can be utilized for future standardization and inter-comparison of photonic thermometers.

Citation

Sensors and Actuators A: Physical

Pub Type

Journals

Download Paper

https://doi.org/10.1016/j.sna.2022.113987

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Keywords

bayesian, photonic thermometry, reference function, metrology

Citation

Ahmed, Z. (2022), Physics-based Models for photonic thermometers, Sensors and Actuators A: Physical, [online], https://doi.org/10.1016/j.sna.2022.113987, https://tsapps.nist.gov/publication/get_pdf.cfm?pub_id=935151 (Accessed October 9, 2024)