Multiple Linear Regression-Enhanced RGB-based Luminescence Thermometry for High-sensitivity Thermal Readout

Abstract

The practical implementation of phosphors for luminescence-based thermal sensing and imaging requires simple, user-friendly approaches that enable convenient and sensitive temperature readout. To the best of our knowledge, this is the first demonstration of combining RGB-based thermal imaging using a conventional digital camera with multiple linear regression (MLR) to achieve straightforward and highly sensitive temperature determination and spatially resolved thermal imaging. Importantly, the implementation of the MLR approach enhances the relative sensitivity by more than 3-fold, compared with conventional analysis based solely on the G/R or B/R intensity ratios. The application of Ca3Al2O6:Mn2+-Ce3+ as a luminescent temperature probe, in which the intensity ratio between the Ce3+ and Mn2+ emission bands exhibits a pronounced temperature dependence, enables temperature readout through several complementary approaches. These include conventional luminescence intensity ratio thermometry (SR = 1.46% K-1), analysis of the CIE 1931 chromaticity coordinates (SRx = 0.45% K-1 and SRy = 0.14% K-1), as well as RGB-based thermal sensing and imaging using a digital camera. This multimodal optical response, together with the accessibility of camera-based readout and the substantial sensitivity enhancement enabled by MLR, establishes a practical strategy for spatially resolved luminescence thermometry.