Аннотация:This study explores the effects of minor chemical structure modifications on the thermometric performance of a novel mixed-metal complex [Tb0.94Eu0.06L3(TPPO)2] (HL – 4,4,4-trifluoro-1-(furan-2-yl)butan-1,3-dione, TPPO – triphenylphosphine oxide). By replacing NO3− with an HL− anion, we observed a significant enhancement in the complex's luminescent properties, including a shift in the high-sensitivity temperature range from 250 K to 150 K and a 3.3-fold increase in the relative thermal sensitivity (Sr). The modified behavior of the charge transfer (CT) state improved the energy transfer efficiency between Eu3+ and Tb3+ ions. Additionally, a convolutional neural network (CNN) was employed to analyze temperature-dependent luminescence data under real-world conditions, yielding superior accuracy and precision to conventional methods. This combination of structure variation and machine learning advances the potential of luminescent thermometers in real-world applications.
