A Dual-Excitation Decoding Strategy Based on NIR Hybrid Nanocomposites for High-Accuracy Thermal Sensing

Abstract

Optical thermal sensing holds great promise for disease theranostics. However, traditional ratiometric thermometry methods, in which intensity ratio of two nonoverlapping emissions is defined as the thermosensitive parameter, may have a limited accuracy in temperature read-out due to the deleterious interference from wavelength- and temperature-dependent photon attenuation in tissue. To overcome this limitation, a dual-excitation decoding strategy based on NIR hybrid nanocomposites comprising self-assembled quantum dots (QDs) and Nd3+ doped fluoride nanocrystals (NCs) is proposed for thermal sensing. Upon excitation at 808 nm, the intensity ratio of two emissions at identical wavelength (1057 nm) from QDs and NCs, respectively, is defined as the thermometric parameter R. By employing another 830 nm laser beam following the same optical path as 808 nm laser to exclusively excite QDs, the two overlapping emissions can be easily decoded. The acquired R proves to be inert to the detection depth in tissue, with a minimized temperature reading error of ≈2.3 °C at 35 °C (at a depth of ≈1.1 mm), while the traditional thermometry mode based on the nonoverlapping 1025 and 863 nm emissions may exhibit a large error of ≈43.0 °C. The insights provided by this work pave the way toward high-accuracy deep-tissue biosensing.