Concepedia

TLDR

Luminescent nanothermometers enable contactless thermal readings, yet achieving high‑sensitivity infrared sensing for in‑vivo, time‑resolved subcutaneous imaging remains a challenge. This study aims to create supersensitive infrared nanothermometers for subcutaneous thermal imaging. The authors engineer core/shell LaF₃ nanoparticles doped with rare earth ions (Er, Tm, Yb) to achieve this sensitivity. The resulting nanoparticles reach a record 5 % °C⁻¹ sensitivity, enabling subcutaneous thermal video acquisition in a living animal and revealing tissue properties that could inform new diagnostic tools.

Abstract

Some of the old and unrealizable dreams of biomedicine have become possible thanks to the appearance of novel advanced materials such as luminescent nanothermometers, nanoparticles capable of providing a contactless thermal reading through their light emission properties. Luminescent nanothermometers have already been demonstrated to be capable of in vivo subcutaneous punctual thermal reading but their real application as diagnosis tools still requires demonstrating their actual capacity for the acquisition of in vivo, time‐resolved subcutaneous thermal images. The transfer from 1D to 2D subcutaneous thermal sensing is blocked in the last years mainly due to the lack of high sensitivity luminescent nanothermometers operating in the infrared biological windows. This work demonstrates how core/shell engineering, in combination with selective rare earth doping, can be used to develop supersensitive infrared luminescent nanothermometers. Erbium, thulium, and ytterbium core–shell LaF 3 nanoparticles, operating within the biological windows, provide thermal sensitivities as large as 5% °C −1 . This “record” sensitivity has allowed for the final acquisition of subcutaneous thermal videos of a living animal. Subsequent analysis of thermal videos allows for an unequivocal determination of intrinsic properties of subcutaneous tissues, opening the venue to the development of novel thermal imaging‐based diagnosis tools.

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