Nanoscale Ultrasensitive Temperature Sensing Based on Upconversion Nanoparticles with Lattice Self-Adaptation

Area of Science:

• Materials Science
• Nanotechnology
• Physical Chemistry

Background:

• Upconversion nanoparticles (UCNPs) are crucial for nanoscale temperature sensing.
• Existing methods for enhancing UCNP thermal sensitivity are limited.
• A need exists for efficient strategies to boost UCNP performance in thermometry.

Purpose of the Study:

• To investigate lattice self-adaptation as a novel route for enhancing UCNP thermal sensitivity.
• To demonstrate a significant improvement in temperature sensing performance using this approach.
• To explore the mechanism behind enhanced thermal sensitivity in engineered UCNPs.

Main Methods:

• Fabrication of core/shell NaGdF4/NaYF4 heterojunction upconversion nanoparticles.
• Utilizing the fluorescence intensity ratio (FIR) of Er3+ dopant for temperature indication.
• Analyzing the temperature-dependent changes in lattice distortion at the heterojunction interface.
• Comparing the thermal sensitivity of core-shell UCNPs with lattice self-adaptation to core-only UCNPs.

Main Results:

• A heterojunction interface with temperature-sensitive lattice distortion was successfully created.
• Lattice self-adaptation at the interface led to an additional increase in FIR with rising temperature.
• Core/shell UCNPs with lattice self-adaptation exhibited three times higher thermal sensitivity compared to core-only UCNPs.
• The study demonstrated a remarkable enhancement in UCNP thermometry performance.

Conclusions:

• Lattice self-adaptation provides an efficient and novel strategy for significantly enhancing the thermal sensitivity of upconversion nanoparticles.
• Engineered heterojunctions in UCNPs can unlock new mechanisms for improved nanoscale temperature sensing.
• This work opens new avenues for developing highly sensitive UCNP-based thermometers for various applications.