Less is more: dimensionality reduction as a general strategy for more precise luminescence thermometry.

ABSTRACT: Thermal resolution (also referred to as temperature uncertainty) establishes the minimum discernible temperature change sensed by luminescent thermometers and is a key figure of merit to rank them. Much has been done to minimize its value via probe optimization and correction of readout artifacts, but little effort was put into a better exploitation of calibration datasets. In this context, this work aims at providing a new perspective on the definition of luminescence-based thermometric parameters using dimensionality reduction techniques that emerged in the last years. The application of linear (Principal Component Analysis) and non-linear (t-distributed Stochastic Neighbor Embedding) transformations to the calibration datasets obtained from rare-earth nanoparticles and semiconductor nan

SUBMITTER: Ximendes E 

PROVIDER: S-EPMC9329371 | biostudies-literature | 2022 Jul

REPOSITORIES: biostudies-literature