Neural Networks Push the Limits of Luminescence Lifetime Nanosensing.

Luminescence lifetime-based sensing is ideally suited to monitor biological systems due to its minimal invasiveness and remote working principle. Yet, its applicability is limited in conditions of low signal-to-noise ratio (SNR) induced by, e.g., short exposure times and presence of opaque tissues. Herein this limitation is overcome by applying a U-shaped convolutional neural network (U-NET) to improve luminescence lifetime estimation under conditions of extremely low SNR. Specifically, the prowess of the U-NET is showcased in the context of luminescence lifetime thermometry, achieving more precise thermal readouts using Ag2 S nanothermometers. Compared to traditional analysis methods of decay curve fitting and integration, the U-NET can extract average lifetimes more precisely and consistently regardless of the SNR value. The improvement achieved in the sensing performance using the U-NET is demonstrated with two experiments characterized by extreme measurement conditions: thermal monitoring of free-falling droplets, and monitoring of thermal transients in suspended droplets through an opaque medium. These results broaden the applicability of luminescence lifetime-based sensing in fields including in vivo experimentation and microfluidics, while, hopefully, spurring further research on the implementation of machine learning (ML) in luminescence sensing.

Thermoresponsive Polymeric Nanolenses Magnify the Thermal Sensitivity of Single Upconverting Nanoparticles.

Lanthanide-based upconverting nanoparticles (UCNPs) are trustworthy workhorses in luminescent nanothermometry. The use of UCNPs-based nanothermometers has enabled the determination of the thermal properties of cell membranes and monitoring of in vivo thermal therapies in real time. However, UCNPs boast low thermal sensitivity and brightness, which, along with the difficulty in controlling individual UCNP remotely, make them less than ideal nanothermometers at the single-particle level. In this work, it is shown how these problems can be elegantly solved using a thermoresponsive polymeric coating. Upon decorating the surface of NaYF4 :Er3+ ,Yb3+ UCNPs with poly(N-isopropylacrylamide) (PNIPAM), a >10-fold enhancement in optical forces is observed, allowing stable trapping and manipulation of a single UCNP in the physiological temperature range (20-45 °C). This optical force improvement is accompanied by a significant enhancement of the thermal sensitivity- a maximum value of 8% °C+1 at 32 °C induced by the collapse of PNIPAM. Numerical simulations reveal that the enhancement in thermal sensitivity mainly stems from the high-refractive-index polymeric coating that behaves as a nanolens of high numerical aperture. The results in this work demonstrate how UCNP nanothermometers can be further improved by an adequate surface decoration and open a new avenue toward highly sensitive single-particle nanothermometry.

Correction: Perspectives for Ag2S NIR-II nanoparticles in biomedicine: from imaging to multifunctionality.

Correction for 'Perspectives for Ag2S NIR-II nanoparticles in biomedicine: from imaging to multifunctionality' by Yingli Shen, et al., Nanoscale, 2019, DOI: 10.1039/c9nr05733a.