Elisa Ortiz-Rivero, Katarzyna Prorok, Riccardo Marin, Artur Bednarkiewicz, Daniel Jaque, Patricia Haro-González
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Unlocking Single-Particle Multiparametric Sensing: Decoupling Temperature and Viscosity Readouts through Upconverting Polarized Spectroscopy.
Upconverting particles (UCPs), renowned for their capability to convert infrared to visible light, serve as invaluable imaging probes. Furthermore, their responsiveness to diverse external stimuli holds promise for leveraging UCPs as remote multiparametric sensors, capable of characterizing medium properties in a single assessment. However, the utility of UCPs in multiparametric sensing is impeded by crosstalk, wherein distinct external stimuli induce identical alterations in UCP luminescence, hindering accurate interpretation, and yielding erroneous outputs. Overcoming crosstalk requires alternative strategies in upconverting luminescence analysis. In this study, it is shown how a single spinning NaYF4:Er3+, Yb3+ upconverting particle enables simultaneous and independent readings of temperature and viscosity. This is achieved by decoupling thermal and rehological measurements-employing the luminescence of thermally-coupled energy levels of Er3+ ions for thermal sensing, while leveraging the polarization of luminescence from non-thermally coupled levels of Er3+ ions to determine viscosity. Through simple proof-of-concept experiments, the study validates the capability of a single spinning UCP to perform unbiased, simultaneous temperature, and viscosity sensing, thereby opening new avenues for advanced sensing in microenvironments.
Small MethodsMaterials Science-General Materials Science
CiteScore
17.40
自引率
1.60%
发文量
347
期刊介绍:
Small Methods is a multidisciplinary journal that publishes groundbreaking research on methods relevant to nano- and microscale research. It welcomes contributions from the fields of materials science, biomedical science, chemistry, and physics, showcasing the latest advancements in experimental techniques.
With a notable 2022 Impact Factor of 12.4 (Journal Citation Reports, Clarivate Analytics, 2023), Small Methods is recognized for its significant impact on the scientific community.
The online ISSN for Small Methods is 2366-9608.