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Ratiometric Temperature Sensing with Semiconducting Polymer Dots

Open access
Ye, Fangmao, Wu, Changfeng, Jin, Yuhui, Chan, Yang-Hsiang, Zhang, Xuanjun, Chiu, Daniel T.·2011·Journal of the American Chemical Society

Abstract

This communication describes ultrabright single-nanoparticle ratiometric temperature sensors based on semiconducting polymer dots (Pdots). We attached the temperature sensitive dye-Rhodamine B (RhB), whose emission intensity decreases with increasing temperature-within the matrix of Pdots. The as-prepared Pdot-RhB nanoparticle showed excellent temperature sensitivity and high brightness because it took advantage of the light harvesting and amplified energy transfer capability of Pdots. More importantly, the Pdot-RhB nanoparticle showed ratiometric temperature sensing under a single wavelength excitation and has a linear temperature sensing range that matches well with the physiologically relevant temperatures. We employed Pdot-RhB for measuring intracellular temperatures in a live-cell imaging mode. The exceptional brightness of Pdot-RhB allows this nanoscale temperature sensor to be used also as a fluorescent probe for cellular imaging.

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Metadata

Authors
Ye, F., Wu, C., Jin, Y., Chan, Y.-H., Zhang, X., & Chiu, D. T.
Venue
Journal of the American Chemical Society
Published
2011-05-11
Volume
133
Issue
21
Pages
8146-8149
ISSN
  • 0002-7863 (ISSN-L)
  • 1520-5126
OpenAlex
W2146560584
Cited by
390
References
0
FWCI
14.72
Type
journal article
Language
en
Open access
green

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CoChat. (2026). Citation check: Ratiometric Temperature Sensing with Semiconducting Polymer Dots. https://app.cochat.ai/papers/10.1021/ja202945g
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Ye, F., Wu, C., Jin, Y., Chan, Y.-H., Zhang, X., & Chiu, D. T. (2011). Ratiometric Temperature Sensing with Semiconducting Polymer Dots. Journal of the American Chemical Society. https://doi.org/10.1021/ja202945g

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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.