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Carbon Dot-based Inverse-opal Hydrogels with Photoluminescence: Dual-mode Sensing of Solvent and Metal Ions

Abstract

Dual-mode sensing platform, including fluorescence and reflectance modes, have been demonstrated for highly sensitive and selective detection of solvent and metal ions based on carbon dot-based inverse opal hydrogels (CD-IOHs). In this work, CD-IOHs have first been synthesized via the typical templating technique. Two kinds of CDs, including solvent or Cu(II) ions sensitive CDs, have been incorporated into the matrix of IOHs during co-polymerization of acrylic acid (AA) and 2-hydroxyethl methacrylate (HEMA). The CD-IOHs not only show green under daylight but exhibit stable photoluminescence (PL) under UV light owing to the stop-band effect of photonic crystals and the quantum effect of CDs, respectively. By using these two optical phenomena, for solvent sensing, the CD-IOHs change their colors from green, yellow, red, to semitransparent state and show a good linear sensing with the ethanol content from 0 to 45% at reflection mode. While, their PL intensities exhibit a nonlinear detection trend: first increase and then decrease with the ethanol content at fluorescence mode. Remarkably, for metal ions sensing, the CD-IOHs have highly selectivity for Cu(II) ions via using the specific PL quenching effect of Cu(II) ions sensitive CDs. Furthermore, the CD-IOHs show good linear detection at both modes and the wide linear range from 0.1 µM to 7 mM is achieved. Thus, high selectivity, colorimetric detection, broad linear detection range, and dual-mode sensing can be realized based on CD-IOHs.

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Supplementary files

Publication details

The article was received on 09 Jul 2019, accepted on 09 Aug 2019 and first published on 09 Aug 2019


Article type: Paper
DOI: 10.1039/C9AN01287G
Analyst, 2019, Accepted Manuscript

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    Carbon Dot-based Inverse-opal Hydrogels with Photoluminescence: Dual-mode Sensing of Solvent and Metal Ions

    Y. Zhu, J. Wang, X. Zhu, J. Wang, L. Zhou, J. Li, T. Mei, J. Qian, L. Wei and X. Wang, Analyst, 2019, Accepted Manuscript , DOI: 10.1039/C9AN01287G

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