2017
DOI: 10.1016/j.snb.2016.09.186
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Fluorescence sensor array based on amino acid derived carbon dots for pattern-based detection of toxic metal ions

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Cited by 153 publications
(63 citation statements)
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“…This behavior was also reflected in the three-dimensional spectrum ( Figure S2 ), which exhibited three emission peaks, one characteristic peak at 450 nm and two weak scattering peaks over 300–400 nm. In addition, the QY of MR-CDs was calculated to be 18%, which was comparable to those of most amino acid-derived CDs reported previously [ 38 , 39 , 40 ].…”
Section: Resultssupporting
confidence: 84%
“…This behavior was also reflected in the three-dimensional spectrum ( Figure S2 ), which exhibited three emission peaks, one characteristic peak at 450 nm and two weak scattering peaks over 300–400 nm. In addition, the QY of MR-CDs was calculated to be 18%, which was comparable to those of most amino acid-derived CDs reported previously [ 38 , 39 , 40 ].…”
Section: Resultssupporting
confidence: 84%
“…1,2 With a diameter less than 10 nm and abundant hydrophilic functional groups on their surface, 3 C-dots can easily cross cellular membranes 4,5 and, therefore, are considerably attractive for bio-imaging and theranostics applications. More importantly, compared with the traditional metal quantum dot material, C-dots containing no heavy metals 6 are thought to be more environmentally friendly and should be safer for biological use. Despite this, C-dots should still be scrutinized for their safety before their wide application.…”
Section: Introductionmentioning
confidence: 99%
“…To develop an efficient metal ion discrimination model based on chemometrics, we used LDA for the colorimetric responses of this sensor array against metal ions. LDA, which is one of the best‐known supervised pattern recognition methods, recognizes the group to which a new unknown analytes belongs. In this multivariate data analysis method, samples with known class identities (12 kinds of metal ions) were used for training.…”
Section: Resultsmentioning
confidence: 99%