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Transforming glucose into fluorescent graphene quantum dots via microwave radiation for sensitive detection of Al3+ ions based on aggregation-induced enhanced emission.
Yao, Maomao; Huang, Jinkun; Deng, Zihao; Jin, Wenying; Yuan, Yali; Nie, Jinfang; Wang, Hua; Du, Fuyou; Zhang, Yun.
Afiliação
  • Yao M; College of Chemistry and Bioengineering, Guilin University of Technology, Guilin 541004, P. R. China. zy@glut.edu.cn Niejinfang@glut.edu.cn.
Analyst ; 145(21): 6981-6986, 2020 Oct 26.
Article em En | MEDLINE | ID: mdl-32857828
ABSTRACT
This paper initially describes a nanosensor for fluorescence detection of Al3+ ions by using graphene quantum dots (GQDs) that are synthesized via microwave-assisted single-step ring-closure condensation of glucose molecules. The one-pot synthesis strategy based on the microwave radiation could be finished in several minutes and no post-modification of the GQDs was required. In particular, the GQD nanoprobes showed a sensitive and specific fluorescence enhancement response to Al3+. The involved mechanism might be the Al3+-mediated aggregation of the GQDs leading to aggregation-induced enhanced emission (AIEE). Under optimal conditions, this new fluorescent nanosensor was able to quantitatively detect Al3+ in a linear concentration range of 0.4-500 µM. The limit of detection was estimated to be ∼59.8 nM according to the 3σ rule, which made it be among the most sensitive systems currently available for sensing the target ion. Moreover, satisfactory recovery results (ranging from 96.8 to 109.7%) of analyzing a set of real water examples additionally validated its accuracy for practical applications. Considering its simplicity, high sensitivity and specificity, low cost, and good reliability, the developed fluorescent nanosensing system for Al3+ holds great promise for broad uses in water safety, environmental monitoring, and waste management.

Texto completo: 1 Base de dados: MEDLINE Tipo de estudo: Diagnostic_studies Idioma: En Ano de publicação: 2020 Tipo de documento: Article

Texto completo: 1 Base de dados: MEDLINE Tipo de estudo: Diagnostic_studies Idioma: En Ano de publicação: 2020 Tipo de documento: Article