Fluorescent carbon quantum dots (CDs) are synthesized and employed as fluorescent nanochemosensors for selective detection of amino acids. A detailed investigation of excitation−emission maps revealed that the fluorescence properties of CDs are intensely and strongly influenced by the interaction at the surface with different amino acids. The discrimination capability was demonstrated by tensor rank decomposition of the differences induced by the surface reaction in the excitation−emission maps and by means of a common machine learning approach based on artificial neural networks.

Carbon Quantum Dots as Fluorescence Nanochemosensors for Selective Detection of Amino Acids

Tuccitto, Nunzio
Primo
;
Fichera, Luca;Ruffino, Roberta;Cantaro, Valentina;Sfrazzetto, Giuseppe Trusso;Li-Destri, Giovanni;Licciardello, Antonino;Torrisi, Alberto
2021-01-01

Abstract

Fluorescent carbon quantum dots (CDs) are synthesized and employed as fluorescent nanochemosensors for selective detection of amino acids. A detailed investigation of excitation−emission maps revealed that the fluorescence properties of CDs are intensely and strongly influenced by the interaction at the surface with different amino acids. The discrimination capability was demonstrated by tensor rank decomposition of the differences induced by the surface reaction in the excitation−emission maps and by means of a common machine learning approach based on artificial neural networks.
2021
nanoparticles, amino acids, machine learning, sensors, chemospecific
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/20.500.11769/508465
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