On-line carbon dots synthesis using flow injection analysis. Application to aluminium determination in water samples

Por favor, use este identificador para citar o enlazar este ítem: http://hdl.handle.net/10045/131982
Información del item - Informació de l'item - Item information
Título: On-line carbon dots synthesis using flow injection analysis. Application to aluminium determination in water samples
Autor/es: Uriarte, Damián | Gómez, Natalia | Canals, Antonio | Domini, Claudia E. | Garrido, Mariano
Grupo/s de investigación o GITE: Espectroscopía Atómica-Masas y Química Analítica en Condiciones Extremas
Centro, Departamento o Servicio: Universidad de Alicante. Departamento de Química Analítica, Nutrición y Bromatología | Universidad de Alicante. Instituto Universitario de Materiales
Palabras clave: Carbon dots | On-line synthesis | Aluminium determination | Flow system
Fecha de publicación: 8-feb-2023
Editor: Elsevier
Cita bibliográfica: Talanta Open. 2023, 7: 100192. https://doi.org/10.1016/j.talo.2023.100192
Resumen: An on-line synthesis of CDots is proposed for the first time, using the flow injection analysis (FIA) technique, which was coupled, in a single system, to the analytical determination of aluminium in water samples. The nanoparticles were obtained from the carbonization of glucose and iron(III) in an acidic medium, and their photoluminescence increased in the presence of aluminium ions. Under optimal experimental conditions, the proposed method has shown an acceptable linearity range –between 0.04 and 3.0 mg L−1 (R2 = 0.9999) – and a detection limit of 0.007 mg L−1. The analysis of drinking water and groundwater samples showed good accuracy (recoveries ranged between 91 – 113%) and RSD% < 13. The on-line system exhibited a high sample throughput (36 h−1), since no incubation time was required.
Patrocinador/es: Financial support from Universidad Nacional del Sur (PGI 24/Q099 and 24/Q123, CONICET 11220200102603CO, CONICET 11220200103198CO and the ANPCyT PICT-2019-04458 (2021-2023) is gratefully acknowledged. This research was part of the Ph.D. thesis of Damian Uriarte, which was supported by a doctoral grant funded by Consejo Nacional de Investigaciones Científicas y Técnicas (CONICET). M. Garrido and C.E. Domini wish to thank CONICET.
URI: http://hdl.handle.net/10045/131982
ISSN: 2666-8319
DOI: 10.1016/j.talo.2023.100192
Idioma: eng
Tipo: info:eu-repo/semantics/article
Derechos: © 2023 The Authors. Published by Elsevier B.V. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).
Revisión científica: si
Versión del editor: https://doi.org/10.1016/j.talo.2023.100192
Aparece en las colecciones:INV - SP-BG - Artículos de Revistas

Archivos en este ítem:
Archivos en este ítem:
Archivo Descripción TamañoFormato 
ThumbnailUriarte_etal_2023_TalantaOpen.pdf3,19 MBAdobe PDFAbrir Vista previa


Este ítem está licenciado bajo Licencia Creative Commons Creative Commons