Desenvolvimento de um sensor fotoeletroquímico para determinação de ácido cafêico empregando nanomateriais

• Autor(a) principal: BOTELHO, Chirlene Nascimento
• Data de Publicação: 2019
• Tipo de documento: Dissertação
• Idioma: por
• Título da fonte: Biblioteca Digital de Teses e Dissertações da UFMA
• Texto Completo: https://tedebc.ufma.br/jspui/handle/tede/tede/2861
• topic: Sensor fotoeletroquímico; Ácido cafêico; Dióxido de titânio; Nanotubos de carbono; Pontos quânticos; Telureto de cádmio; photoelectrochemical sensor; Caffeic acid; Titanium dioxide; Carbon nanotubes; Quantum dots; Cadmium telluride; Química Inorgânica

Caffeic acid (CA) is a compound of natural origin that presents antioxidant activities and anti-inflammatories of great importance to the human organism. In this sense, the present work aims the development of a photoelectrochemical sensor based on nanoparticles of titanium dioxide and carbon nanotubes (TiO2/CNTs), sensitized with cadmium telluride quantum dots (QDsCdTe) for the determination of this phenolic compound. The photosensor was denominated TiO2/CNTs/QDsCdTe/FTO and exhibited a high photocurrent in the presence of CA under visible LED light, compared to each component of the composite material. The characterization at the materials was performed by X-ray diffraction (XRD), scanning electron microscopy (SEM), cyclic voltammetry (CV), electrochemical impedance spectroscopy (EIS), and amperometry. Under optimized experimental and operational conditions the proposed photosensor shaved a linear response range of 0.5 to 360 μmol L-1 and a detection limit of 0.15 μmol L-1. The selectivity of the electrochemical photosensor was tested, in different species that may be present in samples containing the CA, which showed that this sensor is promising for the detection of this phenolic compound in presence of other species. Finally, the sensor was successfully applied for the determination of CA in samples of tea and granulated soluble coffee, presenting recovery values for the analyte of 96.15% and 101.32%, respectively good accuracy.