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Polyacrylonitrile/Reduced Graphene Oxide Free-Standing Nanofibrous Membranes for Detecting Endocrine Disruptors

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Autor(es):
Facure, Murilo H. M. ; Mercante, Luiza A. ; Correa, Daniel S.
Número total de Autores: 3
Tipo de documento: Artigo Científico
Fonte: ACS APPLIED NANO MATERIALS; v. 5, n. 5, p. 9-pg., 2022-04-27.
Resumo

Endocrine-disrupting chemicals (EDCs) are emerging pollutants whose uncontrolled release in natural aquatic environments can pose risks to human and animal health. In this scenario, the development of simple, low-cost, and sensitive methods to detect trace amounts of EDCs in the environment is highly sought. In this work, a nanofiber-based sensor was fabricated by functionalizing a polyacrylonitrile (PAN) electrospun nanofibrous membrane with reduced graphene oxide (rGO) to be used as a flexible and free-standing electrode to detect EDCs through electrical impedance measurements. The rGO was obtained from graphene oxide using a hydrothermal route, while the PAN/rGO composite membrane was prepared through vacuum filtration. The rGO provided high electrical conductivity to the membrane, which presented a good performance in the detection of endocrine hormones. The electrical resistance variation enabled the detection of 17 alpha-ethinylestradiol (EE2) in a linear range between 10(-5) and 10(-11) mol L-1. Moreover, by using the principal component analysis (PCA) for data treatment, the sensor was able to discriminate EE2, estrone, estradiol, and progesterone at 100 pmol L-1 in real river water samples. These results open up the possibility to fabricate in a simple way functionalized nanofibrous membranes to be used as sensing material for the detection of varied analytes with high sensitivity and low cost. (AU)

Processo FAPESP: 17/10582-8 - Produção e caracterização de quantum dots de grafeno e sua aplicação em sensores químicos
Beneficiário:Murilo Henrique Moreira Facure
Modalidade de apoio: Bolsas no Brasil - Doutorado
Processo FAPESP: 18/22214-6 - Rumo à convergência de tecnologias: de sensores e biossensores à visualização de informação e aprendizado de máquina para análise de dados em diagnóstico clínico
Beneficiário:Osvaldo Novais de Oliveira Junior
Modalidade de apoio: Auxílio à Pesquisa - Temático