Graphene oxide (GO) and carbon nanotubes (CNTs) were loaded at different mutual ratios into poly(vinylidene fluoride-co-hexafluoropropylene) (PVDF-co-HFP) matrix and electrospun to construct mats that were assessed as smart sorbents for decontaminating water from methylene blue (MB) pollutant, while ensuring the additional possibility of detecting the dye amounts. The results revealed that sorption capacity enhances upon increasing GO content, which is beneficial to wettability and active area. Equilibrium adsorption of these materials is precisely predicted by the Langmuir isotherm model and the maximum capacities herein achieved, ranging from 120 to 555 mg/g depending on the formulation, are higher than those reported for similar systems. The evolution of the structure and properties of such materials as a function of dye adsorption was studied. The results reveal that MB molecules prompted the increase of electrical conductivity of the samples in a dose-dependent manner. Mats containing solely CNTs, while displaying the worst sorption performance, showed the highest electrical performances, displaying interesting changes in their electrical response as a function of the dye amount adsorbed, with a linear response and high sensitivity (309.4 mu S cm-1 mg-1) in the range 0-235 mu g of dye adsorbed. Beyond the possibility to monitor the presence of small amounts of MB in contaminated water and the saturation state of sorbents, this feature could even be exploited to transform waste sorbents into high-added value products, including flexible sensors for detecting low values of pressure, human motion, and so on.

Scaffaro, R., Maio, A., Gammino, M. (2024). Electrospun polymeric nanohybrids with outstanding pollutants adsorption and electroactivity for water treatment and sensing devices. ADVANCED COMPOSITES AND HYBRID MATERIALS, 7(1) [10.1007/s42114-023-00827-w].

Electrospun polymeric nanohybrids with outstanding pollutants adsorption and electroactivity for water treatment and sensing devices

Scaffaro, Roberto;Maio, Andrea;Gammino, Michele
2024-01-15

Abstract

Graphene oxide (GO) and carbon nanotubes (CNTs) were loaded at different mutual ratios into poly(vinylidene fluoride-co-hexafluoropropylene) (PVDF-co-HFP) matrix and electrospun to construct mats that were assessed as smart sorbents for decontaminating water from methylene blue (MB) pollutant, while ensuring the additional possibility of detecting the dye amounts. The results revealed that sorption capacity enhances upon increasing GO content, which is beneficial to wettability and active area. Equilibrium adsorption of these materials is precisely predicted by the Langmuir isotherm model and the maximum capacities herein achieved, ranging from 120 to 555 mg/g depending on the formulation, are higher than those reported for similar systems. The evolution of the structure and properties of such materials as a function of dye adsorption was studied. The results reveal that MB molecules prompted the increase of electrical conductivity of the samples in a dose-dependent manner. Mats containing solely CNTs, while displaying the worst sorption performance, showed the highest electrical performances, displaying interesting changes in their electrical response as a function of the dye amount adsorbed, with a linear response and high sensitivity (309.4 mu S cm-1 mg-1) in the range 0-235 mu g of dye adsorbed. Beyond the possibility to monitor the presence of small amounts of MB in contaminated water and the saturation state of sorbents, this feature could even be exploited to transform waste sorbents into high-added value products, including flexible sensors for detecting low values of pressure, human motion, and so on.
15-gen-2024
Scaffaro, R., Maio, A., Gammino, M. (2024). Electrospun polymeric nanohybrids with outstanding pollutants adsorption and electroactivity for water treatment and sensing devices. ADVANCED COMPOSITES AND HYBRID MATERIALS, 7(1) [10.1007/s42114-023-00827-w].
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/10447/635655
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