3D CNT macrostructure synthesis catalyzed by MgFe2O4 nanoparticles—A study of surface area and spinel inversion influence - Université Toulouse III - Paul Sabatier - Toulouse INP Accéder directement au contenu
Article Dans Une Revue Applied Surface Science Année : 2017

3D CNT macrostructure synthesis catalyzed by MgFe2O4 nanoparticles—A study of surface area and spinel inversion influence

Résumé

The MgFe2O4 spinel exhibits remarkable magnetic properties that open up numerous applications in biomedicine, the environment and catalysis. MgFe2O4 nanoparticles are excellent catalyst for carbon nanotube (CNT) production. In this work, we proposed to use MgFe2O4 nanopowder as a catalyst in the production of 3D macroscopic structures based on CNTs. The creation of these nanoengineered 3D architectures remains one of the most important challenges in nanotechnology. These systems have high potential as supercapacitors, catalytic electrodes, artificial muscles and in environmental applications. 3D macrostructures are formed due to an elevated density of CNTs. The quantity and quality of the CNTs are directly related to the catalyst properties. A heat treatment study was performed to produce the most effective catalyst. Factors such as superficial area, spinel inversion, crystallite size, degree of agglomeration and its correlation with van der Waals forces were examined. As result, the ideal catalyst properties for CNT production were determined and high-density 3D CNT macrostructures were produced successfully.
Fichier principal
Vignette du fichier
Zampiva_20460.pdf (15.38 Mo) Télécharger le fichier
Origine : Fichiers produits par l'(les) auteur(s)
Loading...

Dates et versions

hal-01907321 , version 1 (29-10-2018)

Identifiants

Citer

Rúbia Young Sun Zampiva, Claudir Gabriel Kaufmann Junior, Juliano Schorne-Pinto, Priscila Chaves Panta, Annelise Kopp Alves, et al.. 3D CNT macrostructure synthesis catalyzed by MgFe2O4 nanoparticles—A study of surface area and spinel inversion influence. Applied Surface Science, 2017, 422, pp.321-330. ⟨10.1016/j.apsusc.2017.06.020⟩. ⟨hal-01907321⟩
40 Consultations
34 Téléchargements

Altmetric

Partager

Gmail Facebook X LinkedIn More