In this study epoxy resin/TiO2 nanocomposites have been prepared according to the Reactive Suspension Method, to obtain TiO2 nanoparticles (NPs) covalently bonded to the macromolecular network. After the chemical- physical characterization of both NPs and polymeric matrix, the dynamic-mechanical properties (storage modulus as a function of the temperature) of the nanocomposites have been studied. In particular, the experi- mental storage modulus in the rubbery state has been found significantly higher than the value predicted by the generalized Kerner equation. This has been rationalized considering that the inorganic NPs act as additional cross-linking points, as confirmed by the solid-state NMR investigations, leading to a very high and unexpected increase of the stiffness. Consequently, the experimental data have been also fitted using the Halpin-Tsai equation, which has allowed to obtain suitable predictions of the storage modulus by adjusting the so-called reinforcing geometry factor. By the proposed approach has been possible to incorporate in the Halpin-Tsai model a factor that considers the contribution due to the presence of filler/matrix covalent bonds and to obtain more accurate predictions.

Epoxy resin/TiO2 nanocomposites prepared by the Reactive Suspension Method: Dynamic-mechanical properties and their prediction by theoretical models

Micaela Degli Esposti;Valeria Righi;Paola Fabbri;Davide Morselli
2022

Abstract

In this study epoxy resin/TiO2 nanocomposites have been prepared according to the Reactive Suspension Method, to obtain TiO2 nanoparticles (NPs) covalently bonded to the macromolecular network. After the chemical- physical characterization of both NPs and polymeric matrix, the dynamic-mechanical properties (storage modulus as a function of the temperature) of the nanocomposites have been studied. In particular, the experi- mental storage modulus in the rubbery state has been found significantly higher than the value predicted by the generalized Kerner equation. This has been rationalized considering that the inorganic NPs act as additional cross-linking points, as confirmed by the solid-state NMR investigations, leading to a very high and unexpected increase of the stiffness. Consequently, the experimental data have been also fitted using the Halpin-Tsai equation, which has allowed to obtain suitable predictions of the storage modulus by adjusting the so-called reinforcing geometry factor. By the proposed approach has been possible to incorporate in the Halpin-Tsai model a factor that considers the contribution due to the presence of filler/matrix covalent bonds and to obtain more accurate predictions.
2022
Micaela Degli Esposti; Francesca Bisi; Valeria Righi; Paola Fabbri; Federica Bondioli; Massimo Messori; Davide Morselli
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11585/878823
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