Tailoring an Effective Interface between Nanocellulose and the Epoxidized Linseed Oil Network through Functionalization.
Mădălina I NecolauBrînduşa BălănucăAdriana Nicoleta FroneCelina Maria DamianPublished in: ACS omega (2023)
Sustainable nanocomposite materials based on different functionalized nanocellulose (NC) structures embedded in epoxidized linseed oil (ELO) were developed as foundation toward a greener approach for anticorrosive coating evolution. The work leans on functionalization with (3-aminopropyl) triethoxysilane (APTS), (3-glycidyloxypropyl)trimethoxysilane (GPTS), and vanillin (V) of NC structures isolated from plum seed shells, evaluated as potential reinforcing agents for the increase of thermomechanical properties and water resistance of epoxy nanocomposites from renewable resources. The successful surface modification was confirmed from the deconvolution of X-ray photoelectron spectra for C 1s and correlated with Fourier transform infrared (FTIR) data. The secondary peaks assigned to C-O-Si at 285.9 eV and C-N at 286 eV were observed with the decrease of the C/O atomic ratio. Compatibility and efficient interface formation between the functionalized NC and the biobased epoxy network from linseed oil were translated as decreased values for the surface energy of bio-nanocomposites and better dispersion imaged through scanning electron microscopy (SEM). Thus, the storage modulus of the ELO network reinforced with only 1% APTS-functionalized NC structures reached 5 GPa, an almost 20% increase compared with that of the neat matrix. Mechanical tests were applied to assess an increase of 116% in compressive strength for the addition of 5 wt % NCA to the bioepoxy matrix.
Keyphrases
- electron microscopy
- high resolution
- quantum dots
- reduced graphene oxide
- fatty acid
- carbon nanotubes
- molecularly imprinted
- visible light
- gold nanoparticles
- electronic health record
- magnetic resonance imaging
- room temperature
- density functional theory
- network analysis
- ionic liquid
- computed tomography
- highly efficient
- mass spectrometry
- deep learning
- solid phase extraction