| People | Locations | Statistics |
|---|---|---|
| Naji, M. |
| |
| Motta, Antonella |
| |
| Aletan, Dirar |
| |
| Mohamed, Tarek |
| |
| Ertürk, Emre |
| |
| Taccardi, Nicola |
| |
| Kononenko, Denys |
| |
| Petrov, R. H. | Madrid |
|
| Alshaaer, Mazen | Brussels |
|
| Bih, L. |
| |
| Casati, R. |
| |
| Muller, Hermance |
| |
| Kočí, Jan | Prague |
|
| Šuljagić, Marija |
| |
| Kalteremidou, Kalliopi-Artemi | Brussels |
|
| Azam, Siraj |
| |
| Ospanova, Alyiya |
| |
| Blanpain, Bart |
| |
| Ali, M. A. |
| |
| Popa, V. |
| |
| Rančić, M. |
| |
| Ollier, Nadège |
| |
| Azevedo, Nuno Monteiro |
| |
| Landes, Michael |
| |
| Rignanese, Gian-Marco |
|
Chauveau, Edouard
in Cooperation with on an Cooperation-Score of 37%
Topics
Publications (8/8 displayed)
- 2023Influence of the Graft Length on Nanocomposite Structure and Interfacial Dynamicscitations
- 2023Influence of the Graft Length on Nanocomposite Structure and Interfacial Dynamicscitations
- 2023How Tuning Interfaces Impacts the Dynamics and Structure of Polymer Nanocomposites Simultaneouslycitations
- 2020Tailoring the viscoelasticity of polymer gels of gluten proteins through solvent qualitycitations
- 2020Rejuvenating the structure and rheological properties of silica nanocomposites based on natural rubbercitations
- 2020Structural identification of percolation of nanoparticlescitations
- 2019Phase separation dynamics of gluten protein mixturescitations
- 2018Nanoscale reversibility and non-linear effects in polymer nanocomposites under strain cycles
Places of action
| Organizations | Location | People |
|---|
article
Structural identification of percolation of nanoparticles
Abstract
We propose a method relying on structural measurements by small-angle scattering to quantitatively follow aggregation of nanoparticles (NPs) in concentrated colloidal assemblies or suspensions up to percolation, regardless of complex structure factors arising due to interactions. As an experimental model system, the dispersion of silica NPs in a styrene-butadiene matrix has been analyzed by small-angle X-ray scattering and transmission electron microscopy (TEM), as a function of particle concentration. A reverse Monte Carlo analysis applied to the NP scattering compared favorably with TEM. By combining it with an aggregate recognition algorithm, series of representative real space structures and aggregation number distribution functions have been determined up to high concentrations, taking into account particle polydispersity. Our analysis demonstrates that the formation of large percolating aggregates on the scale of the simulation box (of linear dimension 1/q(min), here micron-sized) can be mapped onto the macroscopic percolation characterized by rheology. Our method is thus capable of determining aggregate structure in dense NP systems with strong - possibly unknown - interactions visible in scattering. It is hoped to be useful in many other colloidal systems, beyond the case of polymer nanocomposites exemplarily studied here.