Ref HAL: hal-01768107_v1
PMID 29443532
Ref Arxiv: 2007.15470
DOI: 10.1021/acs.langmuir.7b03932
WoS: WOS:000427095400012
Ref. & Cit.: NASA ADS
Exporter : BibTex | endNote
9 Citations
Résumé:

A new method based on the combination of small-anglescattering, reverse Monte Carlo simulations, and an aggregate recognition algorithm is proposed to characterize the structure of nanoparticle suspensions in solvents and polymer nanocomposites, allowing detailedstudies of the impact of different nanoparticle surface modifications.Experimental small-angle scattering is reproduced using simulated annealing of configurations of polydisperse particles in a simulation box compatible with the lowest experimental q-vector. Then, properties of interest likeaggregation states are extracted from these configurations and averaged. This approach has been applied to silane surface-modified silica nanoparticles with different grafting groups, in solvents and after casting into polymer matrices.It is shown that the chemistry of the silane function, in particular mono- or trifunctionality possibly related to patch formation, affects the dispersion state in a given medium, in spite of an unchanged alkylchain length. Our approach may be applied to study any dispersion or aggregation state of nanoparticles. Concerningnanocomposites, the method has potential impact on the design of new formulations allowing controlled tuning of nanoparticle dispersion.