  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.
