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Understanding how nanoparticles (NPs) diffuse, stick, and assemble into larger structures within polymers is key to the design and fabrication of NP-polymer composites. Here we describe an approach for inferring the dynamic parameters of NP assembly from spatially and temporally disjointed images of composites. The approach involves iterative adjustment of the parameters of a kinetic model of assembly until the computed size statistics of NP clusters match those obtained from high-throughput analysis of the experimental images. Application of this approach to the assembly of shaped, metal NPs in polymer films suggests that NP structures grow via a cluster-cluster aggregation mechanism, where NPs and their clusters diffuse with approximately Stokes-Einstein diffusivity and stick to other NPs or clusters with a probability that depends strongly on the size and shape of the NPs and the molecular weight of the polymer.

Dynamics of nanoparticle assembly from disjointed images of nanoparticle-polymer composites