(543d) Recovering Dynamic Parameters of Nanoparticle Assembly from Disjointed Images of Nanoparticle-Polymer Composites

Arya, G. - Presenter, University of California San Diego
Murthy, C., University of California San Diego
Gao, B., University of California, San Diego
Tao, A., University of California, San Diego
The incorporation of nanoparticles (NPs) into polymers constitutes a powerful strategy for enhancing their thermomechanical properties and for introducing new optical, electrical, and magnetic functionalities into the polymers. Here we will describe an approach for inferring dynamic parameters of NP assembly from spatially and temporally disjointed images of NP-polymer composites [1]. The approach involves adjustment of the parameters of a kinetic model of assembly until the size statistics of NP clusters computed from the model match those obtained from high-throughput analysis of the experimental images [2]. Application to shaped, metal NPs in polymer films reveals that NP structures grow via a cluster-cluster aggregation mechanism, where NPs and their clusters diffuse in a Stokes-Einstein manner and stick with a probability that depends strongly on the size and shape of the NPs and the molecular weight of the polymer.

[1] C. R. Murthy, B. Gao, A. R. Tao, and G. Arya, "Dynamics of nanoparticle assembly from disjointed images of nanoparticle-polymer composites," Physical Review E, 93, 022501 (2016).

[2] C. R. Murthy, B. Gao, A. R. Tao, and G. Arya, "Automated quantitative image analysis of nanoparticle assembly," Nanoscale, 7, 9793-805 (2015)