(728e) Dynamic, Directed Self-Assembly of Nanoparticles Via Toggled Interactions | AIChE

(728e) Dynamic, Directed Self-Assembly of Nanoparticles Via Toggled Interactions

Authors 

Swan, J., Massachusetts Institute of Technology
Crystals self-assembled from nanoparticles have useful properties such as optical activity and sensing capability. During fabrication however, gelation and glassification often leave these materials arrested in defective or disordered metastable states. This is a key difficulty preventing adoption of self-assembled nanoparticle materials at scale. Processes which suppress kinetic arrest and defect formation while accelerating growth of ordered materials are essential for bottom-up approaches to creating nanomaterials. Dynamic, directed self-assembly processes in which the interactions between self assembling components are actuated temporally offer one promising methodology for accelerating and controlling bottom-up growth of nanostructures. We show through simulation and theory how time-dependent, periodically toggled inter-particle attractions can avoid kinetic barriers and yield well-ordered crystalline domains for a dispersion of nanoparticles interacting via a short-ranged, isotropic potential. The growth mechanism and terminal structure of the dispersion are controlled by parameters of the toggling protocol. This control allows for selection of processes that yield rapid self-assembled, low defect crystals. Although self-assembly via periodically toggled attractions is inherently unsteady and out-of-equilibrium, its outcome is predicted by a first principles theory of non-equilibrium thermodynamics. The theory necessitates equality of the time average of pressure and chemical potential in coexisting phases of the dispersion. These quantities are evaluated using well known equations of state. The phase behavior predicted by this theory agrees well with measurements made in Brownian dynamics simulations of sedimentation equilibrium and homogeneous nucleation. The theory can easily be extended to model dynamic self-assembly directed by other toggled conservative force fields. We also present kinetic models that predict the rate of crystallization as a function of the dynamic toggling parameters for several different observed growth mechanisms.

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