273717 Development of an Integrated Computational and Experimental Framework for Understanding and Controlling Nanoparticle Interactions
Nanomaterials hold vast potential for novel, more efficient, and "greener" processes and products due to unique properties that are fundamentally different from their bulk counterparts. These properties, in combination with their extremely small size, make nanoparticles of great interest for use as building blocks in the assembly of complex functional materials to be used in a multitude of applications from electronic devices to new construction materials with truly unique properties. Nanoparticles are also already used in a variety of industrial products and processes, from which they will be released into the environment where their "nanoproperties" may have negative impacts on human health and the environment. Thus, a better understanding of the fundamental interaction forces between nanoparticles would not only provide significant aid in the development and manufacture of complex functional nanomaterials, but may more importantly provide a means for predicting or even controlling the toxicity of nanomaterials. Controlling the interactions between nanoparticles could have vast implications concerning human welfare, as well as environmental health and safety, in view of the ever-increasing use of nanomaterials.
While the interaction forces governing both the macroscopic and molecular size regimes are well understood, our understanding of the interactions that govern the nanoscale regime (i.e., 1 - 100 nm) is only poorly developed to date. Continuum theories, which allow description of the macroscopic regime, break down as particle sizes approach the nanoscale regime. At the same time, atomistic simulations, which can describe interactions on an atomic scale, become impractical due to the large number of atoms in systems composed of collections of nanoparticles.
Using silica as a base model, we are developing a bottom-up framework based on material specific properties, for accurately modeling both static and dynamic nanoparticle systems. First an interparticle potential is constructed by contributions from van der Waals and electrostatic forces, both of which are implemented via a form of coarse-grained molecular dynamics. Van der Waals forces are accounted for by packing small silica clusters, represented as single points, into the particle geometry. Electrostatics are modeled by calculating the sum of electrostatic interactions between silica nanoparticles for which atomic charges were determined with a large-scale DFT implementation and the resulting electron density gradient fitted to a function dependent on particle size. Validation of the model is completed with the colloidal probe technique in atomic force microscopy (AFM). An accurate interparticle potential can then be implemented in dissipative particle dynamics (DPD) to simulate large nanoparticle systems.
The proposed model, and the insight it would provide, may allow for predicting or even controlling the toxicity of current nanomaterials and guide the development of novel functional materials constructed via self-assembly.