1. NIRT: Reduced Degree of Freedom Predictive Methods for Control & Design of Interfaces in Nanofeatured Systems D.W. Brenner, M. Buongiorno-Nardelli, G. Iafrate, M. Zikry, R. Scattergood, N. C. State University, DMR-0304299 With grain sizes less than 100 nm, nanocrystalline materials have unique and desirable mechanical properties compared to conventional materials. Nanocrystalline materials, however, are highly susceptible to grain growth, which limits their application. Using first principles based molecular simulations in tandem with continuum modeling, our NIRT has discovered that trace lead impurities in aluminum segregate to grain boundaries, where they help stabilize grain structures. When lead is incorporated into nanocrystalline aluminum, the resulting nanoalloy is predicted to be more stable than pure nanocrystalline aluminum. The simulations also predict that the impurities increase ductility by increasing the tendency for grain boundary sliding. Our predictions have been supported by our collaborators, who have measured unique properties for these nanoalloys. Illustration of lead atoms (colored red) after migration to a grain boundary in an aluminum bicrystal.

2. Broader Impact: In conventional materials, with grain sizes of microns or larger, increases in hardness almost always result in a decrease in ductility, making hard materials brittle and often difficult to process. In nanocrystalline materials, on the other hand, the deformation dynamics are dominated by the properties of the grain boundaries rather than defect motion in the grains, giving these structures potentially unique combinations of hardness and ductility. The discovery that grains in aluminum can be stabilized by trace lead impurities, which normally have very small solubilities in conventional aluminum, is leading to new strategies for engineering nanocrystalline materials that are more stable and able to withstand temperatures than are currently possible. Illustration of a simulated three-dimensional aluminum nc with lead at the boundaries. Lead atoms are red, remaining atoms are colored by local symmetry. NIRT: Reduced Degree of Freedom Predictive Methods for Control & Design of Interfaces in Nanofeatured Systems D.W. Brenner, M. Buongiorno-Nardelli, G. Iafrate, M. Zikry, R. Scattergood, N. C. State University, DMR-0304299

3. Diamond nanoclusters are emerging as an important class of structure in the family of carbon nanostructures. The clusters are typically formed in detonation soot and then purified and size selected. Extensive simulations by our NIRT of diamond nanoclusters in a polyethylene matrix have suggested that the clusters can increase the glass transition temperature of the composite by over 100K compared to the pure polymer. Furthermore, this increase is independent of cross links between the matrix and cluster. A similar but less dramatic increase in Tg was reported by NASA researchers for nanotubes in polyethylene. Illustration of the composite (right) and its calculated density as a function of temperature (below). NIRT: Reduced Degree of Freedom Predictive Methods for Control & Design of Interfaces in Nanofeatured Systems D.W. Brenner, M. Buongiorno-Nardelli, G. Iafrate, M. Zikry, R. Scattergood, N. C. State University, DMR-0304299

4. Broader Impact: Modifying the thermo- mechanical properties of polymers by adding nanoparticles has been achieved for a number of systems. Nanoclays incorporated into nylon, for example, are now used in the automobile industry to enhance heat conduction in plastics. The addition of diamond nanoclusters into polymers opens new possibilities for creating nanocomposites with unique and technologically important properties. Diamond nanoclusters, in addition to being relatively inexpensive, can be surface functionalized, leading to better dispersion and stronger matrix-particle interactions compared to existing nanoparticles. Illustration of a diamond nanocluster embedded into a polyethylene matrix NIRT: Reduced Degree of Freedom Predictive Methods for Control & Design of Interfaces in Nanofeatured Systems D.W. Brenner, M. Buongiorno-Nardelli, G. Iafrate, M. Zikry, R. Scattergood, N. C. State University, DMR-0304299