Abstract:

Computational Materials and Data Science, Sandia National Laboratories, Albuquerque NM

While nanocrystalline metals can exhibit extraordinary mechanical properties, they often remain impractical for engineering design due to instabilities in grain size under even modest amounts of stress or heat.  Increases in grain size can dramatically reduce the strength of nanocrystalline metals and adversely impact tribological response.  While it has been possible to achieve low friction and wear with metals, the ability to quantify and predict this behavior has remained elusive, leaving engineers with only phenomenological models as design tools.  We have used fundamental correlations between experiments and simulations to develop a physics-based predictive framework for describing the tribological stability thresholds of nanocrystalline metal contacts.  In this context, we address the long-standing causal misconception that higher hardness leads to higher wear resistance and explain the origin and regimes of validity of this notion through a quantitative mechanistic model. We will show how the predictions of this model, coupled with novel routes for stabilization of nanocrystalline microstructures, have led to the development of a metal alloy with extraordinary wear resistance, similar to state-of-the-art materials such as diamond-like carbon.

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