Materials are increasingly being applied in devices that derive their function from small-scale, and even nanometer-scale, features. Examples include advanced battery materials and quantum wires that are being proposed for use in the next generation of opto-electronics. Unfortunately, features on these scales are subject to profound changes over time, primarily because of the thermally induced motion of atoms. This project is focused on developing the computational tools that are required for predicting the way these features evolve over time by developing computer programs referred to as "meta-codes." These meta-codes allow researchers to consider these problems by integrating knowledge obtained from the smallest scales, on which electrons control atomic interactions, to the largest scales, on which elastic interactions drive features to form or dissolve with time. The expected result is an automated, top-down working paradigm that naturally integrates tools from quantum mechanics, statistical physics and continuum elasticity. The impact of this research derives both from an increased understanding of how to develop meta- codes to undertake multi-scale modeling and from a deeper understanding of the energy storage and electronic materials studied with these novel tools. The broader impact of this work arise from the development of an approach that integrates chemistry, physics and mechanics, and that can be used to refine our understanding of how a wide variety of materials systems evolve when there exist large spatial variations in composition and stress.  This project is a collaboration with Krishna Garikipati and Anton Van der Ven’s research groups at the University of Michigan in Ann Arbor.