Collaborative Research: A Data-Driven Statistical Approach to Aging and Elasticity in Colloidal Glasses

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The research objective of this grant is to understand the fundamental process of aging of glassy materials from a statistical and microscopic point of view. Aging of glassy materials is a long standing problem: a glass is an out-of-equilibrium material, so its mechanical and electrical properties change over time, but the microscopic reasons for this are still unknown. Understanding aging has implications for extending the lifetime of products made from glassy materials (both "regular" glass and plastics). This project involves simulations of glassy systems and will employ novel statistical techniques to reconstruct local elastic properties of the material. We will learn how these properties change during the aging process. Complementary experiments will be conducted on colloidal glasses, a well-characterized model system which exhibits aging. Due to the limited amount of data the experiments can obtain - and more fundamentally, the limited data one can obtain before a system ages into a new state - we will need to extend statistical techniques from bioinformatics and econometrics to be able to the relevant information from our data.The developed statistical techniques will be useful in a variety of applications beyond aging or materials science. Of equal importance is understanding the fundamental mechanisms of aging in glassy systems, which may have a long-term impact on how glassy materials are produced. The students involved in this project will gain interdisciplinary experience, as the project merges physics and engineering, statistics and soft materials, statistical mechanics theory and microscopy experiments. Outreach efforts will target Pittsburgh area high schools with under-represented populations and will target Atlanta area K-12 students via "Squishy Physics" field trips.