Amit Shavit

Physical Aging, the Local Dynamics of Glass-Forming Polymers under Nanoscale Confinement

The glass transition temperature marks a point below which a materials properties change significantly, and it is well-established that confinement to the nanoscale modifies the properties of glass-forming materials. We use molecular dynamics simulations to investigate the dynamics and aging behavior of model glass-forming polymers near and below the glass transition temperature of bulk and confined films. We show that both relaxation times and physical age rates vary similarly throughout a free-standing polymer film at temperatures close to the bulk glass transition temperature, where the surfaces have both lower relaxation times and physical age rates. Moreover, we provide evidence suggesting that string lengths in the bulk control dynamic length scales in the film. This realization, combined with the similarity between aging behavior and dynamic profiles, has implications for design rationale in the microelectronics industry.

Structure-property relationships from universal signatures of plasticity in disordered solids

Behavioral universality across size scales Glassy materials are characterized by a lack of long-range order, whether at the atomic level or at much larger length scales. But to what extent is their commonality in the behavior retained at these different scales? Cubuk et al. used experiments and simulations to show universality across seven orders of magnitude in length. Particle rearrangements in such systems are mediated by defects that are on the order of a few particle diameters. These rearrangements correlate with the materials softness and yielding behavior. Science, this issue p. 1033 A range of particle-based and glassy systems show universal features of the onset of plasticity and a universal yield strain. When deformed beyond their elastic limits, crystalline solids flow plastically via particle rearrangements localized around structural defects. Disordered solids also flow, but without obvious structural defects. We link structure to plasticity in disordered solids via a microscopic structural quantity, “softness,” designed by machine learning to be maximally predictive of rearrangements. Experimental results and computations enabled us to measure the spatial correlations and strain response of softness, as well as two measures of plasticity: the size of rearrangements and the yield strain. All four quantities maintained remarkable commonality in their values for disordered packings of objects ranging from atoms to grains, spanning seven orders of magnitude in diameter and 13 orders of magnitude in elastic modulus. These commonalities link the spatial correlations and strain response of softness to rearrangement size and yield strain, respectively.