(328h) A Generalized Memory Function Based on Recoverable Strain and Its Relation to Nanoscale Structure | AIChE

(328h) A Generalized Memory Function Based on Recoverable Strain and Its Relation to Nanoscale Structure

Authors 

Rogers, S. - Presenter, University of Illinois At Urbana-Champaign
Kamani, K., University of Illinois at Urbana-Champaign
Shim, Y., University of Illinois at Urbana-Champaign
Griebler, J., Sandia National Laboratories
Narayanan, S., Argonne National Laboratory
Leheny, R. L., Johns Hopkins University
Harden, J., University of Ottawa
Zhang, Q., Argonne National Laboratory
The physics behind the mechanism of memory formation and loss in soft materials is of great interest to understanding the behavior of biological, environmental, and industrial materials. Understanding how memories are stored and forgotten in soft materials is critical to remote additive manufacturing success, where completed products and pieces are constructed on site. The traditional rheological memory function quantifies the rate at which memory is lost and assumes that the memory originates from application of a step strain, making it difficult to apply to arbitrary transient rheological protocols. Recent studies of memory apply cyclic shearing and implement a stroboscopic protocol for determining differences and similarities in structural measures but have yet to connect the transient rheology to memory formation and loss. In this work, we propose a generalized memory function and apply it to the analysis of rheo-X-ray photon correlation spectroscopy (rheo-XPCS) experimental data from an aggregated fumed silica gel and predictions from a continuum model under dynamic shearing. Our proposal is defined in terms of changes in the ultimate recoverable strain over an interval and includes the traditional definition of memory in response to a small step strain, but generalizes it to any linear or nonlinear deformation or loading protocol, allowing for the determination of when and how quickly memories are imparted and forgotten. Our rheo-XPCS data show that the aggregate-level structure recorrelates whenever the change in recoverable strain over some interval is zero. The macroscopic recoverable strain is therefore a measure of the nano-scale structural memory. We further show that the magnitude of the structural recorrelation determined in rheo-XPCS is proportional to how much of the applied strain is recoverable. We therefore equate the property of memory with the behavior of recovery. Our proposed memory function is generic, as it can be equally applied to any soft materials under any deformation protocol. This work emphasizes the critical role of recoverable strain in connecting structural measures to bulk rheological responses, and adds another chapter to a building literature on the fundamental nature of recoverable strain.