Searching for structural predictors of plasticity in dense active packings. Issue 7 (2nd February 2022)

• Record Type: Journal Article
• Authors: Giannini, Julia A.; Stanifer, Ethan M.; Manning, M. Lisa
• Is Part Of: Soft matter. Volume 18:Issue 7(2022)
• Page Start: 1540
• Page End: 1553
• Publication Date: 2022-02-02
• Subjects: Soft condensed matter -- Periodicals; 530.413
• DOI: 10.1039/d1sm01675j
• Languages: English
• ISSNs: 1744-683X

Abstract

Abstract : We seek to predict rearrangements in assemblies of active particles using linear response theory – global pressure gradients affect this approach. Abstract : In amorphous solids subject to shear or thermal excitation, so-called structural indicators have been developed that predict locations of future plasticity or particle rearrangements. An open question is whether similar tools can be used in dense active materials, but a challenge is that under most circumstances, active systems do not possess well-defined solid reference configurations. We develop a computational model for a dense active crowd attracted to a point of interest, which does permit a mechanically stable reference state in the limit of infinitely persistent motion. Previous work on a similar system suggested that the collective motion of crowds could be predicted by inverting a matrix of time-averaged two-particle correlation functions. Seeking a first-principles understanding of this result, we demonstrate that this active matter system maps directly onto a granular packing in the presence of an external potential, and extend an existing structural indicator based on linear response to predict plasticity in the presence of noisy dynamics. We find that the strong pressure gradient necessitated by the directed activity, as well as a self-generated free boundary, strongly impact the linear response of the system. In low-pressure regions the linear-response-based indicator is predictive, but it does not work well in the high-pressure interior of our active packings. Our findings motivate and inform future work that could better formulate structure-dynamics predictions in systems with strong pressure gradients.