Shear-stress fluctuations in self-assembled transient elastic networks
J.P. Wittmer, I. Kriuchevskyi, A. Cavallo, H. Xu, J., Baschnagel

TL;DR
This study numerically investigates shear-stress fluctuations in self-assembled transient elastic networks, establishing efficient methods to determine the shear-stress relaxation modulus across liquid to solid transition regimes.
Contribution
It generalizes previous work on permanent networks by providing a simple average method to compute the shear-stress relaxation modulus for transient networks across different topological states.
Findings
The shear-stress relaxation modulus can be efficiently determined using a simple average involving the shear stress mean-square displacement.
The relation between $G(t)$ and shear-stress autocorrelation function $C(t)$ is analyzed, with bounds on the number of configurations needed.
The study bridges the understanding of shear-stress fluctuations from liquid to solid states in transient network models.
Abstract
Focusing on shear-stress fluctuations we investigate numerically a simple generic model for self-assembled transient networks formed by repulsive beads reversibly bridged by ideal springs. With being the sampling time and the Maxwell relaxation time (set by the spring recombination frequency ) the dimensionless parameter is systematically scanned from the liquid limit ( to the solid limit () where the network topology is quenched and an ensemble average over independent configurations is required. Generalizing previous work on permanent networks it is shown that the shear-stress relaxation modulus may be efficiently determined for all using the simple-average expression with characterizing the canonical-affine shear transformation of the…
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
