Search arXivSearch

arXiv · 1903.08493

Interaction network analysis in shear thickening suspensions

Abstract

Dense, stabilized, frictional particulate suspensions in a viscous liquid undergo increasingly strong continuous shear thickening (CST) as the solid packing fraction, $ϕ$, increases above a critical volume fraction, and discontinuous shear thickening (DST) is observed for even higher packing fractions. Recent studies have related shear thickening to a transition from mostly lubricated to predominantly frictional contacts with the increase in stress. The rheology and networks of frictional forces from two and three-dimensional simulations of shear-thickening suspensions are studied. These are analyzed using measures of the topology of the network, including tools of persistent homology. We observe that at low stress the frictional interaction networks are predominantly quasi-linear along the compression axis. With an increase in stress, the force networks become more isotropic, forming loops in addition to chain-like structures. The topological measures of Betti numbers and total persistence provide a compact means of describing the mean properties of the frictional force networks and provide a key link between macroscopic rheology and the microscopic interactions. A total persistence measure describing the significance of loops in the force network structure, as a function of stress and packing fraction, shows behavior similar to that of relative viscosity and displays a scaling law near the jamming fraction for both dimensionalities simulated.

Explore related subjects

Keep this discovery

Explore connections, maps & timelines

BibTeXRIS

Marcio Gameiro, Abhinendra Singh, Lou Kondic, Konstantin Mischaikow, Jeffrey F. Morris. 2019-03-20. Interaction network analysis in shear thickening suspensions. https://doi.org/10.1103/physrevfluids.5.034307

Cite the original work for its findings. Save a collection to share your selection of sources.

KEEP EXPLORING

Related papers

Scale dependent chirality in twist-bend liquid crystals

The discovery of new classes of lyotropic and thermotropic liquid crystals (e.g., twist-bend, splay, and ferroelectric phases), together with significant advances in experimental techniques for their investigation, has renewed interest in a number of physical phenomena that have been studied in classical liquid crystals (nematics, cholesterics, and smectics) for more than a century. In this paper, we revisit one such ''old--new'' problem, recently highlighted in the preprint by A. Ashkinazi, H. Chhabra, A. El Moumane, M. M. C. Tortora, and J. P. K. Doye, ''Chirality Transfer in Lyotropic Twist-Bend Nematics,'' arXiv:2508.03544v1 (2025), in which various mechanisms of chirality transfer from the molecular scale to the structural scale were discussed. Here we present a simple theoretical analysis of chirality transfer within a Landau theory describing the phase transition between cholesteric and chiral twist-bend liquid crystals. We demonstrate that the handedness of the heliconical structure is opposite to that of the parent cholesteric phase. This relationship originates from the orthogonality between the cholesteric director and the vector order parameter characterizing the phase.

cond-mat.soft

Why life is hot

The process of evolution by natural selection leads to phenotypes of increasing fitness. For cellular chemical reaction networks, this means optimising a variety of fitness functions such as robustness, precision, or sensitivity to external stimuli. We argue that these diverse goals can be achieved by a versatile, generic mechanism: coupling chemical reaction networks to reservoirs that are strongly out of equilibrium. Using theory and numerics we show that this mechanism of optimisation comes at the price of significant heat dissipation. We compute the heat flux caused by kinetic proofreading in {\it Escherichia coli} and show that it constitutes a significant fraction of the total heat flux experimentally measured in this model organism. We then demonstrate that the degree of optimality achievable saturates, and that Nature appears to operate near saturation despite high energetic costs. We argue that `life is hot' largely because of the need for a versatile mechanism to optimise a variety of fitness functions.

cond-mat.soft

Understanding Structural Representation in Foundation Models for Polymers

From the relative scarcity of training data to the lack of standardized benchmarks, the creation of effective foundation models for polymers faces significant and multi-faceted challenges. At the core, many of these issues are tied directly to the structural representation of polymers. Here, we present a chemical language foundation model built on using a SMILES-based polymer graph representation (CPG) that incorporates polymer architectural features and connectivity that are often missing in other line notations. This foundation model exhibited excellent performance on 30 different polymer property benchmark datasets. Critical evaluation of the developed representation against other variations in control experiments reveals this approach to be a robust method of representing polymers in language-based foundation models. These experiments also reveal a strong invariance of structural representations to small perturbations, with many variations of structural representation exceeding or equaling state-of-the-art (SOTA) performance. Surprisingly, SMILES representations which are chemically or semantically invalid also provided near or SOTA performance in several instances--underscoring an unexamined blind spot in the development of chemistry language models. Examination of error sources and attention maps for the evaluated structural representations corroborate the findings of the control experiments, highlighting the ability of the model to interpolate SMILES sequence space in a manner that is loosely congruent to chemical and architectural space for polymers. Overall, this work highlights the surprising robustness of chemistry language models to structural representation perturbations and identifies the conditions under which CPG representation provides meaningful advantages.

cond-mat.soft