Search arXivSearch

arXiv · 2608.16874

Size matters more than packing in bimodal colloidal gel compositions

Abstract

Colloidal gels are frequently modeled as monodisperse particle networks, although practical formulations commonly contain particles with multiple characteristic sizes. Here, we use large-scale, hydrodynamically resolved simulations of colloidal depletion gels to isolate the effects of particle size and local packing in bimodal systems with a small-to-large size ratio of 1:2. Increasing the large-particle fraction introduces new heterotypic angular motifs and substantially increases the fraction of bonds participating in tetrahedral structures, with a maximum at intermediate composition. However, these additional rigid motifs do not reorganize into larger or more highly connected tetrahedral aggregates. The mean coordination and characteristic aggregate size remain nearly composition independent. By contrast, the void and cluster-size distributions coarsen systematically as the large-particle fraction increases. These mesoscale distributions largely collapse when normalized by a composition-dependent particle length scale, indicating that changes in composition primarily rescale gel architecture rather than producing distinct rigid-network topologies. An elastic modulus estimated using Cauchy-Born theory similarly follows this effective length scale more closely than the abundance of local tetrahedral motifs. These results show that, for moderate size disparity, particle size controls the structural scale and predicted mechanical response of bimodal colloidal gels more strongly than enhanced local packing.

Explore related subjects

Keep this discovery

Explore connections, maps & timelines

BibTeXRIS

Robert A. Campbell, Ziye Zhuang, Ali Mohraz, Safa Jamali. 2026-08-17. Size matters more than packing in bimodal colloidal gel compositions. https://arxiv.org/abs/2608.16874

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