Bubble formation in active binary mixture model

Phase separation, the spontaneous segregation of density, is a ubiquitous phenomenon observed across diverse physical and biological systems. Within a crowd of motile elements, active phase separation emerges from the interplay of activity (i.e., self-propulsion) and density interactions. A striking feature of active phase separation is the persistent formation of dilute-phase bubbles within the dense phase, which has been explored in theoretical models. However, the fundamental parameters that systematically control bubble formation remain unclear in conventional self-propelled particle models. Here, we introduce an active binary mixture model in which solutes and solvents dynamically exchange positions on a lattice; both solutes and solvents are self-propelled particles, but solvents play a role analogous to empty space in typical dry active matter. Within this model, we find that spontaneous bubble formation of solvents can be tuned by activity asymmetry, which is the difference between the solute and solvent activities. Numerical simulations reveal that moderate solvent activity enhances bubble formation, while larger solvent activity, comparable to solute activity, suppresses it. By employing mean-field theory, which captures essential phase behaviors, we consider the mechanism for the enhancement of bubble formation induced by solvent activity. Beyond these findings, when solute and solvent activities are equal, we apply the finite-size scaling analysis to estimate the critical exponents for active phase separation under the suppression of bubbles. Our findings establish activity asymmetry as a key control parameter for active matter phase transitions, offering insights into universality in nonequilibrium systems.

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Publication Details

Journal
Physical Review Research
Published
2025-12-11
DOI
https://doi.org/10.1103/c8lt-743c
Primary Topic
Micro and Nano Robotics
Type
article
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article

Bubble formation in active binary mixture model

Karl J. Friston
Physical Review Research
Micro and Nano Robotics
article

Bubble formation in active binary mixture model

Karl J. Friston
article en

Abstract

Phase separation, the spontaneous segregation of density, is a ubiquitous phenomenon observed across diverse physical and biological systems. Within a crowd of motile elements, active phase separation emerges from the interplay of activity (i.e., self-propulsion) and density interactions. A striking feature of active phase separation is the persistent formation of dilute-phase bubbles within the dense phase, which has been explored in theoretical models. However, the fundamental parameters that systematically control bubble formation remain unclear in conventional self-propelled particle models. Here, we introduce an active binary mixture model in which solutes and solvents dynamically exchange positions on a lattice; both solutes and solvents are self-propelled particles, but solvents play a role analogous to empty space in typical dry active matter. Within this model, we find that spontaneous bubble formation of solvents can be tuned by activity asymmetry, which is the difference between the solute and solvent activities. Numerical simulations reveal that moderate solvent activity enhances bubble formation, while larger solvent activity, comparable to solute activity, suppresses it. By employing mean-field theory, which captures essential phase behaviors, we consider the mechanism for the enhancement of bubble formation induced by solvent activity. Beyond these findings, when solute and solvent activities are equal, we apply the finite-size scaling analysis to estimate the critical exponents for active phase separation under the suppression of bubbles. Our findings establish activity asymmetry as a key control parameter for active matter phase transitions, offering insights into universality in nonequilibrium systems.

Physical Review ResearchVol. 8(1)
RIKEN (JP)
Openalex Percentile: Top 74%
Micro and Nano Robotics
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Bubble formation in active binary mixture model — Karl J. Friston · Physical Review Research (2025) | TGRS Research Map | TGRS