Scaling the glassy dynamics of active particles: Tunable fragility and reentrance

• 成果类型: Article
• 署名作者: Pareek, Puneet; Sollich, Peter; Nandi, Saroj Kumar; Berthier, Ludovic
• 署名单位: Tata Institute of Fundamental Research (TIFR); University of Gottingen; Centre National de la Recherche Scientifique (CNRS); Universite PSL; CNRS - Institute of Chemistry (INC); Ecole Superieure de Physique et de Chimie Industrielles de la Ville de Paris (ESPCI)
• 刊物名称: PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA
• ISSN/ISSBN: 0027-8424; 1091-6490
• DOI: 10.1073/pnas.2516624123
• 发表日期: 2026-01-27
• 页码: e2516624123
• 关键词: active glass; reentrant dynamics; glassy dynamics; dense self-propelled particles; fragility; EPITHELIAL-MESENCHYMAL TRANSITIONS; MODE-COUPLING THEORY; collective migration; cell-shape; driven

摘要

Understanding the influence of activity on dense amorphous assemblies is crucial for biological processes such as wound healing, embryogenesis, or cancer progression. Here, we study the effect of self-propulsion forces of amplitude f0 and persistence time tau p in dense assemblies of soft repulsive particles by simulating a model particle system that interpolates between particulate active matter and biological tissues. We identify the fluid and glass phases of the three-dimensional phase diagram obtained by varying f0, tau p, and the packing fraction phi. The morphology of the phase diagram accounts for a nonmonotonic evolution of the relaxation time with tau p, which is a direct consequence of the crossover in the dominant relaxation mechanism, from glassy to jamming. A second major consequence is the evolution of the glassy dynamics from sub-Arrhenius to super-Arrhenius. We show that this tunable glass fragility extends to active systems analogous observations reported for passive particles. This analogy allows us to apply a dynamic scaling analysis proposed for the passive case, in order to account for our results for active systems. Finally, we discuss similarities and differences between our results and recent findings in the context of computational models of biological tissues.