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Short-range correlation of stress chains near solid-to-liquid transition in active monolayers

Cite this dataset

Khosh Sokhan Monfared, Siavash; Ravichandran, Guruswami; Andrade, Jose; Doostmohammadi, Amin (2024). Short-range correlation of stress chains near solid-to-liquid transition in active monolayers [Dataset]. Dryad. https://doi.org/10.5061/dryad.18931zd4k

Abstract

Using a three-dimensional model of cell monolayers, we study the spatial organization of active stress chains as the monolayer transitions from a solid to a liquid state. The critical exponents that characterize this transition map the isotropic stress percolation onto the two-dimensional random percolation universality class suggesting short-range stress correlations near this transition. This mapping is achieved via two distinct, independent pathways: (i) cell-cell adhesion and (ii) active traction forces. We unify our findings by linking the nature of this transition to high-stress fluctuations, distinctly linked to each pathway. The results elevate the importance of the transmission of mechanical information in dense active matter and provide a new context for understanding the non-equilibrium statistical physics of phase transition in active systems.

README: Short-range correlation of stress chains near solid-to-liquid transition in active monolayers

https://doi.org/10.5061/dryad.18931zd4k

There are two types of simulation output data included here. (i) the center of mass data for each cell and at each output time step and (ii) the time-averaged isotropic stress field. For each drive (cell-cell adhesion, active traction), there are three realizations. Additionally, two Python (.py) codes are included for (i) plotting a field and (ii) cluster statistics for varying distribution percentiles.

Description of the data and file structure

(i) The center of mass data is formatted as time step, x-coordinate, y-coordinate, z-coordinate

(ii) The time-averaged isotropic stress fields. For realization 1, for each drive, this is included for each parameter. The finite size scaling is only carried out at the onset of the solid-to-liquid transition (see paper for more details).

Sharing/Access information

Data is generated using the code available here: https://doi.org/10.5281/zenodo.10790896

Code/Software

Two Python (.py) codes are included for (i) plotting a field and (ii) cluster statistics for varying distribution percentiles.

Funding

United States Army Research Office, Award: W911NF-19-1-0245

Novo Nordisk Foundation, Award: NNF18SA0035142

Villum Fonden, Award: 29476