Active matter
Can a particle-based fluid simulation capture active nematic turbulence?
Open access · cc by · source: Europe PMC
A new mesoscale simulation method for active liquid crystals reproduces active turbulence with the length and speed scalings theory predicts, while also showing the large density fluctuations seen in active particle systems.
Study at a glance
- Design
- Computational / modelling — Two-dimensional particle-based active nematic multiparticle collision dynamics (AN-MPCD) simulations with periodic boundaries, sweeping activity over four orders of magnitude.
- N
- No sample; simulations mostly in a 200 x 200 cell box, with system sizes from 25 to 400 checked.
- Population
- Simulated wet, compressible, extensile active nematic fluid
- Outcome
- Defect density and spacing, RMS flow speed, velocity correlation lengths, enstrophy spectra and density (number) fluctuations versus activity
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Key findings
Below a threshold activity the thermostat absorbed the injected energy and the fluid behaved like a passive nematic; at intermediate activity kink walls and spontaneous flows formed; above a turbulence threshold, defect pairs unbound and active turbulence developed. In that regime the flow speed scaled with activity with a fitted exponent of 0.45 ± 0.05 (theory 1/2) and the velocity correlation length with −0.48 ± 0.05 (theory −1/2). Enstrophy spectra rose then fell with wave number, peaking at the vortex size, and particle number fluctuations became anomalously large (giant number fluctuations), though density did not correlate with nematic order or speed.
Methodology
The authors extended multiparticle collision dynamics, a coarse-grained fluid method, by adding a collision rule that gives particles equal and opposite kicks along the local nematic director, injecting energy without adding net momentum. They ran two-dimensional simulations and varied activity to map regimes from near-equilibrium to fully developed active turbulence. They measured defect populations, flow speeds, correlation lengths, enstrophy spectra and particle-number fluctuations and compared exponents to dimensional-analysis predictions.
Limitations
All results are from two-dimensional simulations in simulation units, not from an experiment on bacteria or microtubule systems, so mapping to real materials is qualitative. Threshold activities depend on system size, and at the highest activities the method breaks down. The paper validates the algorithm against expected scalings rather than testing a new physical prediction, and the suggested uses (colloids, polymers in active media) are not yet demonstrated.
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