Clustering dynamics of chemotactic particles

Micro-organisms in nature can perform chemotaxis when exposed to a chemical gradient in order to find advantageous substances (e.g. food and nutrients) or to escape from dangerous ones (e.g. toxins and poisons) [1].

In this work, we model micro-organisms via self-propelled particles coupled with a chemical field [2]. The emerging dynamics is the result of the combination of self-propulsion, steric interaction, and chemical interactions. Tuning the chemotactic parameters, it is possible to explore various dynamical regimes which include collapse, when particles form one giant cluster, dynamical clustering, when particles dynamically form small clusters, and a state reminiscent of the well established Motility Induced Phase Separation (MIPS) with a cluster and particles continuously moving to and from it at the boundary [3].

We perform computer simulations with GPU-CUDA to explore the system at various Peclet numbers and packing fractions of the particles.

References:

[1] B. Liebchen and H. Lowen, Acc. Chem. Res. 51, 2982-2990 (2018).

[2] O. Pohl and H. Stark, Phys. Rev. Lett. 112, 238303 (2014); O. Pohl and H. Stark, Eur. Phys. J. E 38, 93 (2015); B. Liebchen, D. Marenduzzo, and M. Cates, Phys. Rev. Lett. 118, 268001 (2017).

[3]  Y. Fily and M. Marchetti, Phys. Rev. Lett. 108, 235702 (2012); G. Redner, M. Hagan, and Baskaran.A., Phys. Rev. Lett. 110, 055701 (2013).