Nonequilibrium Statistical Mechanics

Vachier, Jeremy

Collective behavior of active particles

dc.contributor.advisor	Mazza, Marco Giacomo Dr.
dc.contributor.author	Vachier, Jeremy
dc.date.accessioned	2020-03-27T09:11:11Z
dc.date.available	2020-03-27T09:11:11Z
dc.date.issued	2020-03-27
dc.identifier.uri	http://hdl.handle.net/21.11130/00-1735-0000-0005-136F-A
dc.identifier.uri	http://dx.doi.org/10.53846/goediss-7928
dc.identifier.uri	http://dx.doi.org/10.53846/goediss-7928
dc.language.iso	eng	de
dc.rights.uri	http://creativecommons.org/licenses/by-nc-nd/4.0/
dc.subject.ddc	571.4	de
dc.title	Nonequilibrium Statistical Mechanics	de
dc.title.alternative	Collective behavior of active particles
dc.type	doctoralThesis	de
dc.contributor.referee	Mazza, Marco Giacomo Dr.
dc.date.examination	2020-03-10
dc.description.abstracteng	Active matter is everywhere, from macroscopic to microscopic scales, we find systems such as human crowd or flock of birds as well as bacterial colonies. These systems composed of particles are able to convert their surrounding energy into motion, and naturally exist out of thermodynamic equilibrium. At the microscopic scale, a specific class of active particles is particularly interesting: called microswimmers, these are biological or artificial micro-sized particles able to move in a fluid, such as bacteria or chemically driven Janus particles. In nature, these microswimmers rarely swim alone and can exhibit intriguing collective behavior at interfaces such as cluster formation, as well as swarming, swirling, raft and biofilm formation. The fundamental mechanisms of the emergence of collective behavior for living and inanimate active systems is not yet understood, especially because these systems are far from equilibrium, where our experimental and theoretical understanding is limited. This thesis aims to elucidate the impact of the activity on the emergence of collective behavior in an active system, at a microscopic level, by using a stochastic approach, over three works, from active sedimenting particles to early biofilm formation in the case of the bacteria Pseudomonas aereginosa, via the aggregation formation for the micro-algae Chlamydomonas reinhardtii. The first work describes the sedimentation profile of one active particle as a function of its activity, in three dimensions under the influence of the gravity. The system is described in terms of two overdamped Langevin equations for the position and the orientation of the particle. From these equations the associated Fokker-Planck equation is derived. In this work, we developed an analytical method to study the sedimentation profile and the analytical solution of the Fokker-Planck equation in 3D for an active particle under gravity and with a confining wall is derived. We recovered experimental results: first in the steady- state the sedimentation profile given by an exponential decay of the density profile; second, the change of the length of the sedimentation by increasing the activity. This analytical method gave a direct access to the transient dynamics and kept the coupling between the position and the orientation. In order to study many interacting particles, we developed active Brownian particles simulations. By comparing the analytical solution for one active particle to the one obtained from the simulations and experimental results (Janus colloids), we have shown that our analytical solution was also valid in the dilute case. In addition, the simulations show the emergence of collective behavior as function of the activity. The second work characterizes the aggregation of active particles. By means of active Brownian particles simulations, we studied the aggregation phenomena of active particles, for different activities, under confinement. Moreover, recent experimental results (in the case of the algae C. reinhardtii) have shown that the phenomenon could not be described by a Motility-Induced Phase Separation (MIPS) model and the need of a new model was required. By varying the activity as well as the diffusion coefficients as functions of the local cell den- sity and in the case of many interacting active particles, we observed in the steady state regime the emergence of collective behavior such as an aggregation of particles at the center of the compartment or a ring pattern. We show that the use of active Brownian particles simulations designed to describe the effect of the local cell density and confinement on the dynamics re-create the patterns observed in the experiment. Finally, we studied the early stage biofilm formation in the case of two canonical strains of the bacteria family P. aereginosa, PA01 and PA14. Before forming a bacterial biofilm community, it is commonly observed that free-swimming bacteria initially undergo a phase known as “reversible attachment”, a random and variable lag period of transient cell attachment. The population dynamics was described with a ‘birth and death’ process with a temporal dependence of the rates. These rates describe the reversible attachment by a division rate and a detachment rate. The division rate was described in terms of lineage time, meaning the time that the lineage stay continually on the surface. As a conclusion, our results unified disparate findings in the literature regarding early events in biofilm formation for PA01 and PA14. Moreover, we have shown that our model gave a framework to characterize different surface colonization strategies which lead to biofilm formation.	de
dc.contributor.coReferee	Enderlein, Jörg Prof. Dr.
dc.subject.eng	Active matter	de
dc.subject.eng	Stochastic processes	de
dc.subject.eng	Collective behavior	de
dc.subject.eng	Nonequilibrium Statistical Mechanics	de
dc.subject.eng	Biophysics	de
dc.subject.eng	Pattern aggregation	de
dc.subject.eng	active Brownian particles	de
dc.identifier.urn	urn:nbn:de:gbv:7-21.11130/00-1735-0000-0005-136F-A-9
dc.affiliation.institute	Göttinger Graduiertenschule für Neurowissenschaften, Biophysik und molekulare Biowissenschaften (GGNB)	de
dc.subject.gokfull	Biologie (PPN619462639)	de
dc.identifier.ppn	1693447827

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GGNB - Göttinger Graduiertenzentrum für Neurowissenschaften, Biophysik und molekulare Biowissenschaften [1114]
GGNB - Göttingen Graduate Center for Neurosciences, Biophysics and Molecular Biosciences

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