We determine the physical processes promoting and contrasting the growth of a density fluctuation in suspensions of repulsive active Brownian particles, and determine the spinodal line by balancing the associated timescales. Particle motility both promotes density fluctuations, fostering the encounter of particles with opposing self-propelling directions, as well as the homogeneous one, allowing the particles to drift apart. The homogeneous phase is also promoted by the rotational diffusion coefficient. The predicted U-shaped spinodal line well compares to numerical simulations, in both two and three spatial dimensions.

In some conditions, bacteria self-organize into biofilms, supracellular structures made of a self-produced embedding matrix, mainly composed of polysaccharides, DNA, proteins, and lipids. It is known that bacteria change their colony/matrix ratio in the presence of external stimuli such as hydrodynamic stress. However, little is still known about the molecular mechanisms driving this self-adaptation. In this work, we monitor structural features of Pseudomonas fluorescens biofilms grown with and without hydrodynamic stress. Our measurements show that the hydrodynamic stress concomitantly increases the cell density population and the matrix production. At short growth timescales, the matrix mediates a weak cell-cell attractive interaction due to the depletion forces originated by the polymer constituents. Using a population dynamics model, we conclude that hydrodynamic stress causes a faster diffusion of nutrients and a higher incorporation of planktonic bacteria to the already formed microcolonies. This results in the formation of more mechanically stable biofilms due to an increase of the number of crosslinks, as shown by computer simulations. The mechanical stability also relies on a change in the chemical compositions of the matrix, which becomes enriched in carbohydrates, known to display adhering properties. Overall, we demonstrate that bacteria are capable of self-adapting to hostile hydrodynamic stress by tailoring the biofilm chemical composition, thus affecting both the mesoscale structure of the matrix and its viscoelastic properties that ultimately regulate the bacteria-polymer interactions.

Several bacteria and bacteria strands form biofilms in different environmental conditions, e.g. pH, temperature, nutrients, etc. Biofilm growth, therefore, is an extremely robust process. Because of this, while biofilm growth is a complex process affected by several variables, insights into biofilm formation could be obtained studying simple schematic models. In this manuscript, we describe a hybrid molecular dynamics and Monte Carlo model for the simulation of the early stage formation of a biofilm, to explicitly demonstrate that it is possible to account for most of the processes expected to be relevant. The simulations account for the growth and reproduction of the bacteria, for their interaction and motility, for the synthesis of extracellular polymeric substances and Psl trails. We describe the effect of these processes on the early stage formation of biofilms, in two dimensions, and also discuss preliminary three-dimensional results.

Frictional forces affect the rheology of hard-sphere colloids, at high shear rate. Here we demonstrate, via numerical simulations, that they also affect the dynamics of active Brownian particles and their motility-induced phase separation. Frictional forces increase the angular diffusivity of the particles, in the dilute phase, and prevent colliding particles from resolving their collision by sliding one past to the other. This leads to qualitatively changes of motility-induced phase diagram in the volume-fraction motility plane. While frictionless systems become unstable towards phase separation as the motility increases only if their volume fraction overcomes a threshold, frictional systems become unstable regardless of their volume fraction. These results suggest the possibility of controlling the motility-induced phase diagram by tuning the roughness of the particles.

Large density fluctuations are commonly observed in biological systems of selfpropelling particles. Examples we are all familiar with include fish schools, bird flocks, herds of animals. These density fluctuations are frequently interpreted as the manifestation of phase separation, despite the underlying system being out of thermal equilibrium. The active elements consume energy to self-propel. Due to the absence of a thermodynamic description, a question of great interest concerns the identification of the microscopic processes that induce these density fluctuations, as well as to develop of a non-equilibrium theory to predict the phase diagram of these systems.Research in this direction follows two paths. On one side, we might assume these density fluctuations originate from underlying physical processes that are universal across different biological systems. Hence, to rationalize the microscopic origin of these fluctuations, one might devise simple models which are able to reproduce them and then investigate these models in detail. On the other side, one might acknowledge that different biological systems are different, and hence try to understand a particular system. In my research work, I have followed both approaches to some extent.The most significant part of my research work, and hence of this thesis, focused on the investigation of a prototypical schematic model of the active particle, known as Active Brownian Particles (ABPs). This model describes a collection of particles interacting via short-range repulsive forces, experiencing thermal noise and selfpropelling force.The self-propulsion results from an active force acting on each particle, which differs across particles, whose directions are persistent on nature. This active force induces a velocity, known as the active velocity of the particles. At high enough particle density and high enough active velocity, ABPs undergo a transition from a i v vi Mainly, I enjoyed the friendship of my fellow Ph.D. students Wang You and Jia Guichong as we walk through Ph.D. struggles together. My special thanks to the University Well-being Centre, the staffs, and consultants working there. During a hard time of my Ph.D., they helped me to think positively towards the difficulty in life, although sometimes you cannot change it. With their help, I gradually controlled my depression state.Last but not least, I want to thank my beloved husband Dr. Bo En, my wise father, and my caring mother. Without their unconditional love, support, and understanding, I could not managed to achieve these results.