**Brownian motion**

### Background

Objects in miniaturized systems could be moving in an environment with varying configurations, temperatures and fluid properties, among other factor. Thermal fluctuations are important to the motion of such objects and must be included in any fundamental modeling scheme.The previously developed Brownian dynamics (BD) and Stokesian dynamics (SD) approaches for the Brownian motion of particles are based on the Langevin equation for particle motion. A random force is included in the particle equation of motion. Although these techniques are effective in many cases, using these techniques to objects of irregular shapes and to cases where the fluid exhibits varying properties is not straightforward. This is mainly because the properties of the random force in the particle equations depend on the hydrodynamic interactions, which in turn depends on the particle positions, shapes and the fluid properties.

### Our approach

In light of the above issues we considered fully resolved simulation of fluid-particle motion to be an excellent tool to fundamentally investigate the motion of micron scale particles in varying fluid environments. Hence, our primary objective was to devise a convenient way to incorporate the effect of thermal fluctuations in the fully resolved schemes.

Our work in Fluctuating Hydrodynamics (FHD) concerns the efficient simulation of many, micron--scale, passive and active rigid particles suspended in fluid. At this scale, special care must be taken to ensure that thermal fluctuations from the fluid are correctly accounted for in the motion of the rigid particles but this can be prohibitively expensive if done naively. A combination of cleverly designed temporal integration schemes, sophisticated numerical linear algebra, and parallel implementation resulted in simulation algorithms which scaled linearly in complexity with the number of particles, allowing us to study system sizes previously considered infeasible. Using the methods and code we developed, we were able to quantitatively compare our results to experiments done on dense suspensions of rotating spheres and even make suggestions for future experiments by identifying key features in the simulated dynamics.

### Uniqueness, impact and outlook

The uniqueness of this approach is that it can be applied to general configurations and particle shapes, potentially in a variety of fluid environments, without any additional complexity. It can model short and long time thermal motion of the particles. The translational as well as the rotational diffusion of the particle are simulated simultaneously.

It is to be noted that this approach captures the algebraic tail in the velocity autocorrelation function consistent with the molecular time autocorrelation functions unlike the Langevin approach (e.g. in BD) which gives an exponential tail in the velocity autocorrelation function.

This approach is easily incorporated into existing fluid flow solvers based on the Navier-Stokes equations. Extension of the method to droplets and elastic bodies immersed in fluids should be considered in the future.

### Applications

We are interested in applying this tool to understand the dynamics of intracellular processes, e.g. motion of motor proteins and to develop multiscale techniques. The FHD approach is also being used to study slip near hydrophobic surfaces.

Biomaterials, such as cellular materials contain biomolecules suspended in the aqueous component of the cytoplasm. Examples of biomolecules include motor proteins and polymerizing/de-polymerizing filaments which use chemical energy and produce motion or generate force (mechanical energy). These are active processes. It is essential to link the microscale dynamics of the active processes to the mechanics of the cell material. We are interested in using our approach to study such problems.