Multi-scale modeling on the meso and micro scales

For accurate insights on a complex material, it's crucial to have an understanding of its meso and micro-scale physics and structure formation. Fluid flow at the macroscale (visible to the naked eye) is often simulated using computational fluid dynamics (CFD). However, materials developed today have functions emerging from various physical processes across broad length and time scales. Take emulsions for example. Surfactant behavior at interfaces is a microscopic process, but behavior of emulsion droplets in flow is at the mesoscopic level. Simulating complex fluids and materials therefore requires modeling through both micro and meso scales - multiscale modeling. We have adopted this approach, using two core simulation techniques; Smoothed Particle Hydrodynamics (meso), and Molecular Dynamics (micro). 

Smoothed Particle Hydrodynamics (SPH) on the meso-scale

Our technique of choice for complex fluid simulations on the mesoscale is Smoothed Particle Hydrodynamics (SPH). The advantage of the particle approach is that we can cleanly incorporate solid microparticles into the fluid simulations. We have undertaken extensive theoretical work to tailor SPH to multi-component fluids. The result is ‘Continuous Smoothed Particle Hydrodynamics’, or CSPH. In SPH each blob contains only one component, but in CSPH the blobs can contain multiple components, which shift between blobs by diffusion. Our development of CSPH is crucial not only for modeling mixing of different fluids, but also for allowing components (like surfactants) to diffuse through a fluid at experimentally realistic low concentrations. Chemical interactions between blobs have been developed based on lattice fluid theory.

Molecular Dynamics (MD) on the molecular scale

The molecular-scale aspect of our multiscale modeling strategy is Molecular Dynamics (MD). MD lets us capture the structure of molecules, and how they configure themselves in space at the microscale. To balance computational cost with physical accuracy, we employ ‘coarse-grained’ MD, where molecules are represented as one or more “beads”. Coarse-grained MD is powerful for simulating structure formation at the nanometer scale. The results from MD simulation inform the evolution of the physics in larger-scale smoothed particle hydrodynamics. They may also be analyzed on their own, for microscopic insight into a material 

Removing Complexity with Hansen Solubility Parameters (HSP)

One of the challenges in modeling is figuring out how to select the right input to use for the system you would like to research. RheoCube helps to remove some of this complexity. One way it does so is by using Hansen Solubility Parameters (HSP) as input for the cohesive energy density of an ingredient. HSP is especially suitable as it’s not limited to a narrow group of ingredients. It can be measured (or calculated) for solvents, polymers, or particles. It even offers insight into surfactants. 

High Performance Computing (HPC) in the cloud

Realizing simulations of sufficient detail to capture complex fluids is computationally demanding. We have developed a dynamically-sized, on-demand supercomputer (large parallel computer) and connected it to Rheocube. The best compute resources for your simulation are automatically chosen, or can be tailored to optimize time or cost. The computational services we employ maintain the highest security standards, so your data is safe.