Harnessing elastic instabilities for enhanced mixing and reaction kinetics in porous media

Turbulent flows have been used for millennia to mix solutes; a familiar example is stirring cream into coffee. However, many energy, environmental, and industrial processes rely on the mixing of solutes in porous media where confinement suppresses inertial turbulence. As a result, mixing is drastically hindered, requiring fluid to permeate long distances for appreciable mixing and introducing additional steps to drive mixing that can be expensive and environmentally harmful. Here, we demonstrate that this limitation can be overcome just by adding dilute amounts of flexible polymers to the fluid. Flow-driven stretching of the polymers generates an elastic instability (EI), driving turbulent-like chaotic flow fluctuations, despite the pore-scale confinement that prohibits typical inertial turbulence. Using in situ imaging, we show that these fluctuations stretch and fold the fluid within the pores along thin layers (``lamellae'') characterized by sharp solute concentration gradients, driving mixing by diffusion in the pores. This process results in a $3\times$ reduction in the required mixing length, a $6\times$ increase in solute transverse dispersivity, and can be harnessed to increase the rate at which chemical compounds react by $3\times$ -- enhancements that we rationalize using turbulence-inspired modeling of the underlying transport processes. Our work thereby establishes a simple, robust, versatile, and predictive new way to mix solutes in porous media, with potential applications ranging from large-scale chemical production to environmental remediation

Building Predictive Chemistry Models

Density Functional Theory (DFT) simulations allow for sophisticated modeling of chemical interactions, but the extreme computational cost makes it inviable for large scale applications. Molecular dynamics models, specifically ReaxFF, can model much larger simulations with greater speed, but with lesser accuracy. The accuracy of ReaxFF can be improved by comparing predictions of both methods and tuning ReaxFF’s parameters. Molecular capabilities of ReaxFF were gauged by simulating copper complexes in water over a 200 ps range, and comparing energy predictions against ReaxFF. To gauge solid state capabilities, volumetric strain was applied to simulated copper bulk and the strain response functions used to predict elastic constants, which were then compared against experimental data and ReaxFF predictions. Results suggest ReaxFF’s predictions are fairly robust, making it useful for molecular simulations. Training ReaxFF with this data can improve the accuracy of molecular dynamics simulations, providing wider application of molecular modeling software

Elastic turbulence generates anomalous flow resistance in porous media

Diverse processes rely on the viscous flow of polymer solutions through porous media. In many cases, the macroscopic flow resistance abruptly increases above a threshold flow rate in a porous medium---but not in bulk solution. The reason why has been a puzzle for over half a century. Here, by directly visualizing the flow in a transparent 3D porous medium, we demonstrate that this anomalous increase is due to the onset of an elastic instability. We establish that the energy dissipated by the unstable flow fluctuations, which vary across pores, generates the anomalous increase in flow resistance through the entire medium. Thus, by linking the pore-scale onset of unstable flow to macroscopic transport, our work provides generally-applicable guidelines for predicting and controlling polymer solution flows