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Knowledge Gap: The aggregation of clay minerals in liquid water exemplifies colloidal self-assembly in nature. These negatively charged aluminosilicate platelets interact through multiple mechanisms with different sensitivities to particle shape, surface charge, aqueous chemistry, and interparticle distance and exhibit complex aggregation structures. Experiments have difficulty resolving the associated colloidal assemblages at the scale of individual particles. Conversely, all-atom molecular dynamics (MD) simulations provide detailed insight on clay colloidal interaction mechanisms, but they are limited to systems containing a few particles. Simulations: We develop a new coarse-grained (CG) model capable of representing assemblages of hundreds of clay particles with accuracy approaching that of MD simulations, at a fraction of the computational cost. Our CG model is parameterized based on MD simulations of a pair of smectite clay particles in liquid water. A distinctive feature of our model is that it explicitly represents the electrical double layer (EDL), i.e., the cloud of charge-compensating cations that surrounds the clay particles. Findings: Our model captures the simultaneous importance of long-range colloidal interactions (i.e., interactions consistent with simplified analytical models, already included in extant clay CG models) and short-range interactions such as ion correlation and surface and ion hydration effects. The resulting simulations correctly predict, at low solid-water ratios, the existence of ordered arrangements of parallel particles separated by water films with a thickness up to ~10 nm and, at high solid-water ratios, the coexistence of crystalline and osmotic swelling states, in agreement with experimental observations. 

The abundance and isotopic composition of noble gases dissolved in water have many applications in the geosciences. In recent years, new analytical techniques have opened the door to the use of high-precision measurements of noble gas isotopes as tracers for groundwater hydrology, oceanography, mantle geochemistry, and paleoclimatology. These analytical advances have brought about new measurements of solubility equilibrium isotope effects (SEIEs) in water (i.e., the relative solubilities of noble gas isotopes) and their sensitivities to the temperature and salinity. Here, we carry out a suite of classical molecular dynamics (MD) simulations and employ the theoretical method of quantum correction to estimate SEIEs for comparison with experimental observations. We find that classical MD simulations can accurately predict SEIEs for the isotopes of Ar, Kr, and Xe to order 0.01‰, on the scale of analytical uncertainty. However, MD simulations consistently overpredict the SEIEs of Ne and He by up to 40% of observed values. We carry out sensitivity tests at different temperatures, salinities, and pressures and employ different sets of interatomic potential parameters and water models. For all noble gas isotopes, the TIP4P water model is found to reproduce observed SEIEs more accurately than the SPC/E and TIP4P/ice models. Classical MD simulations also accurately capture the sign and approximate magnitude of temperature and salinity sensitivities of SEIEs for heavy noble gases. We find that experimental and modeled SEIEs generally follow an inverse-square mass dependence, which implies that the mean-square force experienced by a noble gas atom within a solvation shell is similar for all noble gases. This inverse-square mass proportionality is nearly exact for Ar, Kr, and Xe isotopes, but He and Ne exhibit a slightly weaker mass dependence. We hypothesize that the apparent dichotomy between He–Ne and Ar–Kr–Xe SEIEs may result from atomic size differences, whereby the smaller noble gases are more likely to spontaneously fit within cavities of water without breaking water–water H-bonds, thereby experiencing softer collisions during translation within a solvation shell. We further speculate that the overprediction of simulated He and Ne SEIEs may result from the neglection of higher-order quantum corrections or the overly stiff representation of van der Waals repulsion by the widely used Lennard-Jones 6–12 potential model. We suggest that new measurements of SEIEs of heavy and light noble gases may represent a novel set of constraints with which to refine hydrophobic solvation theories and optimize the set of interatomic potential models used in MD simulations of water and noble gases. 

Earth's surface materials constitute the basis for life and natural resources. Most of these materials can be catergorized as soft matter, yet a general physical understanding of the ground beneath our feet is still lacking. Here we provide some perspectives. 

Bacteria in porous media, such as soils, aquifers, and filters, often form surface-attached communities known as biofilms. Biofilms are affected by fluid flow through the porous medium, for example, for nutrient supply, and they, in turn, affect the flow. A striking example of this interplay is the strong intermittency in flow that can occur when biofilms nearly clog the porous medium. Intermittency manifests itself as the rapid opening and slow closing of individual preferential flow paths (PFPs) through the biofilm–porous medium structure, leading to continual spatiotemporal rearrangement. The drastic changes to the flow and mass transport induced by intermittency can affect the functioning and efficiency of natural and industrial systems. Yet, the mechanistic origin of intermittency remains unexplained. Here, we show that the mechanism driving PFP intermittency is the competition between microbial growth and shear stress. We combined microfluidic experiments quantifying Bacillus subtilis biofilm formation and behavior in synthetic porous media for different pore sizes and flow rates with a mathematical model accounting for flow through the biofilm and biofilm poroelasticity to reveal the underlying mechanisms. We show that the closing of PFPs is driven by microbial growth, controlled by nutrient mass flow. Opposing this, we find that the opening of PFPs is driven by flow-induced shear stress, which increases as a PFP becomes narrower due to microbial growth, causing biofilm compression and rupture. Our results demonstrate that microbial growth and its competition with shear stresses can lead to strong temporal variability in flow and transport conditions in bioclogged porous media.