Steven Bryant, PhD , University of Texas (Austin)
Water-in-oil emulsions showed a wide range of droplet volume fractions (20% to 70%), and the volume fraction exhibited a maximum at a nanoparticle concentration of 0.5 wt%. The oil-in-water emulsions were typically 60% to 80% oil by volume, with droplet sizes from 1 to 10 microns. The large volume fractions mean the droplets are very closely packed; for reference the maximum packing fraction for a disordered packing of equal spheres is 64%. The largest volume fractions occurred at smallest nanoparticle concentrations, because the droplets in those emulsion are larger and are deformable. At large nanoparticle concentrations, droplets are small and their surfaces nearly completely covered with nanoparticles, making deformation difficult and keeping the packing fraction smaller.
Droplet sizes increased as the nanoparticle concentration decreased (for constant ratio of oil volume to nanoparticle dispersion volume of 1:1), or as the ratio of oil volume to nanoparticle dispersion volume increased (for a small constant nanoparticle concentration of 0.05 wt%). For the latter set of experiments at small nanoparticle concentration, the fraction of oil emulsified decreased rapidly when the oil:dispersion ratio increased from 1:3 to 1:1. These observations suggest that droplet size can be limited by availability of nanoparticles. However the range of nanoparticle concentrations over which droplet size varies smoothly appears to be quite narrow.
A key finding of this part of the research was an organizing principle underlying these observations: the specific surface area of the emulsion “phase” (surface area of droplets per unit volume of emulsion) is an increasing function of nanoparticle concentration, and this function is almost independent of salinity. Thus larger nanoparticle concentrations can stabilize systems with larger surface energy density. The role of salinity is nevertheless important, as it influenced the surface coverage of nanoparticles on the droplets. The surface coverage for emulsions generated with nanoparticle dispersions of 0.5, 1 and 5 wt % was computed from droplet size measurements and a nanoparticles mass balance. Nearly a monolayer of nanoparticles covered droplets in high salinity emulsion (1 wt% and 10 wt% NaCl) but less than a third of a monolayer covered droplets in low salinity emulsions. This was not because of a lack of nanoparticles, since it was observed even at large loadings in the aqueous phase (5 wt%). We conclude that when emulsions are generated by sonication, as in this research, no more nanoparticles are added to the surface of a droplet once that droplet has acquired enough nanoparticles to be stable. Interestingly, at low salinity (0.1 wt%) the fraction of the droplet surface covered by nanoparticles was a strong function of nanoparticle concentration in the aqueous phase – but the droplet coverage decreased as the dispersion concentration increased. This trend did not occur at other salinities.
The equilibrated emulsion viscosity was measured across a range of shear rates by using the TA Instruments’ Advanced Rheometric Expansion System (ARES) LS-1 rheometer. The rheology of stable emulsions proved to be strongly shear thinning, for both o/w and w/o emulsions. This raises the possibility of very effective strategies for blocking unwanted flow paths: an emulsion can be injected at large flow rate, at which it has moderate viscosity (a few tens to a few 100s cP at 100 1/s). If flow is halted, it will be difficult to remobilize the injected emulsion because its viscosity at low shear rates is very large (a few 1000s to a few million cP at 0.01 1/s). Thus subsequently injected fluid will flow around the placed emulsion or into other zones.
For some applications of nanoparticles the ability to transport them significant distances through sedimentary rock is prerequisite. We conducted an extensive series of columnfloods in which stable aqueous dispersions of several kinds of nanoparticles were injected through sand packs of various lengths (1 ft to 15 ft) with sand grains of various sizes (sieved into narrow fractions between 60 and 400 microns) admixed with clay (kaolinite, illite) to give a wide range of specific surface areas, and a range of flow velocities. The concentration of nanoparticles in the effluent was measured and the fraction of nanoparticles not eluted during a six-pore-volume postflush was regarded as permanently retained in the sandpack. The degree of retention correlated with specific surface area, as would be expected given that van der Waals force is the only attraction between suitably treated nanoparticles (to have no electrostatic affinity for sand) and sand grains. The forces opposing adhesion are Brownian motion and hydrodynamics. Thus we would expect that flow rate would strongly affect nanoparticles retention. The columnfloods however show no clear effect of flow rate. Straightforward models of particle retention – either a Langmuir-type adsorption model based on chemical potential, or a filtration model based on empirical collision efficiencies – predict a significant effect of flow velocity. Thus we conclude that the interaction between nanoparticles and grain surfaces is more complicated than originally envisioned. Another project has been initiated to examine this interaction in more detail.