Flow through Deformed Carbon Nanotubes Predicted by Rigid and Flexible Water Models.

In this study, using nonequilibrium molecular dynamics simulation, the flow of water in deformed carbon nanotubes is studied for two water models TIP4P/2005 and simple point charge/FH (SPC/FH). The results demonstrated a nonuniform dependence of the flow on the tube deformation and the flexibility imposed on the water molecules, leading to an unexpected increase in the flow in some cases. The effects of the tube diameter and pressure gradient are investigated to explain the abnormal flow behavior with different degrees of structural deformation.

Intercalation of CO2 Selected by Type of Interlayer Cation in Dried Synthetic Hectorite.

Clay minerals are abundant in caprock formations for anthropogenic storage sites for CO2, and they are potential capture materials for CO2 postcombustion sequestration. We investigate the response to CO2 exposure of dried fluorohectorite clay intercalated with Li+, Na+, Cs+, Ca2+, and Ba2+. By in situ powder X-ray diffraction, we demonstrate that fluorohectorite with Na+, Cs+, Ca2+, or Ba2+ does not swell in response to CO2 and that Li-fluorohectorite does swell. A linear uptake response is observed for Li-fluorohectorite by gravimetric adsorption, and we relate the adsorption to tightly bound residual water, which exposes adsorption sites within the interlayer. The experimental results are supported by DFT calculations.

CO2 Adsorption Enhanced by Tuning the Layer Charge in a Clay Mineral.

Due to the compact two-dimensional interlayer pore space and the high density of interlayer molecular adsorption sites, clay minerals are competitive adsorption materials for carbon dioxide capture. We demonstrate that with a decreasing interlayer surface charge in a clay mineral, the adsorption capacity for CO2 increases, while the pressure threshold for adsorption and swelling in response to CO2 decreases. Synthetic nickel-exchanged fluorohectorite was investigated with three different layer charges varying from 0.3 to 0.7 per formula unit of Si4O10F2. We associate the mechanism for the higher CO2 adsorption with more accessible space and adsorption sites for CO2 within the interlayers. The low onset pressure for the lower-charge clay is attributed to weaker cohesion due to the attractive electrostatic forces between the layers. The excess adsorption capacity of the clay is measured to be 8.6, 6.5, and 4.5 wt % for the lowest, intermediate, and highest layer charges, respectively. Upon release of CO2, the highest-layer charge clay retains significantly more CO2. This pressure hysteresis is related to the same cohesion mechanism, where CO2 is first released from the edges of the particles thereby closing exit paths and trapping the molecules in the center of the clay particles.

Brine-Oil Interfacial Tension Modeling: Assessment of Machine Learning Techniques Combined with Molecular Dynamics.

The physical chemistry mechanisms behind the oil-brine interface phenomena are not yet fully clarified. The knowledge of the relation between brine composition and concentration for a given oil may lead to the ionic tuning of the injected solution on geochemical and enhanced oil recovery processes. Thus, it is worth examining the parameters influencing the interfacial properties. In this context, we have combined machine learning (ML) techniques with classical molecular dynamics simulations (MD) to predict oil/brine interfacial tensions (IFT) effectively and compared this process to a linear regression (LR) method. To diversify our data set, we have introduced a new atomistic crude oil model (medium) with 36 different types of hydrocarbon molecules. The MD simulations were performed for mono- and multicomponent (toluene, heptane, Heptol, light, and medium) oil systems interfaced with sulfate and chloride brines with varying cations (Na+, K+, Ca2+, and Mg2+) and salinity concentration. Thus, a consistent IFT data set was built for the ML training and LR fitting at room temperature and pressure conditions, over the feature space considering oil density, oil composition, salinity, and ionic concentrations. On the basis of gradient boosted (GB) algorithms, we have observed that the dominant quantities affecting the IFT are related to the oil attributes and the salinity concentration, and no specific ion dominates the IFT changes. When the obtained LR model was validated against MD and experimental data from the literature, the error varied up to 2% and 9%, respectively, showing a robust and consistent transferability. The combination of MD simulations and ML techniques may provide a fast and cost-effective IFT determination over multiple and complex fluid-fluid and fluid-solid interfaces.

Multilevel Molecular Modeling Approach for a Rational Design of Ionic Current Sensors for Nanofluidics.

The complexity displayed by nanofluidic-based systems involves electronic and dynamic aspects occurring across different size and time scales. To properly model such kind of system, we introduced a top-down multilevel approach, combining molecular dynamics simulations (MD) with first-principles electronic transport calculations. The potential of this technique was demonstrated by investigating how the water and ionic flow through a (6,6) carbon nanotube (CNT) influences its electronic transport properties. We showed that the confinement on the CNT favors the partially hydrated Na, Cl, and Li ions to exchange charge with the nanotube. This leads to a change in the electronic transmittance, allowing for the distinguishing of cations from anions. Such an ionic trace may handle an indirect measurement of the ionic current that is recorded as a sensing output. With this case study, we are able to show the potential of this top-down multilevel approach, to be applied on the design of novel nanofluidic devices.