Size effect in determining the water diffusion rate in carbon nanotubes

Nontrivial effects of geometric and charge defects on one-dimensional confined water

Water confined within nanochannels with specific functionalities serves as the foundation for a variety of emerging nanofluidic applications. However, the structure and dynamics of the confined liquid are susceptibly influenced by practically hard-to-avoid defects, yet knowledge of this fact remains largely unexplored. Here, using extensive molecular dynamics simulations, we elucidate the significant influence of geometric and charge defects on one-dimensional confined water. We show that the two types of defects can both reshape the water density distribution by constraining the translocation of water molecules along the circumferential direction. In addition to structural alterations, collective translocation and rotation of water slabs arise during transportation under external pressure. Below the temperature threshold marking the initiation of liquid-solid transition, the geometric defect retards water diffusion through a pinning effect, while the charge defect induces an anti-freezing effect. The latter is attributed to the electrostatic interaction between the charge defect and water molecules that hinders the formation of a stable hydrogen bond network by disrupting molecular dipole orientation. Consequently, this behavior results in a reduction in the number and lifetime of hydrogen bonds within the phase transition interval. The distinct roles of the two types of defects could be utilized to control the structure and dynamics of confined liquids that may result in distinct functionalities for nanofluidic applications.

Molecular Dynamics Study on the Diffusion Mass Transfer Behaviour of CO2 and Crude Oil in Fluids Produced via CO2 Flooding

Carbon dioxide flooding is one of the main methods used to improve crude oil recovery. It can not only improve oil recovery but also reduce greenhouse gas emissions. However, the addition of carbon dioxide makes crude oil become a more complex multiphase fluid; that is, carbon dioxide flooding-produced fluid, in which CO2 and various components in crude oil mass transfer each other. This results in significant changes in the structure and properties of crude oil that increase the hazards associated with its gathering and transportation. Therefore, it is very important to explore the microscopic mechanism for the diffusion mass transfer of CO2 and crude oil in this fluid, especially during its gathering and transportation. In this study, the diffusion mass transfer process of CO2 and crude oil in fluids produced via CO2 flooding is studied using molecular dynamics, and the influences of temperature, gas-oil ratio and water content are explored. Observations of the configuration and dynamic behaviour of the system show that after the system reaches equilibrium, the majority of the CO2 molecules are distributed at the oil-water interface, and CO2 is more prone to diffusing into the oil phase than the water phase. Increases in temperature and water content inhibit, while increases in the gas-oil ratio promote, the diffusion mass transfer of CO2 in the crude oil system. The results of this study reveal the mechanism for the diffusion mass transfer of CO2 and crude oil in fluids produced via CO2 flooding and account for the influence of the water phase, which is consistent with actual production conditions and has certain guiding significance for the safe operation of oil and gas gathering and transportation.

Transferability evaluation of the deep potential model for simulating water-graphene confined system

Machine learning potentials (MLPs) are poised to combine the accuracy of ab initio predictions with the computational efficiency of classical molecular dynamics (MD) simulation. While great progress has been made over the last two decades in developing MLPs, there is still much to be done to evaluate their model transferability and facilitate their development. In this work, we construct two deep potential (DP) models for liquid water near graphene surfaces, Model S and Model F, with the latter having more training data. A concurrent learning algorithm (DP-GEN) is adopted to explore the configurational space beyond the scope of conventional ab initio MD simulation. By examining the performance of Model S, we find that an accurate prediction of atomic force does not imply an accurate prediction of system energy. The deviation from the relative atomic force alone is insufficient to assess the accuracy of the DP models. Based on the performance of Model F, we propose that the relative magnitude of the model deviation and the corresponding root-mean-square error of the original test dataset, including energy and atomic force, can serve as an indicator for evaluating the accuracy of the model prediction for a given structure, which is particularly applicable for large systems where density functional theory calculations are infeasible. In addition to the prediction accuracy of the model described above, we also briefly discuss simulation stability and its relationship to the former. Both are important aspects in assessing the transferability of the MLP model.

Pb2+ removal based on the confinement effect in polygonal carbon nanotubes: a molecular dynamics simulation

Heavy metal Pb²⁺ pollutants have become an important environmental problem, which threatens public health and ecosystems worldwide. In this study, to explore the effective treatment of trace Pb²⁺ pollution in water, molecular dynamics simulation combined with DFT calculations was used to study the transportation behavior of Pb²⁺ using polygonal carbon nanotubes (PCNT: P = 4, 5, 6, 8)/graphene composites (PCNTs/G). It is shown that due to the confinement effect of PCNTs, both H₂O and H₃O⁺ can form a hydrogen-bonding network and transport them in the form of proton exchange through the PCNT channels. The trajectory shows that with the help of a hydrogen-bonding network, the probability of Pb²⁺ passing through the 8N channel is enhanced. Then, upon the fluorine modification of PCNTs, mutual effects of both the hydrogen-bonding network and electrophilic attraction make Pb²⁺ get through the channel of 8F. It is indicated that with respect to 4CNT/G, 5CNT/G, and 6CNT/G, 8CNT/G is not accurate for Pb²⁺ interception at the outlets. In addition, the RDF, and HOMO-LUMO orbitals indicate that the affinity from the hydrogen-bonding network and PCNT walls both play important roles in particle transportation. This work can not only provide a basic understanding of Pb²⁺ transportation in PCNTs from the perspective of diffusion but also be helpful to guide the strategy on how to deal with Pb²⁺ pollution in waters.

Ab Initio Molecular Dynamics Simulation of Water Transport through Short Carbon Nanotubes

Water transport through short single-walled (6, 6) carbon nanotubes (CNTs) was investigated with ab initio molecular dynamics (AIMD) simulation at different temperatures. The water molecules under extreme confinement present a one-dimensional jagged pattern owing to hydrogen bonding, with the near-perfect alignment of the dipole orientations. CNTs ending with dangling bonds can promote water dissociation near the entrance and the occurrence of dipole flipping along the water wire at high temperatures, accompanied by the formation of D defects and L defects in the hydrogen-bond network. In contrast, dissociation of water molecules rarely takes place if the dangling bonds at the ends of the CNTs are terminated with H atoms. Angular jumps of water molecules are commonplace inside the narrow CNTs, implying a low-energy barrier for hydrogen-bond exchange among water molecules in narrow CNTs. The simulation results demonstrate the high activity of dangling bonds at the ends of short CNTs, accompanying passivation processes and their profound impact on water structure and transport, which is important for diverse technological applications.

Impact of Impure Gas on CO2 Capture from Flue Gas Using Carbon Nanotubes: A Molecular Simulation Study

We used a grand canonical Monte Carlo simulation to study the influence of impurities including water vapor, SO₂, and O₂ in the flue gas on the adsorption of CO₂/N₂ mixture in carbon nanotubes (CNTs) and carboxyl doped CNT arrays. In the presence of single impure gas, SO₂ yielded the most inhibitions on CO₂ adsorption, while the influence of water only occurred at low pressure limit (0.1 bar), where a one-dimensional chain of hydrogen-bonded molecules was formed. Further, O₂ was found to hardly affect the adsorption and separation of CO₂. With three impurities in flue gas, SO₂ still played a major role to suppress the adsorption of CO₂ by reducing the adsorption amount significantly. This was mainly because SO₂ had a stronger interaction with carbon walls in comparison with CO₂. The presence of three impurities in flue gas enhanced the adsorption complexity due to the interactions between different species. Modified by hydrophilic carboxyl groups, a large amount of H₂O occupied the adsorption space outside the tube in the carbon nanotube arrays, and SO₂ produced competitive adsorption for CO₂ in the tube. Both of the two effects inhibited the adsorption of CO₂, but improved the selectivity of CO₂/N₂, and the competition between the two determined the adsorption distribution of CO₂ inside and outside the tube. In addition, it was found that (7, 7) CNT always maintained the best CO₂/N₂ adsorption and separation performance in the presence of impurity gas, for both the cases of single CNT and CNT array.

Pressure-driven water flow through a carbon nanotube controlled by a lateral electric field

Tuning the water flow through nanochannels provides a key to many physicochemical phenomena, such as energy harvesting, desalination, biosensors and so on.