Abstract
Interfacial water at the low-rank coal (LRC) surface plays an important role in many technological processes, including flotation, slime water settling and dewatering. In this work, molecular dynamics simulations were performed for a series of model systems consisting of a model surface of Wender lignite and 100–600 adsorbed water molecules. A number of equilibrium properties, including density profiles, radial distribution functions (RDFs) and binding energies, are reported to explain the characteristics of interfacial water. The RDF results demonstrate that the order degree of the water molecules decreased with increasing distance from the LRC surface, although the structure of interfacial water at the LRC surface is substantially similar to that in bulk water. In addition, the results also present that the four groups affecting interfacial water at the LRC surface follow the order of carboxyl > hydroxyl ≫ ether > carbon chain. The density profiles of water molecules are insufficient to give a description of interfacial water in detail, but it can be speculated from the density profiles and RDFs that water molecule adsorption at the LRC surface is preferentially fixed around the polar functional groups when there are fewer water molecules. With increasing number of water molecules, water gathers at the hollows. Finally, the water molecules cover the whole surface of the LRC. The calculated binding energies increase monotonically with increasing number of water molecules, while the unit binding energies show the opposite trend. Furthermore, a common non-ionic surfactant, dodecyl 7-ethoxyl ether (C12EO7), was selected to modify the LRC surface. The hydrogen bonding, density profile and binding energy are reported to provide a microscopic understanding of the behaviour of interfacial water before and after surfactant adsorption. The results indicate that surfactant adsorption reduces the difference between interfacial water and bulk water. The simulation results are in accordance with the available experimental data.
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