Interaction between water and carbon nanostructures: How good are current density functional approximations?

Abstract

Due to their current and future technological applications, including realisation of water filters and desalination membranes, water adsorption on graphitic sp 2 -bonded carbon is of overwhelming interest. However, these systems are notoriously challenging to model, even for electronic structure methods such as density functional theory (DFT), because of the crucial role played by London dispersion forces and non-covalent interactions in general. Recent efforts have established reference quality interactions of several carbon nanostructures interacting with water. Here, we compile a new benchmark set (dubbed WaC18), which includes a single water molecule interacting with a broad range of carbon structures, and various bulk (3D) and two dimensional (2D) ice polymorphs. The performance of 28 approaches, including semi-local exchange-correlation functionals, non-local (Fock) exchange contributions, and long-range van der Waals (vdW) treatments, are tested by computing the deviations from the reference interaction energies. The calculated mean absolute deviations on the WaC18 set depends crucially on the DFT approach, ranging from 135 meV for LDA to 12 meV for PBE0-D4. We find that modern vdW corrections to DFT significantly improve over their precursors. Within the 28 tested approaches, we identify the best performing within the functional classes of: generalized gradient approximated (GGA), meta-GGA, vdW-DF, and hybrid DF, which are BLYP-D4, TPSS-D4, rev-vdW-DF2, and PBE0-D4, respectively.

Solid wetting-layers in inorganic nano-reactors: the water in imogolite nanotube case

“…Although aware of the challenges of semi-local XCfunctionals, such as PBE used here, in describing non-covalent interactions in condensed phases of H 2 O, [59][60][61][62][63] we expect the calculated enhancement of the covalent component of the Ge-INT/H 2 O bonding in comparison with interactions in I h to be qualitatively meaningful which is demonstrably due to electronic re-hybridisation ( Fig. S13 in the ESI, † such an increase of the Ge-INT's wall dipole density markedly affects the electrostatics inside the cavity with a $1.3 eV shi of the vacuum electrostatic plateau inside the nanotube's cavity.…”

Machine learning potentials for complex aqueous systems made simple

“…MLPs will always only be as good as their underlying reference method, and a user has to make a careful choice for each system of interest. In this context, density functional theory (DFT) has become indispensable for the investigation of aqueous systems, while careful benchmark studies ( 52 – 59 ) can guide the selection of suitable functionals. In addition, there have been promising steps to better understand remaining limitations of existing functionals and provide potential solutions in recent studies ( 60 – 62 ).…”

A Dispersion Corrected DFT Investigation of the Inclusion Complexation of Dexamethasone with β-Cyclodextrin and Molecular Docking Study of Its Potential Activity against COVID-19

“…Due to the size of the studied systems (204 atoms and 812 electrons for each configuration of non-covalent complexes), the resolution of the identity method was applied to speed up the calculations [40,52]. The use of the most recent dispersioncorrected DFT approximation based on the new charge-dependent D4 dispersion model is an adequate approach for describing the interactions of non-covalent systems [53,54]. The starting configurations used for molecular docking simulations between β-CD and dexamethasone were generated according to the method of Liu and Guo [55], where the center of dexamethasone and β-CD was defined as the center of the coordination system (0 Å).…”