Exploring CO2 @sI Clathrate Hydrates as CO2 Storage Agents by Computational Density Functional Approaches.

The formation of specific clathrate hydrates and their transformation at given thermodynamic conditions depends on the interactions between the guest molecule/s and the host water lattice. Understanding their structural stability is essential to control structure-property relations involved in different technological applications. Thus, the energetic aspects relative to CO2 @sI clathrate hydrate are investigated through the computation of the underlying interactions, dominated by hydrogen bonds and van der Waals forces, from first-principles electronic structure approaches. The stability of the CO2 @sI clathrate is evaluated by combining bottom-up and top-down approaches. Guest-free and CO2 guest-filled aperiodic cages, up to the gradually CO2 occupation of the entire sI periodic unit cells were considered. Saturation, cohesive and binding energies for the systems are determined by employing a variety of density functionals and their performance is assessed. The dispersion corrections on the non-covalent interactions are found to be important in the stabilization of the CO2 @sI energies, with the encapsulation of the CO2 into guest-free/empty cage/lattice being always an energetically favorable process for most of the functionals studied. The PW86PBE functional with XDM or D3(BJ) dispersion corrections predicts a lattice constant in accord to the experimental values available, and simultaneously provides a reliable description for the guest-host interactions in the periodic CO2 @sI crystal, as well as the energetics of its progressive single cage occupancy process. It has been found that the preferential orientation of the single CO2 in the large sI crystal cages has a stabilizing effect on the hydrate, concluding that the CO2 @sI structure is favored either by considering the individual building block cages or the complete sI unit cell crystal. Such benchmark and methodology cross-check studies benefit new data-driven model research by providing high-quality training information, with new insights that indicate the underlying factors governing their structure-driven stability, and triggering further investigations for controlling the stabilization of these promising long-term CO2 storage materials.