Assessment of DFT approaches in noble gas clathrate-like clusters: stability and thermodynamics

Literature Information

Publication Date 2021-12-17
DOI 10.1039/D1CP04935F
Impact Factor 3.676
Authors

Rita Prosmiti


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Abstract

We have assessed the performance and accuracy of different wavefunction-based electronic structure methods, such as DFMP2 and domain-based local pair-natural orbital (DLPNO-CCSD(T)), as well as a variety of density functional theory (DFT) approaches on He@(H2O)N cage systems. We have selected representative clathrate-like structures corresponding to the building blocks present in each of the sI, sII and sH natural gas clathrate hydrates, and we have carefully studied the interaction between a He atom with each of their individual cages. We reported well-converged DFMP2 and DLPNO-CCSD(T) reference data, together with interaction and cohesive energies of four different density functionals (two GGA, revPBE and PW86PBE, and two hybrids, B3LYP and PBE0), including diverse dispersion correction schemes (D3(0), D3(BJ), D4 and XDM) for both He-filled and empty clathrate-like cages. After the analysis of the results, we came to the conclusion that the PW86PBE functional, with both XDM and D4 corrections, and the PBE0-D4 functional present reasonably adequate approaches to describe the guest–host noncovalent interactions that take place in such He clathrate hydrates. Taking into account that the He@sII is the only helium clathrate that scientists have been able to synthesize recently, we have performed a thermodynamic study on the individual 512 and 51264 cages present in the sII crystal. We determined the change in enthalpy, ΔH, and in Gibbs free energy, ΔG, at various temperatures and pressures, and we found out that in the range of experimental conditions the reactions associated with the encapsulation of the He atom inside the cages are exothermic and spontaneous. Finally, we highlighted the importance of an accurate description of the interaction in He@water mixtures, as a crucial component in construction of reliable data-driven models.

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Physical Chemistry Chemical Physics

Physical Chemistry Chemical Physics
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