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

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...

Delving into guest-free and He-filled sI and sII clathrate hydrates: a first-principles computational study

“…4 these binding energy values of He to the sI/sII hydrates, as well as the cohesive energies of the empty sI/sII crystals at their corresponding equilibrium lattice constant, a 0 , obtained from the present DFT-D computations, are displayed. The binding energies (per He atom) characterizing the guest–host interactions, and the cohesive energies per water molecule are consistent with energies previously reported for the individual He-filled and empty 5 12 (present in sI and sII), 5 12 6 2 (present in sI) and 5 12 6 4 (present in sII) cages from DLPNO-CCSD(T)/AVTZ reference calculations, 70 and are plotted in Fig. 4 (see vertical dashed and dashed-dotted lines), together with the reference DMC value for the bulk sI hydrate, Δ E sI coh , (see vertical solid line) available in the literature.…”

“…26,27 The incorporation of enthalpy and entropy effects could determine whether the calculated stabilization energies are related to observed phase diagram transformations. 13,33,67,70,106,107 Understanding the underlying factors involved in the stability of such hydrates allows the extension of this work in this direction. Thus the next step consists to consider multiple cage occupancy similar to those established by diffraction experiments 23 with up to 4 He atoms in the large sII cages and one guest in the small ones, for a more direct comparison with measurements on structural properties.…”

“…[84][85][86] Dispersion corrections were also considered using the exchange dipole moment (XDM) scheme, 87,88 as implemented in QE, and the D4 term 89,90 as a postprocessing through the DFTD4 91 program. The selection of the PW86PBE functional and the specific dispersion correction schemes is made on the basis of previous investigations on the assessment of various GGA, meta-GGA and hybrid DFT functionals for finite-size clathrate-like cages, 3,10,70,92 as well as on similar gas hydrate systems, 3,12,93 in comparison with benchmark data from DF-MP2, DLPNO-MP2 and DLPNO-CCSD(T) approaches, taking into consideration the computational resources available and the cost of the calculations. Further, we should also note that non-local dispersion effects are also explored through the vdW-DF and vdW-DF2 functionals, 94,95 as implemented in the QE code, although we found an expansion in the lattice parameter for both He-filled sI and sII structures, observed previously in similar clathrate systems, 2,51 and thus they were not considered any further.…”

“…Thus, in this work we performed DFT-D calculations on He-filled and empty sI and sII clathrate hydrates in order to obtain valuable structural and energetic insights, by evaluating their binding through the computation of the two main, host–host and guest–host, interactions. Comparisons with the individual cages, 70 as well as with experimental and previous theoretical data available in the literature for similar systems are also considered and discussed.…”

Recent advances in density functional theory and molecular dynamics simulation of mechanical, interfacial, and thermal properties of natural gas hydrates in Canada

“…The Phonopy package was used with VASP to apply phonon theory, the canonical ensemble in statistical mechanics, the finite displacement method, and the quasiharmonic approximation (QHA) to accurately calculate the thermal properties of gas hydrates. [40,41] Known for its transferability, simplicity, and reliability, [42] DFT is considered a useful tool for predicting various physical properties of natural gas hydrates, including second order elastic constants, [24] anisotropy, [43,44] infrared and Raman spectra and their relationship to material strength, [4,[45][46][47][48] heat capacity and thermal expansion, [3] compressibility, [49] elastic resistance, [5] shear modulus, [50] ideal strength, [51] and molecular mobility. [8] Properties prediction using DFT provides a low-cost access to many of materials characteristics which are nearly inaccessible through experimental investigations.…”