Univ. College London (UCL), Bloomsbury (United Kingdom). London Centre for Nanotechnology, Dept. of Physics and Astronomy, and Thomas Young Centre
Univ. College London (UCL), Bloomsbury (United Kingdom). London Centre for Nanotechnology, Dept. of Physics and Astronomy, Thomas Young Centre, and Dept. of Earth Sciences
Bristol Univ. (United Kingdom). School of Chemistry
The quantum Monte Carlo (QMC) method is used to generate accurate energy benchmarks for methane-water clusters containing a single methane monomer and up to 20 water monomers. The benchmarks for each type of cluster are computed for a set of geometries drawn from molecular dynamics simulations. The accuracy of QMC is anticipated to be comparable with that of coupled-cluster calculations, and this is confirmed by comparisons for the CH4-H2O dimer. The benchmarks are used to assess the accuracy of the second-order Møller-Plesset (MP2) approximation close to the complete basis-set limit. A recently created embedded many-body technique is shown to give an efficient procedure for computing basis-set converged MP2 energies for the large clusters. It is found that MP2 values for the methane binding energies and the cohesive energies of the water clusters without methane are in close agreement with the QMC benchmarks, but the agreement is aided by partial cancelation between 2-body and beyond-2-body errors of MP2. The embedding approach allows MP2 to be applied without loss of accuracy to the methane hydrate crystal, and it is shown that the resulting methane binding energy and the cohesive energy of the water lattice agree almost exactly with recently reported QMC values
Gillan, M. J., et al. "Energy benchmarks for methane-water systems from quantum Monte Carlo and second-order Møller-Plesset calculations." Journal of Chemical Physics, vol. 143, no. 10, Jul. 2015. https://doi.org/10.1063/1.4926444
Gillan, M. J., Alfè, D., & Manby, F. R. (2015). Energy benchmarks for methane-water systems from quantum Monte Carlo and second-order Møller-Plesset calculations. Journal of Chemical Physics, 143(10). https://doi.org/10.1063/1.4926444
Gillan, M. J., Alfè, D., and Manby, F. R., "Energy benchmarks for methane-water systems from quantum Monte Carlo and second-order Møller-Plesset calculations," Journal of Chemical Physics 143, no. 10 (2015), https://doi.org/10.1063/1.4926444
@article{osti_1565342,
author = {Gillan, M. J. and Alfè, D. and Manby, F. R.},
title = {Energy benchmarks for methane-water systems from quantum Monte Carlo and second-order Møller-Plesset calculations},
annote = {The quantum Monte Carlo (QMC) method is used to generate accurate energy benchmarks for methane-water clusters containing a single methane monomer and up to 20 water monomers. The benchmarks for each type of cluster are computed for a set of geometries drawn from molecular dynamics simulations. The accuracy of QMC is anticipated to be comparable with that of coupled-cluster calculations, and this is confirmed by comparisons for the CH4-H2O dimer. The benchmarks are used to assess the accuracy of the second-order Møller-Plesset (MP2) approximation close to the complete basis-set limit. A recently created embedded many-body technique is shown to give an efficient procedure for computing basis-set converged MP2 energies for the large clusters. It is found that MP2 values for the methane binding energies and the cohesive energies of the water clusters without methane are in close agreement with the QMC benchmarks, but the agreement is aided by partial cancelation between 2-body and beyond-2-body errors of MP2. The embedding approach allows MP2 to be applied without loss of accuracy to the methane hydrate crystal, and it is shown that the resulting methane binding energy and the cohesive energy of the water lattice agree almost exactly with recently reported QMC values},
doi = {10.1063/1.4926444},
url = {https://www.osti.gov/biblio/1565342},
journal = {Journal of Chemical Physics},
issn = {ISSN 0021-9606},
number = {10},
volume = {143},
place = {United States},
publisher = {American Institute of Physics (AIP)},
year = {2015},
month = {07}}