245 citations · 1.3k across the 17 of their papers we have counts for
4 papers · 1 filter
Energy benchmarks for water clusters and ice structures from an embedded many-body expansion
M. J. Gillan, D. Alfe, P. J. Bygrave +2
We show how an embedded many-body expansion (EMBE) can be used to calculate accurate \emph{ab initio} energies of water clusters and ice structures using wavefunction-based methods…
Machine learning for predictive condensed-phase simulation
Albert P. Bartok, Michael J. Gillan, Frederick R. Manby +1
We show how machine learning techniques based on Bayesian inference can be used to reach new levels of realism in the computer simulation of molecular materials, focusing here on w…
Assessing the accuracy of quantum Monte Carlo and density functional theory for energetics of small water clusters
M. J. Gillan, F. R. Manby, M. D. Towler +1
We present a detailed study of the energetics of water clusters (HO) with , comparing diffusion Monte Carlo (DMC) and approximate density functional theory (DFT) w…
Bulk and surface energetics of lithium hydride crystal: benchmarks from quantum Monte Carlo and quantum chemistry
S. J. Binnie, S. J. Nolan, N. D. Drummond +4
We show how accurate benchmark values of the surface formation energy of crystalline lithium hydride can be computed by the complementary techniques of quantum Monte Carlo (QMC) an…