Outputs (15)

Four-Body Nonadditive Potential Energy Surface and the Fourth Virial Coefficient of Helium (2023)
Journal Article

The four-body nonadditive contribution to the energy of four helium atoms is calculated and fitted for all geometries for which the internuclear distances exceed a small minimum value. The interpolation uses an active learning approach based on Gauss... Read More about Four-Body Nonadditive Potential Energy Surface and the Fourth Virial Coefficient of Helium.

Parallel Implementation of Nonadditive Gaussian Process Potentials for Monte Carlo Simulations (2023)
Journal Article

A strategy is presented to implement Gaussian process potentials in molecular simulations through parallel programming. Attention is focused on the three-body nonadditive energy, though all algorithms extend straightforwardly to the additive energy.... Read More about Parallel Implementation of Nonadditive Gaussian Process Potentials for Monte Carlo Simulations.

Microporous metallic scaffolds supported liquid infused icephobic construction (2022)
Journal Article

Hypothesis: Ice accretion on component surfaces often causes severe impacts or accidents. Liquid-infused surfaces (LIS) have drawn much attention as icephobic materials for ice mitigation in recent years due to their outstanding icephobicity. However... Read More about Microporous metallic scaffolds supported liquid infused icephobic construction.

Polarisabilities of iterated stockholder atoms (2022)
Journal Article

Polarisabilities of atoms within molecules can be calculated from molecular electron densities using the density partitioning method known as Iterated Stockholder Atoms (ISA). Non-local polarisation effects are removed by optimising the ISA functiona... Read More about Polarisabilities of iterated stockholder atoms.

Machine learning for non-additive intermolecular potentials: quantum chemistry to first-principles predictions (2022)
Journal Article

Prediction of thermophysical properties from molecular principles requires accurate potential energy surfaces (PES). We present a widely-applicable method to produce first-principles PES from quantum chemistry calculations. Our approach accurately in... Read More about Machine learning for non-additive intermolecular potentials: quantum chemistry to first-principles predictions.

Gaussian Process Models of Potential Energy Surfaces with Boundary Optimisation (2021)
Journal Article

A strategy is outlined to reduce the number of training points required to model intermolecular potentials using Gaussian processes, without reducing accuracy. An asymptotic function is used at long range and the cross-over distance between this mode... Read More about Gaussian Process Models of Potential Energy Surfaces with Boundary Optimisation.

Gaussian process models of potential energy surfaces with boundary optimization (2021)
Journal Article

A strategy is outlined to reduce the number of training points required to model intermolecular potentials using Gaussian processes, without reducing accuracy. An asymptotic function is used at a long range, and the crossover distance between this mo... Read More about Gaussian process models of potential energy surfaces with boundary optimization.

Cluster integrals and virial coefficients for realistic molecular models (2020)
Journal Article

We present a concise, general, and efficient procedure for calculating the cluster integrals that relate thermodynamic virial coefficients to molecular interactions. The approach encompasses nonpairwise intermolecular potentials generated from quantu... Read More about Cluster integrals and virial coefficients for realistic molecular models.

Enhanced doping effects of multi?element on anisotropic thermal expansion in ZrO2 with new compositions (2020)
Journal Article

Coefficient of thermal expansion (CTE) of a solid material plays a critical role for a variety of high temperature applications such as thermal barrier coating (TBC) systems during the thermal cycling process. Ceramics contain ionic bonds; hence they... Read More about Enhanced doping effects of multi?element on anisotropic thermal expansion in ZrO2 with new compositions.

Active learning in Gaussian process interpolation of potential energy surfaces (2018)
Journal Article

© 2018 Author(s). Three active learning schemes are used to generate training data for Gaussian process interpolation of intermolecular potential energy surfaces. These schemes aim to achieve the lowest predictive error using the fewest points and th... Read More about Active learning in Gaussian process interpolation of potential energy surfaces.