All Outputs (3)

Microporous metallic scaffolds supported liquid infused icephobic construction (2022)
Journal Article
Wu, M., Wang, J., Ling, S., Wheatley, R., & Hou, X. (2023). Microporous metallic scaffolds supported liquid infused icephobic construction. Journal of Colloid and Interface Science, 634, 369-378. https://doi.org/10.1016/j.jcis.2022.12.034

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
Musse, S., & Wheatley, R. J. (2022). Polarisabilities of iterated stockholder atoms. Molecular Physics, https://doi.org/10.1080/00268976.2022.2111375

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
Graham, R. S., & Wheatley, R. J. (2022). Machine learning for non-additive intermolecular potentials: quantum chemistry to first-principles predictions. Chemical Communications, 58(49), 6898-6901. https://doi.org/10.1039/d2cc01820a

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.