5 papers
Anisotropic representations for E(3)-equivariant machine learning coarse-grained potentials
Varun Shankar, Emil Annevelink
Coarse-graining (CG) lowers the computational cost of atomistic simulations by representing groups of atoms as effective interaction sites, reducing the degrees of freedom of the s…
Triplet Envelope Functions for increasing machine learning interatomic potential efficiency and stability
Emil Annevelink, Varun Shankar
Central to interatomic potential efficiency is the radial envelope function that enables linear scaling with computational cost by defining a local neighborhood of atoms. This has…
Excess Density as a Descriptor for Electrolyte Solvent Design
Celia Kelly, Emil Annevelink, Adarsh Dave +1
Electrolytes mediate interactions between the cathode and anode and determine performance characteristics of batteries. Mixtures of multiple solvents are often used in electrolytes…
Selection rules of twistronic angles in 2D material flakes via dislocation theory
Shuze Zhu, Emil Annevelink, Pascal Pochet +1
Interlayer rotation angle couples strongly to the electronic states of twisted van der Waals layers. However, not every angle is energetically favorable. Recent experiments on rota…
A topologically-derived dislocation theory for twist and stretch moiré superlattices in bilayer graphene
Emil Annevelink, Harley Johnson, Elif Ertekin
We develop a continuum dislocation description of twist and stretch moire superlattices in 2D material bilayers. The continuum formulation is based on the topological constraints i…