1 citations · 1 across the 3 of their papers we have counts for
4 papers
Fast and Accurate Equivariant Foundation Models for Atomistic Simulation
Seán R. Kavanagh, Chuin Wei Tan, Menghang Wang +12
Machine-learned interatomic potentials (MLIPs) have emerged as a transformative tool for computational materials science and chemistry, with universal potentials trained on large a…
Exploring Charge Density Waves in two-dimensional NbSe2 with Machine Learning
Norma Rivano, Francesco Libbi, Chuin Wei Tan +8
Niobium diselenide (NbSe) has garnered significant attention due to the coexistence of superconductivity and charge density waves (CDWs) down to the monolayer limit. However, r…
Density-functional perturbation theory for one-dimensional systems: implementation and relevance for phonons and electron-phonon interactions
Norma Rivano, Nicola Marzari, Thibault Sohier
The electronic and vibrational properties and electron-phonon couplings of one-dimensional materials will be key to many prospective applications in nanotechnology. Dimensionality…
Infrared-active phonons in one-dimensional materials and their spectroscopic signatures
Norma Rivano, Nicola Marzari, Thibault Sohier
Dimensionality provides a clear fingerprint on the dispersion of infrared-active, polar-optical phonons. For these phonons, the local dipoles parametrized by the Born effective cha…