303 citations · 1.2k across the 32 of their papers we have counts for
10 papers · 1 filter
A Systematic Approach to Generating Accurate Neural Network Potentials: the Case of Carbon
Yusuf Shaidu, Emine Kucukbenli, Ruggero Lot +3
Availability of affordable and widely applicable interatomic potentials is the key needed to unlock the riches of modern materials modelling. Artificial neural network based approa…
Unifying framework for strong and fragile liquids via machine learning: a study of liquid silica
Ekin D. Cubuk, Andrea J. Liu, Efthimios Kaxiras +1
The fragility of a glassforming liquid characterizes how rapidly its relaxation dynamics slow down with cooling. The viscosity of strong liquids follows an Arrhenius law with a tem…
Moiré metrology of energy landscapes in van der Waals heterostructures
Dorri Halbertal, Nathan R. Finney, Sai S. Sunku +20
The emerging field of twistronics, which harnesses the twist angle between two-dimensional materials, represents a promising route for the design of quantum materials, as the twist…
Boosting the efficiency of ab initio electron-phonon coupling calculations through dual interpolation
Anderson S. Chaves, Alex Antonelli, Daniel T. Larson +1
The coupling between electrons and phonons in solids plays a central role in describing many phenomena, including superconductivity and thermoelecric transport. Calculations of thi…
Twisted Trilayer Graphene: a Precisely Tunable Platform for Correlated Electrons
Ziyan Zhu, Stephen Carr, Daniel Massatt +2
We introduce twisted trilayer graphene (tTLG) with two independent twist angles as an ideal system for the precise tuning of the electronic interlayer coupling to maximize the effe…
The first 100 days: modeling the evolution of the COVID-19 pandemic
Efthimios Kaxiras, George Neofotistos, Eleni Angelaki
A simple analytical model for modeling the evolution of the 2020 COVID-19 pandemic is presented. The model is based on the numerical solution of the widely used Susceptible-Infecti…