Publications using the ænet code


N. Artrith*, A. Urban, and G. Ceder*,
“Constructing first-principles phase diagrams of amorphous LixSi using machine-learning-assisted sampling with an evolutionary algorithm”,
J. Chem. Phys. 148 (2018) 241711. (Editor’s Pick) (preprint)


N. Artrith*, A. Urban, and G. Ceder*,
“Efficient and accurate machine-learning interpolation of atomic energies in compositions with many species”,
Phys. Rev. B 96 (2017) 014112. (preprint)


J.S. Elias, N. Artrith, M. Bugnet, L. Giordano, G.A. Botton, A.M. Kolpak, and Y. Shao-Horn*,
“Elucidating the Nature of the Active Phase in Copper/Ceria Catalysts for CO Oxidation”,
ACS Catal. 6 (2016) 1675-1679.

N. Artrith* and A. Urban,
“An implementation of artificial neural-network potentials for atomistic materials simulations: Performance for TiO2”,
Comput. Mater. Sci. 114 (2016) 135-150. (Editor’s Choice)


N. Artrith* and A.M. Kolpak,
“Grand canonical molecular dynamics simulations of Cu-Au nanoalloys in thermal equilibrium using reactive ANN potentials”,
Comput. Mater. Sci. 110 (2015) 20-28.


N. Artrith* and A.M. Kolpak,
“Understanding the Composition and Activity of Electrocatalytic Nanoalloys in Aqueous Solvents: A Combination of DFT and Accurate Neural Network Potentials”,
Nano Lett. 14 (2014) 2670–2676.