Interatomic potentials for ionic systems with density functional accuracy based on charge densities obtained by a neural network

A charge optimized many-body (comb) potential for titanium and titania

(2014) Yu-Ting Cheng et al.   JOURNAL OF PHYSICS-CONDENSED MATTER

Orbital-free bond breaking via machine learning

(2013) John C. Snyder et al.   JOURNAL OF CHEMICAL PHYSICS

An Extended Charge Equilibration Method

(2012) Christopher E. Wilmer et al.   Journal of Physical Chemistry Letters

Finding Density Functionals with Machine Learning

(2012) John C. Snyder et al.   PHYSICAL REVIEW LETTERS

Atom-centered symmetry functions for constructing high-dimensional neural network potentials

(2011) Jörg Behler   JOURNAL OF CHEMICAL PHYSICS

High-dimensional neural-network potentials for multicomponent systems: Applications to zinc oxide

(2011) Nongnuch Artrith et al.   PHYSICAL REVIEW B

Second-generation charge-optimized many-body potential forSi/SiO2and amorphous silica

(2010) Tzu-Ray Shan et al.   PHYSICAL REVIEW B

Gaussian Approximation Potentials: The Accuracy of Quantum Mechanics, without the Electrons

(2010) Albert P. Bartók et al.   PHYSICAL REVIEW LETTERS

Daubechies wavelets as a basis set for density functional pseudopotential calculations

(2008) Luigi Genovese et al.   JOURNAL OF CHEMICAL PHYSICS

Pressure-induced phase transitions in silicon studied by neural network-based metadynamics simulations

(2008) Jörg Behler et al.   PHYSICA STATUS SOLIDI B-BASIC SOLID STATE PHYSICS