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Symmetry-Adapted Machine Learning for Tensorial Properties of Atomistic Systems
Here we present 1,000 structures each of a water monomer, water dimer, Zundel cation and bulk water used to train tensorial machine-learning models in Phys. Rev. Lett. 120,... -
Viscosity in water from first-principles and deep-neural-network simulations
We report on an extensive study of the viscosity of liquid water at near-ambient conditions, performed within the Green-Kubo theory of linear response and equilibrium ab initio... -
Mapping uncharted territory in ice from zeolite networks to ice structures
We report a large-scale density-functional-theory study of the configuration space of water ice. We geometry optimise 74,963 ice structures, which are selected and constructed... -
Interaction of water with nitrogen-doped graphene
We have studied the interaction of water and graphene doped with nitrogen in different configurations, namely, graphitic and pyridinic nitrogen, by means of the van der Waals... -
Efficient Training of ANN Potentials by Including Atomic Forces via Taylor Ex...
This data set contains atomic structures of water clusters, bulk water and rock-salt Li8Mo2Ni7Ti7O32 in the XCrySDen [1] structure format (XSF), and total energies are included... -
'eseis' - a comprehensive R software toolbox for environmental seismology
Environmental seismoloy is a scientific field that studies the seismic signals, emitted by Earth surface processes. This R package eseis provides all relevant functions to...
