Nongnuch Artrith
Publications by Year
Research Areas
Machine Learning in Materials Science, Advancements in Battery Materials, Advanced Battery Materials and Technologies, Electrocatalysts for Energy Conversion, Electronic and Structural Properties of Oxides
Most-Cited Works
- → An implementation of artificial neural-network potentials for atomistic materials simulations: Performance for TiO2(2016)506 cited
- → Best practices in machine learning for chemistry(2021)451 cited
- → High-dimensional neural-network potentials for multicomponent systems: Applications to zinc oxide(2011)398 cited
- → High-dimensional neural network potentials for metal surfaces: A prototype study for copper(2012)338 cited
- → Efficient and accurate machine-learning interpolation of atomic energies in compositions with many species(2017)333 cited
- → Understanding the Composition and Activity of Electrocatalytic Nanoalloys in Aqueous Solvents: A Combination of DFT and Accurate Neural Network Potentials(2014)209 cited
- → Electronic-Structure Origin of Cation Disorder in Transition-Metal Oxides(2017)200 cited
- → Elucidating the Nature of the Active Phase in Copper/Ceria Catalysts for CO Oxidation(2016)164 cited
- → Structural and Compositional Factors That Control the Li-Ion Conductivity in LiPON Electrolytes(2018)157 cited
- → Constructing first-principles phase diagrams of amorphous LixSi using machine-learning-assisted sampling with an evolutionary algorithm(2018)154 cited