Cargando…
Machine learning potentials for complex aqueous systems made simple
Simulation techniques based on accurate and efficient representations of potential energy surfaces are urgently needed for the understanding of complex systems such as solid–liquid interfaces. Here we present a machine learning framework that enables the efficient development and validation of model...
Autores principales: | Schran, Christoph, Thiemann, Fabian L., Rowe, Patrick, Müller, Erich A., Marsalek, Ondrej, Michaelides, Angelos |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
National Academy of Sciences
2021
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8463804/ https://www.ncbi.nlm.nih.gov/pubmed/34518232 http://dx.doi.org/10.1073/pnas.2110077118 |
Ejemplares similares
-
Water
Flow in Single-Wall Nanotubes: Oxygen Makes
It Slip, Hydrogen Makes It Stick
por: Thiemann, Fabian L., et al.
Publicado: (2022) -
Classical Quantum
Friction at Water–Carbon
Interfaces
por: Bui, Anna T., et al.
Publicado: (2023) -
Teams: learning made simple
por: Partridge, Lesley
Publicado: (2007) -
MSX made simple: made simple computerbooks
por: Norman, Margaret
Publicado: (1986) -
Healthcare analytics made simple: techniques in healthcare computing using machine learning and Python
por: Kumar, Vikas
Publicado: (2018)