Cargando…
Machine learning of solvent effects on molecular spectra and reactions
Fast and accurate simulation of complex chemical systems in environments such as solutions is a long standing challenge in theoretical chemistry. In recent years, machine learning has extended the boundaries of quantum chemistry by providing highly accurate and efficient surrogate models of electron...
Autores principales: | Gastegger, Michael, Schütt, Kristof T., Müller, Klaus-Robert |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
The Royal Society of Chemistry
2021
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8409491/ https://www.ncbi.nlm.nih.gov/pubmed/34567501 http://dx.doi.org/10.1039/d1sc02742e |
Ejemplares similares
-
Machine learning molecular dynamics for the simulation of infrared spectra
por: Gastegger, Michael, et al.
Publicado: (2017) -
Automatic identification of chemical moieties
por: Lederer, Jonas, et al.
Publicado: (2023) -
Machine Learning Force Fields
por: Unke, Oliver T., et al.
Publicado: (2021) -
SpookyNet: Learning force fields with electronic degrees of freedom and nonlocal effects
por: Unke, Oliver T., et al.
Publicado: (2021) -
Unifying machine learning and quantum chemistry with a deep neural network for molecular wavefunctions
por: Schütt, K. T., et al.
Publicado: (2019)