Cargando…
Electronic Descriptors for Supervised Spectroscopic Predictions
[Image: see text] Spectroscopic properties of molecules hold great importance for the description of the molecular response under the effect of UV/vis electromagnetic radiation. Computationally expensive ab initio (e.g., MultiConfigurational SCF, Coupled Cluster) or TDDFT methods are commonly used b...
Autores principales: | de Armas-Morejón, Carlos Manuel, Montero-Cabrera, Luis A., Rubio, Angel, Jornet-Somoza, Joaquim |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
American Chemical Society
2023
|
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10061681/ https://www.ncbi.nlm.nih.gov/pubmed/36877528 http://dx.doi.org/10.1021/acs.jctc.2c01039 |
Ejemplares similares
-
Real-Time Propagation TDDFT and Density Analysis for
Exciton Coupling Calculations in Large Systems
por: Jornet-Somoza, Joaquim, et al.
Publicado: (2019) -
Visual analytics in cheminformatics: user-supervised descriptor selection for QSAR methods
por: Martínez, María Jimena, et al.
Publicado: (2015) -
Self-Supervised Point Set Local Descriptors for Point Cloud Registration
por: Yuan, Yijun, et al.
Publicado: (2021) -
An Explainable Supervised Machine Learning Model for Predicting Respiratory Toxicity of Chemicals Using Optimal Molecular Descriptors
por: Jaganathan, Keerthana, et al.
Publicado: (2022) -
Machine learning recognition of protein secondary structures based on two-dimensional spectroscopic descriptors
por: Ren, Hao, et al.
Publicado: (2022)