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Artificial neural networks to model the enantioresolution of structurally unrelated neutral and basic compounds with cellulose tris(3,5-dimethylphenylcarbamate) chiral stationary phase and aqueous-acetonitrile mobile phases

Mireia Pérez‐Baeza, Yolanda Martı́n-Biosca, Laura Escuder‐Gilabert, M.J. Medina-Hernández, S. Sagrado

2022Journal of Chromatography A10 citationsDOIOpen Access PDF

Topics & Concepts

Artificial neural networkChemistryBiological systemAcetonitrileTrisCross-validationCelluloseFeature (linguistics)Phase (matter)MoleculePattern recognition (psychology)ChromatographyArtificial intelligenceComputer scienceOrganic chemistryBiologyBiochemistryLinguisticsPhilosophyAnalytical Chemistry and ChromatographyComputational Drug Discovery MethodsVarious Chemistry Research Topics
Artificial neural networks to model the enantioresolution of structurally unrelated neutral and basic compounds with cellulose tris(3,5-dimethylphenylcarbamate) chiral stationary phase and aqueous-acetonitrile mobile phases | Litcius