Correlating physico-chemical properties of analytes with Hansen solubility parameters of solvents using machine learning algorithm for predicting suitable extraction solvent

Correlating physico-chemical properties of analytes with Hansen solubility parameters of solvents using machine learning algorithm for predicting suitable extraction solvent

Abstract Artificial neural networks (ANNs) are biologically inspired algorithms designed to simulate the way in which the human brain processes information. In sample preparation for bioanalysis, liquid–liquid extraction (LLE) represents an important step with the extraction solvent selection is the...

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Bibliographic Details
Main Authors: Eman A. Mostafa, Mohammad Abdul Azim, Asmaa A. ElZaher, Ehab F. ElKady, Marwa A. Fouad, Fatma H. Ghazy, Esraa A. Radi, Mahmoud Abo El Makarim Saleh, Ahmed M. El Kerdawy
Format: Article
Language:English
Published: Nature Portfolio 2024-08-01
Series:Scientific Reports
Subjects:
Liquid–liquid extraction
Artificial Neural Network model
Hansen solubility parameters
Extraction solvent prediction
Model validation
Online Access:https://doi.org/10.1038/s41598-024-68981-9

Internet

https://doi.org/10.1038/s41598-024-68981-9

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