𝔖 Bobbio Scriptorium
✦   LIBER   ✦

Prediction of retention factors in micellar electrokinetic chromatography from theoretically derived molecular descriptors

✍ Scribed by Baher, Elham ;Fatemi, Mohammad H. ;Konoz, Elahe ;Golmohammadi, Hassan


Book ID
106196848
Publisher
Springer-Verlag
Year
2006
Weight
101 KB
Volume
158
Category
Article
ISSN
0344-838X

No coin nor oath required. For personal study only.


πŸ“œ SIMILAR VOLUMES


Artificial neural network prediction of
✍ Hassan Golmohammadi; Mohammed H. Fatemi πŸ“‚ Article πŸ“… 2005 πŸ› John Wiley and Sons 🌐 English βš– 92 KB πŸ‘ 1 views

## Artificial neural network prediction of retention factors of some benzene derivatives and heterocyclic compounds in micellar electrokinetic chromatography A 5-4-1 artificial neural network (ANN) was constructed and trained for prediction of the retention factors of some benzene derivatives and h

Development of a model for predicting re
✍ A. Craig Powell; Michael J. Sepaniak πŸ“‚ Article πŸ“… 1990 πŸ› John Wiley and Sons 🌐 English βš– 599 KB

## Abstract Instrumentation and a computational method are described that are capable of predicting retention times of solutes separated by solvent‐gradient micellar electrokinetic capillary chromatography (MECC). Theoretical predictions are based on capacity factor, electroosmotic flow rate, and m

Prediction of immobilized artificial mem
✍ Mohammad Hossein Fatemi; Hoda Shamseddin πŸ“‚ Article πŸ“… 2009 πŸ› John Wiley and Sons 🌐 English βš– 393 KB

## Abstract In this work multiple linear regression (MLR) was carried out for the prediction of immobilized artificial membrane (IAM) retention factors of 40 basic and neutral drugs in two mobile phase compositions. We developed some MLR models by using linear free energy relationships (LFER) param