Prediction of supercritical fluid chromatographic retention factors at different percents of organic modifiers in mobile phase

Journal of Separation Science

Volumn 32, Issue 4, 2009, Pages 653-659

  Fatemi, Mohammad H ^a   Malekzadeh, Hanieh ^a   Shamseddin, Hoda ^a  

^a UNIVERSITY OF MAZANDARAN   (Iran)

Author keywords

Artificial neural network; Molecular descriptor; Quantitative structure relention relationship; Retention factor; Supercritical fluid chromatography

Indexed keywords

ARTIFICIAL NEURAL NETWORK; MOLECULAR DESCRIPTOR; QUANTITATIVE STRUCTURE RELENTION RELATIONSHIP; RETENTION FACTOR; SUPERCRITICAL FLUID CHROMATOGRAPHY;

BACKPROPAGATION; CHROMATOGRAPHIC ANALYSIS; EFFLUENT TREATMENT; GAS CHROMATOGRAPHY; METHANOL; NEURAL NETWORKS; ORGANIC COMPOUNDS; SULFUR COMPOUNDS; SUPERCRITICAL FLUIDS; WIRELESS NETWORKS;

STATISTICAL TESTS;

METHANOL; ORGANIC COMPOUND;

ARTICLE; ARTIFICIAL NEURAL NETWORK; MULTIPLE LINEAR REGRESSION ANALYSIS; PRIORITY JOURNAL; QUANTITATIVE ANALYSIS; STATISTICAL MODEL; STATISTICAL PARAMETERS; STRUCTURE ANALYSIS; SUPERCRITICAL FLUID CHROMATOGRAPHY; VALIDATION PROCESS;

EID: 66149127764     PISSN: 16159306     EISSN: 16159314     Source Type: Journal    
DOI: 10.1002/jssc.200800594     Document Type: Article

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