Prediction of glycerol removal from biodiesel using ammonium and phosphunium based deep eutectic solvents using artificial intelligence techniques

Chemometrics and Intelligent Laboratory Systems

Volumn 118, Issue , 2012, Pages 193-199

  Shahbaz, Kaveh ^a   Baroutian, Saeid ^b   Mjalli, Farouq Sabri ^c   Hashim, Mohd Ali ^a   AlNashef, Inas Muen ^d  

^a UNIVERSITY OF MALAYA   (Malaysia)

^b SCION   (New Zealand)

^c SULTAN QABOOS UNIVERSITY   (Oman)

^d KING SAUD UNIVERSITY   (Saudi Arabia)

Author keywords

Biodiesel; Deep eutectic solvent; Glycerol; Neural networks; Removal

Indexed keywords

AMMONIUM BASED DEEP EUTECTIC SOLVENT; BIODIESEL; BROMINE DERIVATIVE; CHOLINE; DEEP EUTECTIC SOLVENT; GLYCEROL; METHYL TRIPHENYL PHOSPHONIUM BROMIDE; PHOSPHUNIUM BASED DEEP EUTECTIC SOLVENT; SOLVENT; UNCLASSIFIED DRUG;

ARTICLE; ARTIFICIAL INTELLIGENCE; ARTIFICIAL NEURAL NETWORK; CHEMICAL PROCEDURES; CONTROLLED STUDY; GLYCEROL REMOVAL; HYDROGEN BOND; POSITIVE FEEDBACK; PREDICTION; PRIORITY JOURNAL; QUALITY CONTROL; SYNTHESIS;

EID: 84868212961     PISSN: 01697439     EISSN: 18733239     Source Type: Journal    
DOI: 10.1016/j.chemolab.2012.06.005     Document Type: Article

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