Predicting the capability of carboxylated cellulose nanowhiskers for the remediation of copper from water using response surface methodology (RSM) and artificial neural network (ANN) models

Industrial Crops and Products

Volumn 93, Issue , 2016, Pages 108-120

  Hamid, Hazren A ^a   Jenidi, Youla ^a,b   Thielemans, Wim ^c   Somerfield, Christopher ^a   Gomes, Rachel L ^a  

^a UNIVERSITY OF NOTTINGHAM   (United Kingdom)

^b AECOM   (United Kingdom)

^c UNIVERSITY OF LEUVEN   (Belgium)

Author keywords

Adsorption; Artificial neural networks; Cellulose nanowhiskers; Cu(II) ions; Response surface methodology

Indexed keywords

ADSORPTION; CARBOXYLATION; DYES; ISOTHERMS; KINETICS; MEAN SQUARE ERROR; NANOWHISKERS; NEURAL NETWORKS; SURFACE PROPERTIES; WASTEWATER TREATMENT;

ARTIFICIAL NEURAL NETWORK MODELS; CELLULOSE NANOWHISKERS; COEFFICIENT OF DETERMINATION; CU IONS; LANGMUIR AND FREUNDLICH ISOTHERM MODELS; PSEUDO-SECOND-ORDER KINETIC MODELS; RESPONSE SURFACE METHODOLOGY; WASTEWATER TREATMENT PLANTS;

CELLULOSE;

ADSORPTION; ARTIFICIAL NEURAL NETWORK; CATION; CELLULOSE; COPPER; CRYSTAL; DATA SET; PERFORMANCE ASSESSMENT; POLLUTANT REMOVAL; REACTION KINETICS; WASTEWATER TREATMENT PLANT;

EID: 84971655103     PISSN: 09266690     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.indcrop.2016.05.035     Document Type: Article

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