Laccase immobilized manganese ferrite nanoparticle: Synthesis and LSSVM intelligent modeling of decolorization

• Published in: Water research (Oxford) Vol. 67; pp. 216 - 226
• Main Authors: Mahmoodi, Niyaz Mohammad, Arabloo, Milad, Abdi, Jafar
• Format: Journal Article
• Language: English
• Published: Kidlington Elsevier Ltd 15-12-2014; Elsevier
• Subjects: Applied sciences; Binary system decolorization; Binary systems; Biological and medical sciences; Biological treatment of waters; Biotechnology; Color; Coloring Agents; Decoloring; Dyes; Environment and pollution; Enzymes, Immobilized - chemistry; Exact sciences and technology; Ferric Compounds - chemistry; Ferrite; Fundamental and applied biological sciences. Psychology; Hydrogen-Ion Concentration; Industrial applications and implications. Economical aspects; Industrial wastewaters; Kinetics; Laccase; Laccase - chemistry; Laccase immobilization; Least-Squares Analysis; LSSVM modeling; Manganese; Manganese Compounds - chemistry; Manganese ferrite nanoparticle; Mathematical models; Metal Nanoparticles - chemistry; Models, Chemical; Nanostructure; Pollution; Support Vector Machine; Synthesis; Wastewaters; Water Pollutants, Chemical - analysis; Water Purification - methods; Water treatment and pollution; LSSVM modeling; Binary system decolorization; Synthesis; Manganese ferrite nanoparticle; Laccase immobilization; Discoloration; Organic dye; Enzyme; Nanoparticle; Support vector machine; Modeling; Biological purification; Enzymatic activity; Industrial waste water; Azo dye; Oxidoreductases; Learning algorithm; Entrapped microorganism; Nanostructured materials; Organic compounds; Laccase
• ISSN: 0043-1354; 1879-2448
• DOI: 10.1016/j.watres.2014.09.011

Laccase was immobilized onto manganese ferrite nanoparticle (MFN) and dye decolorization from single and binary systems was studied. The characteristics of laccase immobilized manganese ferrite nanoparticle (LIMFN) were investigated using Fourier transform infrared (FTIR) and scanning electron microscopy (SEM). Direct red 31 (DR31), Acid blue 92 (AB92) and Direct green 6 (DG6) were used. A least square support vector machine (LSSVM) was developed to predict the decolorization efficiency of various single and binary systems based on the obtained laboratory data under different experimental conditions. Statistical and graphical quality measures were also employed to evaluate the performance and accuracy of the developed intelligent models. It is shown that the predictions of the designed LSSVM models are in close agreement with the experimental data. The effects of LIMFN dosage, pH and dye concentration on dye decolorization from single and binary systems were evaluated. Decolorization kinetics followed Michaelis–Menten Model.
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•Laccase was immobilized onto manganese ferrite nanoparticle.•Dye decolorization from single and binary systems was studied.•Least square support vector machine (LSSVM) model was used.•The predictions of LSSVM model are in close agreement with the experimental data.•Decolorization kinetics followed Michaelis–Menten Model.