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Influence of the medium conditions on enzymatic oxidation of bisphenol A
Author(s) -
Yalçınkaya Zeki,
Gün Selim,
Şahan Tekin,
Birhanlı Emre,
Sahiner Nurettin,
Aktaş Nahit,
Yeşilada Özfer
Publication year - 2014
Publication title -
the canadian journal of chemical engineering
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.404
H-Index - 67
eISSN - 1939-019X
pISSN - 0008-4034
DOI - 10.1002/cjce.21920
Subject(s) - response surface methodology , central composite design , chemistry , bisphenol a , quadratic model , monomer , methanol , solvent , chromatography , polymerization , laccase , correlation coefficient , enzyme , organic chemistry , mathematics , polymer , epoxy , statistics
A multistep response surface methodology (RSM) was successfully applied to optimise the medium conditions for the enzymatic polymerisation of bisphenol A (BPA). The laccase enzyme used as the catalyst was derived from Funalia trogii (ATCC 200800) yeast culture. The enzymatic polymerisation rate of BPA, based on the measurements of the initial dissolved oxygen (DO) consumption rate in a closed batch system, was studied through RSM. Initially the most effective medium factors, which are monomer concentration (mg/L), temperature (°C) and solvent content (% methanol), were determined through Plackett–Burman Design (PBD), then the steepest ascent combined with central composite design (CCD) steps were applied to evaluate the optimal reaction conditions for the enzymatic polymerisation. The optimal conditions were evaluated to be 748.46 mg/L, 32.24°C and 15.92% for monomer concentration, temperature and solvent content, respectively. A quadratic model was developed through RSM to represent DO consumption in the medium. The maximum DO consumption rate was calculated to be 0.093 mg DO/L min. Several repetitions were conducted at the optimal conditions to validate the system performance. The data evaluated from the quadratic model were in good agreement with those measured experimentally. The variations between the values did not exceed 10%. The correlation coefficient, R 2 , was calculated to be 0.95, which indicates that 95% of results can be explained by model.