Statistical Analysis of Enzymatic Reaction Parameters for Biolubricant Synthesis via Response Surface Methodology (RSM)


Kutluk Gürkaya B., KUTLUK T., KAPUCU N.

Iranian Journal of Chemistry and Chemical Engineering, cilt.42, sa.6, ss.1995-2007, 2023 (SCI-Expanded) identifier

  • Yayın Türü: Makale / Tam Makale
  • Cilt numarası: 42 Sayı: 6
  • Basım Tarihi: 2023
  • Doi Numarası: 10.30492/ijcce.2022.552455.5306
  • Dergi Adı: Iranian Journal of Chemistry and Chemical Engineering
  • Derginin Tarandığı İndeksler: Science Citation Index Expanded (SCI-EXPANDED), Scopus, Directory of Open Access Journals
  • Sayfa Sayıları: ss.1995-2007
  • Anahtar Kelimeler: Biodiesel, Biolubricant, Lipase, Response Surface methodology, Trimethylolpropane ester
  • Kocaeli Üniversitesi Adresli: Evet

Özet

Recently, the synthesis of biolubricants has been the focus of researchers because of their good lubricating properties and environmentally friendly products. This study was performed to optimize reaction parameters for the enzymatic transesterification reaction between waste edible oil methyl ester (biodiesel, FAME) and trimethylolpropane (TMP) by using Response Surface Methodology (RSM). The parameters that affect the enzymatic transesterification reaction were chosen as temperature (35–55°C), amount of catalyst (0–10 %wt. of mixture), TMP-to-FAME molar ratio (0.17-0.33), and reaction time (0–96 h), to produce TMP triester (biolubricant). Response surface methodology (RSM) and three-level–four-factor Central Composite Design (CCD) were employed to evaluate the effects of these synthesis parameters on the percentage conversion of FAME by transesterification. Enzyme amount and reaction time were the most important variables. The optimum reaction conditions were determined to be the temperature at 50°C; the amount of catalyst, 5%wt; molar ratio, 0.25 and 48 h of reaction time, under these conditions 91% TMP ester's yield was obtained. The interaction parameter of the lipase quantity with the FAME to TMP molar ratio was found to be the most important among all of the other parameters.