Evaluation of synthetic and bio-based additives as oxidation stability enhancers in palm biodiesel

Lau, Chi Hou (2025) Evaluation of synthetic and bio-based additives as oxidation stability enhancers in palm biodiesel. PhD thesis, University of Nottingham.

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Abstract

Study on the antioxidants’ efficiency on biodiesel becomes crucial as the research for greener fuel continues. Set against this background, this thesis aims to evaluate the effects of synthetic and bio-based additives in palm biodiesel through a comprehensive assessment of fuel stability properties, oxidation kinetics and thermodynamics of doped fuels, and long-term storage stability. Synthetic additives were found to be more effective compared to their bio-based counterparts in terms of oxidation stability index (OSI), however, butylated hydroxyanisole (BHA) and tert-butyl hydroquinone (TBHQ) showed contradictory OSI results from Rancimat and PetroOXY test methods. Similar findings were observed in the long-term storage study which highlighted that TBHQ was the best additive followed by BHA and α-T being inefficient in long term storage of palm biodiesel. In addition, kinetics modelling utilising regression analyses coupled with error functions for doped palm biodiesels determined that BHA, BHT, TBHQ, and α-T adhered to the first order kinetic model judging from the high R and R2 values and low χ2 values obtained. The increase in Ea for DPOME showed that the performance of all additives was great, while positive ΔH‡, negative ΔS‡ and positive ΔG‡ values suggested that all oxidation reactions were endothermic, non-spontaneous and endergonic. The gas chromatography-mass spectrometry (GC-MS) analyses revealed that 3-octyl-oxiraneoctanoic acid ME, and 17-octadecynoic acid ME were the major oxidation products of palm biodiesel. ANN models were also developed to predict fuel stability properties, and the accuracy of the models was in the order of Rancimat IP > PetroOXY IP > kinematic viscosity > acid value > iodine value. Developed models highlighted the potential of ANN in reducing cost and time needed for analysis. Comprehensive evaluation of additives in palm biodiesel were carried out.

Item Type: Thesis (University of Nottingham only) (PhD)
Supervisors: Gan, Suyin
Ng, Hoon Kiat
Lee, Lai Yee
Lau, Harrison Lik Nang
Keywords: palm biodiesel; antioxidant additives; oxidation stability; kinetics and thermodynamics; artificial neural network (ANN) modeling
Subjects: T Technology > TP Chemical technology
Faculties/Schools: University of Nottingham, Malaysia > Faculty of Science and Engineering — Engineering > Department of Chemical and Environmental Engineering
Item ID: 81408
Depositing User: Lau, Chi
Date Deposited: 26 Jul 2025 04:40
Last Modified: 26 Jul 2025 04:40
URI: https://eprints.nottingham.ac.uk/id/eprint/81408

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