Microwave-assisted Catalytic Biodiesel Production
Rizwan Fattah
Highly Cited Researcher 2023 & 2022 | Postdoctoral Fellow at UTS | Associate Editor at Frontiers in Energy Research
Microwave-enhanced biodiesel synthesis is a favoured approach due to various advantages such as decreased energy usage, a significant reduction in reaction durations and solvent needs, higher selectivity, and improved conversions with the generation of fewer byproducts. Because of society’s increased concern for sustainability, the conversion of bio-based feedstocks into biodiesel is an important study topic. Various technologies have been used for biodiesel production, one of which, the application of microwaves, has been shown to hold a lot of promise. Microwaves are part of the electromagnetic spectrum, with wavelengths ranging from 1 cm to 1 m (30 GHz to 300 MHz). This work investigates the use of microwave radiation to produce biodiesel at a frequency of 2.45 GHz, the normal operating range available for commercially accessible microwave applicators. It is possible to accelerate the rate of reactions and improve selectivity by using microwave heating instead of conventional heating. Several parameters, including the catalyst type and concentration, microwave irradiation power, reaction temperature, type of alcohol and alcohol-to-oil ratio, the water content of oil, and stirring rate, could all influence microwave-assisted biodiesel production. As a result, it is critical to thoroughly understand these parameters' effects on the biodiesel production process.
This chapter has been published in "Advances in Microwave-assisted Heterogeneous Catalysis" (https://books.rsc.org/books/book/2135/Advances-in-Microwave-assisted-Heterogeneous)
Research Assistant & Scientia PhD Research Fellow at the University of New South Wales (UNSW), Sydney, Australia
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Senior Lecturer at University of Malaya [Areas of Interest: Renwable Energy, Hydrogen, Technoeconomics, LCA modelling, Green steel, Gasification, Biomass, Biofuel, Multiphase flow, Optimisation, Python, CFD, Aspen]
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