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Graphene-based catalysts for biodiesel production: Characteristics and performance

Nazloo, E.K., Moheimani, N.R.ORCID: 0000-0003-2310-4147 and Ennaceri, H. (2022) Graphene-based catalysts for biodiesel production: Characteristics and performance. Science of The Total Environment . Art. 160000.

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Link to Published Version: https://doi.org/10.1016/j.scitotenv.2022.160000
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Abstract

Biodiesel is a promising alternative to reduce the dependency on fossil fuels. However, biodiesel's cost is still higher than its petroleum counterpart, hence its production process must be modified to make it economically viable. Microalgae are an alternative feedstock to replace agricultural crops for biodiesel production, and offer several advantages such as fast growth, use of non-arable land, growth in saline and wastewater, and high lipid yield. Unfortunately, biodiesel production from microalgae is very energy-intensive and costly, mainly due to the high energy consumption required for dewatering and drying. Therefore, utilizing wet microalgal biomass instead of dry biomass can be a promising solution to reduce the biodiesel production cost Furthermore, the use of heterogeneous catalysts offers high efficiency, recoverability, and reusability, and is therefore very promising from the economic and environmental perspectives. The unique characteristics of graphene-based nano-catalysts, such as their high surface area, two-dimensional structure, and functional groups, make them suitable candidates for biodiesel production. In this review, the use of graphene-based catalysts for biodiesel production is analyzed in depth, and their efficiency compared to other heterogeneous catalysts is scrutinized. Moreover, their recoverability, reusability, and economic feasibility are critically discussed, and their potential to produce biodiesel from wet microalgae is explored as a sustainable and cost-effective approach.

Item Type: Journal Article
Murdoch Affiliation(s): Centre for Sustainable Aquatic Ecosystems
Algae R&D Centre
Publisher: Elsevier BV
Copyright: © 2022 Elsevier B.V.
URI: http://researchrepository.murdoch.edu.au/id/eprint/66536
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