Biodiesel production from mixed oils: A sustainable approach towards industrial biofuel production

Abstract

Biodiesel is considered eco-friendly, biodegradable, non-toxic, and carbon-neutral fuel. It is made from edible or non-edible oil feedstocks including other triglyceride sources. The production of biodiesel depends on the availability of a particular feedstock and the cost of desired raw materials. Biodiesel is mainly produced by the transesterification process using a suitable catalyst preferably a heterogeneous catalyst as it is more beneficial in terms of reusability, recovery, product purity, and production cost as well. Various reactors are developed to produce cost-effective biodiesel at the commercial level. The latest trend in biodiesel synthesis is the application of the machine learning (ML) technique to optimize the process parameters. The application of a mixture of two or more oils as feedstock either non-edible or edible oil is emphasized for biodiesel synthesis and is presently getting more importance. In this paper, the production of biodiesel from various mixed oil (hybrid oil) is reviewed and the effects of mixed oil on the reaction, physicochemical properties, fatty acid composition, and fuel quality of the product are discussed. The study highlighted the activity of various catalysts in the reaction of mixed oil and the economic feasibility. It was found that the ratio of mixed oil is an important factor in terms of conversion and quality of biodiesel. It is also revealed that the application of the ML technique is essentially useful to optimize production efficiency. The utilization of mixed oils will overcome the issues related to the non-availability of feedstocks and reduce the overall cost with improved quality of biodiesel. This approach enhances the production possibility of biodiesel at a large-scale and may boost the biorefinery sector satisfying the future energy demand if the research at the advanced level goes in the right direction.

Keywords

• Mixed oil
• Transesterification
• Biodiesel
• Machine learning technique
• Heterogeneous catalyst
• Reactors