Application of computational technologies for transesterification of waste cooking oil into biodiesel
Omojola Awogbemi, Dawood Desai
Abstract
Continued depletion of fossil-based energy resources, environmental concerns, and the necessity to assuage the ever-increasing global energy demand have resulted in efforts to find sustainable and renewable energy sources. Biodiesel, a variety of liquid biofuel, is a feasible renewable energy option to stem the growing emission of toxic emissions and promote energy sustainability. The need to update existing knowledge on the intensification of biodiesel production by deploying appropriate novel technologies makes the current study imperative. This study reviews the application of computational technologies for the transesterification of WCO into biodiesel. The study gives an overview of the generation, collection, pretreatment, and transesterification techniques for WCO, and the deployment of computation technologies in the transesterification process. The development and deployment of computational technologies such as artificial intelligence (AI), machine learning (ML), artificial neural networks (ANN), support vector machines (SVMs), and genetic algorithms (GA) for biodiesel synthesis are discussed. Using inputs such as process parameters and fatty composition, AI, ML, ANN, SVMs, and GA are applied to optimize the transesterification process, predict biodiesel properties, and increase biodiesel yield. The application of computational technologies eliminates trial and error, prevents materials and time wastage, ensures the production of quality biodiesel, and guarantees high biodiesel yield. With appropriate policy formulation and implementation, government funding and support, and future collaborative research, computational technologies hold enormous opportunities in biodiesel processing, energy security, and sustainability. • Waste cooking oil (WCO) is a low-cost and eco-friendly feedstock for biodiesel generation. • The need for energy security and sustainability has increased global biodiesel demand. • Deploying computational technologies enhances the transesterification of WCO to biodiesel. • Merits, drawbacks, policy recommendations, and future research directions are highlighted.