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Supercritical methanol transesterification is a well-established and efficient process that produces biodiesel by reacting methanol with triglycerides under extreme temperature and pressure conditions. Supercritical methanol transesterification is particularly valuable because it enables continuous conversion of free fatty acids and triglycerides into biodiesel, reducing the need to pre-treat waste and low-quality oils. For assessing supercritical methanol transesterification for simultaneous biodiesel production, we consider five processes: enzymatic transesterification, algal biofuel production, anaerobic digestion, hydro-treated vegetable oil, and biomass pyrolysis. But the main problem is that we don’t know which one is suitable for supercritical methanol transesterification for simultaneous biodiesel production. To this end, we design a model of Circular Uncertain Linguistic Intuitionistic Fuzzy Multi-Attribute Border Approximation Area Comparison-Technique for Order Preference by Similarity to Ideal Solution based on Hamacher theory. Finally, we compare our ranking models with prevailing ranking techniques using numerical examples to demonstrate the superiority and validity of the designed approaches. Despite these problems and challenges, our methods and models improve the efficiency of the procedure, reduce costs, and enhance the capability of supercritical methanol transesterification for sustainable large-scale biodiesel production.
Zafar et al. (Tue,) studied this question.