Green fuel synthesis from Jatropha curcas seed oil: A Computational Approach using python programming language

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Sangeeta D Benni, Harshada Dabhade, Ashwini Deshpande, Sarita Bansal, Namrata Saravade, Sarika Satpute, Anil Hulsure, Rameshwar Changdeo Dokhe, Mayuresh Patil, Kasturi Apte

Abstract

The depletion of fossil fuels and environmental concerns in the recent era has gained significant attention in the production of biodiesel from non-edible seed oils as an alternative fuel. Biodiesel is one of the renewable fuel to replace fossil fuel. The synthesis of biodiesel from the seed oils is time consuming and costly. In order to predict new seed oils in biodiesel synthesis, several studies have been conducted to suggest the advantages of artificial intelligence in the field of producing green energy. The fourth industrial revolution is thought to be fuelled by artificial intelligence (AI) and machine learning algorithms, which can understand complicated  issues with non-linear correlations. In the present study attempt has been made to predict the fuel properties of Jatropha curcas seed oil using python programming language. The fatty acid composition required for calculation is derived from literature. This code can be preserved and used multiple times to analyse the fuel properties which is time saving. The values obtained are well within the range of ASTM and EN standards.

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