In the past couple of years, the world has come to realize the importance of renewable sources of energy and the disadvantages of excessive use of fossil fuels. Numerous studies have been conducted to implicate the benefits of artificial intelligence in areas of green energy production. Artificial intelligence (AI) and machine learning algorithms are believed to be the driving forces behind the fourth industrial revolution and possess capabilities for interpreting non-linear relationships that exist in complex problems. Sustainable biofuels are derived from renewable resources such as plants, crops, and waste materials other than food crops. Unlike traditional fossil fuels such as coal and oil, biofuels are considered to be more sustainable and environmentally friendly. The work discusses the transesterification of jatropha oil into biodiesel using KOH and NaOH as alkaline catalysts. This research aims to examine and optimize the nonlinear relationship between transesterification process parameters (molar ratio, temperature, reaction time, and catalyst concentration) and biodiesel properties. The methodology employed in this study utilizes AI and machine learning algorithms to predict biodiesel properties and improve the yield and quality of biodiesel. Deep neural networks, linear regression, polynomial regression, and K-nearest neighbors are the algorithms implemented for prediction purposes. The research comprehensively examines the impact of individual transesterification process parameters on biodiesel properties, including yield, viscosity, and density. Furthermore, this research introduces the use of genetic algorithms for optimizing biodiesel production. The genetic algorithm (GA) generates optimal values for transesterification process parameters based on the desired biodiesel properties, such as yield, viscosity, and density. The results section presents the transesterification process parameters required for obtaining 72%, 85%, and 98% biodiesel yields. By leveraging AI and machine learning, this research aims to enhance the efficiency and sustainability of biodiesel production processes.

Covid 19 is a highly infectious disease caused by SARS-CoV-2 that can spread from an infected person’s nose, mouth during coughing & sneezing. One of the warriors against Covid-19 is personal protection equipment (PPE), which is indispensable for everyone working closely with Covid-19 patients. The kits are made of different types of plastics and their disposal is going to be a serious menace, if not taken care of properly. The sustainable alternative to handle cast-off PPE kit is to convert them into pyrolysis oil using a thermochemical process. In the present paper, pyrolysis of PPE kit is done in a lab scale reactor to get the pyrolysis oil that has the potential to be used as alternate fuel in the neat or in blended form with conventional fuels. GC-MS of the obtained oil shows the presence of (C-7 to C-32) hydrocarbon fraction. FTIR analysis of the oil is also done for functional group composition. The results obtained also support the application of pyrolyisis oil as an alternate fuel. Physico-chemical characteristics of the pyrolysis oil sample are also comparable to the commercially available fuel with exception of viscosity as the fuel obtained has not been fractionated and has both light and heavy naphtha. Graphical Abstract