IIT Madras uses AI to study fuel production from biomass

According to researchers, extracting fuel from biomass can tremendously help the country attain fuel self-sufficiency.  

Researchers at the Indian Institute of Technology (IIT) Madras are using artificial intelligence (AI) tools to study the processes involved in conversion of biomass to gaseous fuel.  The research was led by Himanshu Goyal, Department of Chemical Engineering, IIT Madras, and Niket S Kaisare, Department of Chemical Engineering, IIT Madras.  

The research team used a machine learning (ML) method called Recurrent Neural Networks (RNN) to study the reactions that occur during the conversion of lignocellulosic biomass into energy dense syngas (gasification of biomass). The team said with increasing environmental concerns associated with petroleum-derived fuels, biomass is a practical solution, not in the conventional sense of directly burning wood, cow dung cakes, and coal, but as a source of energy-dense fuel.  

750 million MT biomass produced annually in India 

Researchers all over the world are finding methods to extract fuel from biomass such as wood, grass, and even waste organic matter. Such biomass-derived fuel is particularly relevant to India because the current availability of biomass in India is estimated at about 750 million metric tonnes per year and extracting fuel from biomass can tremendously help the country attain fuel self-sufficiency.  

Niket S Kaisare said, “The novelty of our ML approach is that it is able to predict the composition of the biofuel produced as a function of the time the biomass spends in the reactor. We used a statistical reactor for accurate data generation, which allows the model to be applied over a wide range of operating conditions.” 

The team believes that the rapid advancements in computational methods must be integrated with core engineering for faster development and deployment of deep tech solutions. 

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