New Delhi: IIT Madras researchers are utilising AI tools for studying the fuel production process from biomass. The current biomass availability in India is estimated to be about 750 million metric tonnes per year.
Studying these processes through hands-on experiments is time-consuming & expensive, whereas computer simulations and modelling can help us obtain quicker insights that can be used to build the processes and plants for biomass processing.
“With increasing environmental concerns associated with petroleum-derived fuels, biomass is a practical solution, not in the conventional sense of directly burning cow dung cakes, wood and coal, but also as a source of energy-dense fuel. Researchers all over the world are finding methods to extract fuel from biomass such as wood, grass, and even waste organic matter,” IIT Madras researchers said.
Such biomass-derived fuels are especially crucial to India because the present biomass availability in the country is estimated at around 750 million metric tonnes per year, and the production of fuel from it can immensely help the country in achieving fuel self-sufficiency.
This research project was led by Dr Himanshu Goyal, Assistant Professor, Department of Chemical Engineering, IIT Madras and Dr Niket S Kaisare, Professor, Department of Chemical Engineering, IIT Madras.
Along with them, the student researcher in this project was Krishna Gopal Sharma, Computer science undergrad and Young Research Fellow IIT-M.
Explaining the importance of such studies, Dr Himanshu Goyal, Assistant Professor, Department of Chemical Engineering, IIT Madras, said, "Understanding the complex mechanisms involved in the transformation of raw biomass into fuel is important for the designing of processes and optimizing reactors for the purpose."
“There is an urgent need to train the next generation of engineers on high-performance computing and machine learning skills so that they can address some of the biggest challenges before us, such as developing zero-emission technologies to tackle climate change. This work is one such example,” Dr Goyal further said.
The research team of IIT Madras used an ML method, Recurrent Neural Networks (RNN) to study the reactions that occur during the conversion of lignocellulosic biomass into energy-dense syngas (gasification of biomass).
Even though models are being established across the world to study the conversion of biomass into fuels and chemicals, most of them take a long time to become operational.
However, Artificial Intelligence tools such as Machine Learning (ML) can hasten these modelling processes. The team believes that rapid advancements in computational methods must be integrated with core engineering for the development and deployment of deep tech solutions in a faster manner.
Recent results of their modelling studies were published in the prestigious Royal Society of Chemistry journal Reaction Chemistry and Engineering. The paper has been co-authored by Dr Himanshu Goyal, Dr Niket Kaisare and Mr Krishna Gopal Sharma, Fourth Year CSE Student, IIT Madras.
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