Achieving such an understanding through hands-on experimentation will be time consuming and costly, and as such, computer simulation and modeling studies can provide quick insights into developing biomaterial conversion processes.
Researchers at the Indian Institute of Technology, Madras, are studying the processes involved in converting biomass to gaseous fuels using artificial intelligence. Achieving such an understanding through hands-on experimentation is time consuming and costly. Computer simulation and modeling studies can provide quick insights that can be used to create processes and plants for biomass processing.
With the growing environmental concerns associated with petroleum-derived fuels, biomass is a viable solution, not to burn wood, dung cakes and coal in the conventional sense, but as a source of energy-intensive fuel. Researchers around the world are finding ways to extract fuels from organic matter, such as wood, grass and even organic waste.
The energy derived from such biomass is particularly relevant to India as the current availability of biomass in India is estimated at around 750 million metric tons per year and the extraction of energy from them could greatly help the country achieve energy self-sufficiency.
The study was led by Dr. Himanshu Goel, Assistant Professor, Department of Chemical Engineering, IIT Madras and Dr. Niket S. Kaiser, Professor, Department of Chemical Engineering, IIT Madras.
Recent results from their modeling study were published in the prestigious peer-reviewed Royal Society of Chemistry Journal Reaction Chemistry and Engineering (DOI: 10.1039 / d1re00409c). The paper was co-authored by Dr. Himanshu Goyal, Dr. Niket Kaiser and Krishna Gopal Sharma, 4th year B.Tech. Student, Department of Computer Science and Engineering, IIT Madras.
While models are being developed around the world to understand the transformation of organic matter into fuels and chemicals, most models take a long time to become effective. Artificial intelligence tools such as machine learning (ML) can accelerate modeling processes.
The IIT Madras research team has used an ML method called Recurrent Neural Networks (RNN) that can study the reactions that occur during the conversion of lignocellulosic biomass into energy-dense synapses (gasification of biomass).
Dr. Himanshu Goyal’s research team uses AI equipment not only to study biomass-biofuel conversion but also for socially relevant and environmentally beneficial processes such as carbon capture (CO2 capture to prevent climate change) and the electrification of the chemical industry.
The team believes that rapid advances in computational methods need to be integrated with core engineering for the rapid development and deployment of deep technological solutions. Such development cannot be limited by specialties and categories.
Lead researcher, Dr. Goyal and Dr. Kaiser, IITM’s Department of Chemical Engineering, Student Researcher, Krishna Gopal Sharma, a Bachelor of Computer Science and a Young Research Fellow at the Institute.