back to top
14.1 C
New Delhi
Monday, December 23, 2024
spot_img

SRM University-AP Unveils Revolutionary Predictive System

SRM University-AP’s Net Zero Lab has made a historic contribution to sustainable energy innovation in a world struggling with the twin crises of climate change and depleting fossil fuel supplies. The lab has just invented a technology that, when combined with Patent No. 537715, will revolutionize the manufacturing of bio-oil—a renewable liquid fuel made from biomass, like algae.

This breakthrough uses state-of-the-art machine learning techniques to improve the efficiency and predictability of bio-oil production, while also offering a greener alternative to traditional fossil fuels.

The Promise of Bio-Oil

In the search for renewable energy sources, bio-oil is a ray of hope. It is a very adaptable substitute that is extracted from biomass and converted into a variety of fuels, such as kerosene, heavy fuel oil, diesel, gasoline, and liquefied petroleum gases. Nevertheless, conventional techniques for enhancing the hydrothermal liquefaction (HTL) process—a crucial step in turning biomass into bio-oil—are frequently labor-and time-intensive. This is where the ground-breaking system of SRM University-AP shines.

A Technological Breakthrough

The patented technology, titled “A System and a Method for Prediction of Bio-Oil Production via a Hydrothermal Liquefaction Process,” marks a significant breakthrough in the field. Led by Associate Professor Dr Karthik Rajendran, the research team has harnessed the power of machine learning to streamline the HTL process. By reducing the complexity and number of parameters involved, the system achieves an impressive 84% efficiency in crude oil yield, substantially improving conventional methods.

Machine learning algorithms optimize the elemental and biochemical composition, operational conditions, and proximate analysis of various algae species, resulting in a highly efficient and scalable method for bio-oil production. This not only enhances the yield but also reduces the time and labor required, making bio-oil a more viable and attractive option for widespread use.

Implications for Global Energy

The implications of this technological advancement extend far beyond academic research. By presenting a scalable, efficient, and sustainable method for bio-crude oil production, SRM University-AP’s innovation has the potential to revolutionize the energy industry on a global scale. The system’s ability to optimize production processes can significantly reduce dependence on fossil fuels, thereby contributing to a reduction in greenhouse gas emissions and a more sustainable energy future.

Call for Technology Transfer

Recognizing the transformative potential of their breakthrough, Dr Rajendran is eager to collaborate with academic researchers, industry leaders, and government agencies. Such partnerships are essential to fully realize the global benefits of this innovation and drive a greener, more sustainable future. By bringing this technology to market, these collaborations can help scale the production of bio-oil, thereby advancing global energy sustainability.

SRM University-AP’s pioneering work underscores the power of innovation and collaboration in advancing sustainable energy solutions. Their groundbreaking predictive system for bio-oil production not only represents a significant technological achievement but also offers a viable path towards a more sustainable and environmentally friendly energy future. For more information on technology transfer and collaboration opportunities, interested parties are encouraged to contact coordinator.ipr@srmap.edu.in. Through these efforts, SRM University-AP continues to lead the way in creating solutions that address some of the most pressing environmental challenges of our time.

Get the latest news updates and stay informed with FELA NEWS!

Related Articles

LEAVE A REPLY

Please enter your comment!
Please enter your name here

Stay Connected

3,625FansLike
67,000FollowersFollow
5,582SubscribersSubscribe
- Advertisement -spot_img

Latest Articles