In September 2021, the U.S. Department of Energy (DOE) awarded the Lehigh University Energy Research Center (ERC) a new $3.5 million project to develop advanced technology that would rapidly detect and analyze Municipal Solid Waste (MSW) streams.
The technology will be a blend of Laser-Induced Breakdown Spectroscopy (LIBS) and Raman Spectroscopy and will provide real-time, in-situ spectra for further analysis by AI algorithms. The project will engineer and build both the hardware and software for in-situ demonstration at TRI’s MSW-biofuels pilot plant. By allowing real-time characterization of MSW feedstock for feed-forward process control of downstream biofuel production processes, this supports the Bioenergy Technology Office’s goal of innovation that accelerates feedstock technologies that would propel a bio-economy.
In total, there are 11 university- and industry-led projects that are developing biomass resources that can be converted to low-carbon fuel for airplanes and ships. In regards to the larger DOE project, Secretary of Energy Jennifer Granholm said:
“From food waste to yard trimmings, biomass technology is converting our everyday trash into low-carbon fuel for planes and ships while cutting costs and supporting our critical transportation sector.
“The companies and universities leading these projects will ensure that our cutting-edge biofuel technologies reduce carbon emissions, create new jobs up and down the supply chain, and are made in America by American workers.”
This is part of a much larger project, a $34 million effort from the Bioenergy Technology Office of Energy Efficiency & Renewable Energy. The purpose is to support the research and development that will have a high impact and improve as well as produce biofuels, biopower, and bioproducts.
The team, led by the ERC, will include the Energy Research Company (ERCo), the DOE’s National Energy Technology Laboratory, ThermoChem Recovery International, Covanta Energy, the University of Toledo, and SpG Consulting.
From Lehigh University, Dr. Carlos Romero who is the Principal Research Scientist and Director of the ERC Zheng Yao, a research scientist from the ERC, and Professor Farrah Moazeni from the Department of Civil & Engineering are participating. One notable takeaway is that AI is being used to lead the way to increased waste-to-energy production.
Lehigh University published an article with a few more details of its part in this project. In that article, Dr. Carolos Romero stated:
“There are different ways to process trash.
“One is to take it to a landfill, another is burning it to produce electricity, and another is utilizing it as a feedstock for producing biofuels and bioproducts. However, the nature of MSW, a very heterogeneous material, with large variability in its physical, chemical and biological characteristics, poses significant challenges in optimizing MSW conversion processes.”
Yao spoke of how both the ERC and ERCo have worked on a method using both LIBS and AI to better analyze coal for power generation.
“With LIBS alone, we were only able to measure the elemental composition of the fuel. But, by using AI neural networks we were able to improve measurement accuracy and correlate elemental composition to other high order parameters such as calorific value and ash fusion temperature, for example.”
Dr. Romero noted that waste-to-energy produces have a need for accurate analysis of the waste materials in any given lot.
“There are standardized procedures for how a representative sample is arrived at and analyzed.
“The team’s innovative LIBS-Raman Spectroscopy, combined with AI, has the potential to significantly improve the accuracy of the analysis as well as the speed at which it occurs while facilitating the incorporation of this information into the bioenergy reactor process control.”
I had a short email chat with Yao, who shared that the ERC’s multi-discipline research arena included Traditional and Renewable Power Generations. The ERC aims to solve national and global energy and energy-related problems. The team does this by collaborating with all levels of governmental agencies, energy businesses, technology developers, and suppliers as well as the research community and academic institutions.
He also shared some more details on exactly what the project will develop. This project will develop a new optical technique that will enable rapid detection and analysts of MSW streams and the research team focused on the following five primary objectives:
- Research optical techniques for online MSW detection and quantification.
- Develop Artificial Intelligence (AI) algorithms for system data processing.
- Design an integrated prototype and associated AI software.
- Install and demonstrate prototype at an MSW plant with an industrial environment typical of MSW processing facilities.
- Evaluate prototype performance in terms of meeting Department of Energy’s (DOE’s) project metrics.
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