CX-101943: Machine learning based modeling framework to relate biomass tissue properties with handling and conversion performances

Award Number: DE-EE0008911
CX(s) Applied: A9, B3.6,
Bioenergy Technologies Office
Location(s): GA
Office(s): Golden Field Office

The U.S. Department of Energy (DOE) is proposing to provide federal funding to the University of Georgia Research Foundation (University of Georgia – ‘UGA’) to develop non-destructive imaging and machine learning tools to analyze targeted biomass properties, including chemical composition, conversion performance, and handling performance. Southern pine forest residues (SPFR) and corn stover would be collected, separated, and analyzed in laboratory settings using the tools developed as part of the project. Data acquired from assessments would be used to train machine learning algorithms.