AI research foresees algae as likely alternative energy source

Texas A&M AgriLife Research scientists are using artificial intelligence to set a new world record for producing algae as a reliable, economic source for biofuel that can be used as an alternative fuel source for jet aircraft and other transportation needs.

The team’s findings were published in January in Nature Communications. Ongoing research is funded by the U.S. Department of Energy Fossil Energy Office. The work is also being funded by a gift from Dr. John ’90 and Sally ’92 Hood, who recently met with Yuan to discuss his biofuels research program. The gift is managed by the Texas A&M Foundation.

The project team includes Bin Long, a graduate student from the Department of Plant Pathology and Microbiology; Bart Fischer, Ph.D., co-director of the Texas A&M Agricultural and Food Policy Center and Texas A&M Department of Agricultural Economics; Henry Bryant, Ph.D., Department of Agricultural Economics; and Yining Zeng, Ph.D., staff scientist with the U.S. Department of Energy National Renewable Energy Laboratory.

Overcoming these challenges could enable viable algal biofuels to reduce carbon emissions, mitigate climate change, alleviate petroleum dependency and transform the bioeconomy, Yuan said.

Yuan has previously been successful at finding methods to convert corn stubble, grasses and mesquite into biodegradable, lightweight materials and bioplastics. His latest project utilizes a patented artificial intelligence advanced learning model to predict algae light penetration, growth and optimal density. The prediction model allows for continual harvest of synthetic algae using hydroponics to maintain the rapid growth at the optimal density to allow best light availability.

Texas A&M AgriLife Research scientists are using artificial intelligence for producing algae as a reliable, economic source for biofuel. This illustration depicts integration of machine learning-informed semi-continuous algal cultivation (SAC) and aggregation-based sedimentation (ABS) for biofuel production.

The method Yuan and team have successfully achieved in an outdoor experiment is 43.3 grams per square meter per day of biomass productivity, which would be a world record. The latest DOE target range is 25 grams per square meter per day.

Algae biofuel is regarded as one of the ultimate solutions for renewable energy, but its commercialization is hindered by growth limitations caused by mutual shading and high harvest costs.

Scaling-up the SAC with an outdoor pond system achieves a biomass yield of 43.3 grams per square meter per day, bringing the minimum biomass selling price down to approximately $281 per ton, according to the journal article. In comparison, the standard low-cost feedstock for biomass in ethanol is corn, which is currently approximately $6 per bushel or $260 per ton. However, Yuan’s process does not call for costly pre-treatment before fermentation. Corn must be ground and the mash must be cooked before fermentation.

Tags: AI, Algae, Alternative Energy, Texas A&M AgriLife Research
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