United States – Texas A&M AgriLife Research scientists are using artificial intelligence to set a new world record for producing algae as a reliable, cost-effective source of biofuel for jet aircraft and other transportation needs.
The research is being led by Joshua Yuan, Ph.D., an AgriLife Research scientist, professor and chair of Synthetic Biology and Renewable Products in the Texas A&M College of Agriculture and Life Sciences Department of Plant Pathology and Microbiology.
To predict algae light penetration, growth, and optimal density, the project employs a patented artificial intelligence advanced learning model. The prediction model enables continuous harvesting of synthetic algae using hydroponics to maintain rapid growth at the optimal density for best light availability.
Yuan and his colleagues successfully achieved 43.3 grams per square meter per day of biomass productivity in an outdoor experiment, which would be a world record. The most recent DOE target is 25 grams per square meter per day.
Renewable energy source
Algae biofuel is regarded as one of the ultimate renewable energy solutions, but commercialization is hampered by growth limitations caused by mutual shading and high harvest costs.
Yuan stated that he is employing an aggregation-based sedimentation strategy in order to achieve low-cost biomass harvesting and cost-effective SAC. When the SAC is scaled up with an outdoor pond system, the biomass yield is 43.3 grams per square meter per day, lowering the minimum biomass selling price to around $281 per ton. In comparison, the standard low-cost biomass feedstock for ethanol is corn, which is currently around $6 per bushel or $260 per ton. Yuan’s method, on the other hand, does not necessitate any costly pre-treatment prior to fermentation. Before fermentation, the corn must be ground and the mash must be cooked.
Despite significant potential and extensive efforts, the commercialization of algal biofuel has been hampered by limited sunlight penetration, poor cultivation dynamics, relatively low yield, and a lack of cost-effective industrial harvest methods, according to Yuan.