Texas A&M AgriLife Research experts are utilising AI, to set a new world record for generating algae as a reliable biofuel source. This step will pave the way for a greener and more cost-effective fuel source for jet planes and other modes of transportation. Led by Joshua Yuan, PhD, this study was published in Nature Communications. It is financed by the US Department of Energy’s Fossil Energy Office.
Due of mutual shading and the high cost of collection, one of the major issues with algae’s prominence was their growth restrictions. To overcome this, Machine Learning is being used by researchers to help with cell growth and prevent mutual shading. A sedimentation approach based on aggregation is also being developed to achieve low-cost biomass collection and cost-effective semi-continuous algae production (SAC).
The study team set a new record for biomass production by using an outdoor pond system to produce 43.3 grammes per square metre a day. The Department of Energy’s most recent target range was 25 grammes per square metre each day. The minimum biomass selling price is reduced to roughly $281 per tonne with this technique.
Despite several barriers to algae commercialization, this technique is cost-effective and contributes to the advancement of algae as a viable energy source. Yuan is of the assumption that by addressing these challenges, sustainable biofuels will be able to reduce carbon emission, mitigate climate change, reduce petroleum dependence and alter the bio-economy.
Algal biofuel is recognised as one of the ultimate renewable energy alternatives, but its commercialisation is hampered by mutual shading-induced growth restrictions and high harvest costs. Machine Learning was incorporated into the design of semi-continuous algal cultivation to resolve these obstacles and ensure optimal cell development while reducing mutual shading.
To achieve low-cost biomass collecting and cost-effective SAC, an aggregation-based sedimentation (ABS) technique is devised. The ABS is made possible by genetically modifying a fast-growing strain, Synechococcus elongatus UTEX 2973, to produce limonene, which improves the hydrophobicity of cyanobacterial cell surfaces and allows for effective cell aggregation and sedimentation.
Source: indiaai.gov.in