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Predicting Algae Potential as Alternative Energy Source with AI

Research scientists are using Artificial Intelligence (AI) 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 commercialisation of algal biofuel has been hindered by the relatively low yield and high harvesting cost. The limited light penetration and poor cultivation dynamics both contributed to the low yield. Overcoming these challenges could enable viable algal biofuels to reduce carbon emissions, mitigate climate change, alleviate petroleum dependency and transform the bioeconomy.

The researchers have previously been successful at finding methods to convert corn stubble, grasses and mesquite into biodegradable, lightweight materials and bioplastics. His latest project utilises 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 the best light availability.

Algae can be used as an alternative energy source for many industries, including biofuel and jet fuel. Algae is a good alternative fuel source for this industry. It’s an alternate feedstock for bioethanol refinery without the need for pretreatment. It’s lower cost than coal or natural gas. It also provides for a more efficient way of carbon capture and utilisation

Algae biofuel is regarded as one of the ultimate solutions for renewable energy, but its commercialisation is hindered by growth limitations caused by mutual shading and high harvest costs. We overcome these challenges by advancing machine learning to inform the design of a Semi-continuous Algal Cultivation (SAC) to sustain optimal cell growth and minimise mutual shading. We are using an aggregation-based sedimentation strategy designed to achieve low-cost biomass harvesting and economical SAC.

– Joshua Yuan, PhD, AgriLife Research Scientist

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.

Algae as a renewable fuel source was a hot topic a decade ago. As a result, there’s a lot of scepticism. I was even sceptical. However, the work that Joshua is doing is incredibly innovative. We were excited to partner on this project. At the productivity levels, they obtain—and given the low-cost harvest that the strain allows—it shows a lot of promise.

Despite the significant potential and extensive efforts, the commercialisation of algal biofuel has been hindered by limited sunlight penetration, poor cultivation dynamics, relatively low yield, and the absence of cost-effective industrial harvest methods. This technology is proven to be affordable and help propel algae as a true alternative form of energy.

As reported by OpenGov Asia, the U.S. Department of Energy (DOE) announced $175 million for 68 research and development projects aimed at developing disruptive technologies to strengthen the nation’s advanced energy enterprise. Led by DOE’s Advanced Research Projects Agency-Energy (ARPA-E), the OPEN 2021 program prioritises funding high-impact, high-risk technologies that support novel approaches to clean energy challenges. DOE’s Argonne National Laboratory was awarded $7.8 million for three projects.

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