Thanks to artificial intelligence, the cultivation of algae, which can both help us fight carbon dioxide and provide access to cheap biofuel, becomes much more effective and thus more profitable. Scientists have just figured out a way to facilitate the cultivation of algae on a large scale and at record pace.
Algae farming finally profitable? Artificial intelligence can make it happen
The idea is to use machine learning to control the chaotic growth of cyanobacterial algae. Thanks to a system developed by a team at Texas A&M University, this system is capable of producing over 43 grams of algae per square meter per day under experimental outdoor conditions. It is seemingly unimpressive, but keep in mind that it’s about twice the 25-gram level that the US Department of Energy is aiming for.
Such an acceleration of algae production has the potential to bring the price of algae biofuel to less than $ 1.32 per liter from the current $ 8.71 per liter. All because of a significant drop in the prices of the algae themselves, which will cost about $ 309 per ton, which is less than 25% of their price in 2019. As a result, in conjunction with capturing CO2 and obtaining subsidies for the fight against emissions in this way, companies producing biofuels from algae will be able to offer them at a price similar to, for example, corn ethanol, and sometimes even to fossil fuels.
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This artificial intelligence system, based on machine learning, actually consists of two algorithms that solve the two biggest problems related to algae breeding. One concerns blocking access to light in the lower parts of the reservoirs, and the other concerns the extraction of algae from water, which traditionally involve processes such as centrifugation, filtration or chemical flocculation.
Scientists have also found a way to harvest faster and cheaper by modifying the algae to produce a chemical called limonene, which makes the surface of cells impermeable to water. Work is currently underway to improve the technology and bring it into use on a large scale. You can read the details in an article published in Nature Communications.
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