Could a microscopic organism replace our batteries, plastics, and fuels?

Nature · Published 22 October 2026 Swipe more like this →

In short: Algae are often viewed as a coastal nuisance, but scientists are reimagining them as a versatile raw material. From cleaning microplastics in our drinking water to powering remote electronics, these ancient organisms may hold the key to a future less dependent on oil.

While algae are frequently seen as a problem when they contaminate coastal waters, researchers are exploring their potential as a biological factory for fuel, food, and medicine. Beyond simple biomass, engineered strains are being developed to tackle specific environmental crises. At the University of Missouri, researcher Susie Dai has developed a modified algae strain that produces limonene—the orange-scented oil found in citrus. This oil makes the algae's surface water-repellent, allowing it to act like a magnet for microplastics in water, forming dense clumps that sink for easy removal. This process can simultaneously clean wastewater by absorbing excess nutrients.

The potential applications extend to energy production through 'biocells.' Researchers at Cambridge University are developing these cells as a sustainable alternative to conventional lithium-based batteries, which involve energy-intensive mining and habitat destruction. Although the power output of these biocells is currently too low for high-drain electronics, they are ideal for low-power devices like smoke alarms or remote controls. This could provide life-changing, reliable power for environmental sensors or mobile phone charging in remote, off-grid regions like sub-Saharan Africa.

Scaling this technology to an industrial level remains a significant hurdle. Growing microalgae species like Chlorella vulgaris in photobioreactors requires precise control over light, temperature, pH, and oxygen. Too much light can cause photoinhibition, while high cell density can lead to self-shading. To manage these complex, interacting variables, scientists are now turning to artificial intelligence. Machine-learning models can analyze sensor data and images to predict growth patterns and identify biological stress before it becomes visible to the human eye.

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