Scientists Develop Sodium Ion Batteries Using Waste: Key Component Discovered

Researchers used waste tea leaves to create an affordable and sustainable anode.

Researchers at Harvard University used waste tea leaves to develop a relatively inexpensive but high-capacity sodium ion battery, The Cool Down reports.

Sodium-ion batteries could potentially lower the cost of electric vehicles and make battery production less toxic. However, such batteries had significant drawbacks – low capacity and charging speed, short service life. That’s why they lost out to lithium-ion batteries, which are the leaders in today’s battery technology. The problem with sodium ion devices is that the large size of sodium ions limits rapid movement within battery components.

New research shows the problem can be solved. The researchers converted raw tea leaf stems into “solid carbon” using high temperatures and treated them with acid to reduce strength loss. The resulting porous material provided excellent electrolyte penetration and sodium ion absorption. The anode, based on the new material, withstood more than 1,000 charge/discharge cycles, while its energy density was comparable to commercial lithium-ion batteries.

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The tea stem-based material is called TS-1400-HCl. The starting capacity is 70% higher than the “classical” anode, which consists of a composite of sulfur phosphide and carbon. Additionally, TS-1400-HCl is 91% more efficient than a traditional anode in the first charge/discharge cycle and 7-9 times more durable at 500 cycles. Scientists are confident that the new material can be easily produced on an industrial scale.

More than 1 billion kg of tea waste accumulates annually in China alone. Dr. Zhang’s team believes that their approach to using these biowastes has great potential not only for improving battery technology, but also for helping reduce the toxicity of the production process.

We have previously reported when smartphones will receive new super batteries. Smartphone manufacturers are trying to increase battery capacity, so AI applications need more power and users need more autonomy.

Source: Focus

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