Machine Learning Predicts Sodium-ion Battery Composition

This is a news story, published by ScienceDaily, that relates primarily to the Journal of Materials Chemistry news.

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ScienceDaily

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Leveraging machine learning to find promising compositions for sodium-ion batteries

Summary

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81% Informative

Researchers optimize the composition of a multi-element transition metal oxide to achieve exceptional energy density in sodium-ion batteries.

Their approach could help reduce time and resources needed during exploratory research, speeding up the transition to renewable energy.

The findings of their study were received on September 05, 2024 , with uncorrected proofs and published online in the Journal of Materials Chemistry A on November 06, 2024 .

The number of experiments can be reduced by using machine learning, which brings us one step closer to speeding up and lowering the cost of materials development.

As the performance of electrode materials for Na-ion batteries continues to improve, it is expected that high-capacity and long-life batteries will become available at lower cost in the future.

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