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Phys.org — Technology · October 22, 2026 · On the brief until November 5, 2026

New materials library could help AI design better sodium-ion batteries

Materials ScienceChemistryChemical Engineering
THE AI ANGLE
Predicting battery material performance from experimental composition data

Surrey researchers tested 28 sodium manganese oxide cathode compositions substituted with iron, vanadium, and titanium. Iron increased energy capacity, vanadium improved cycling stability, and titanium aided high-rate performance. The resulting dataset provides a baseline to train future machine-learning models to evaluate cathode behavior before laboratory synthesis.

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THE TEACHING ANGLE
Small compositional shifts force trade-offs between energy capacity, cycling stability, and discharge rates during cathode optimization.

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