ArticleSmall methods2026
Peukert-Informed Prediction and Screening of Manganese-Based High-Rate Potassium Cathode.
Article in Small methods, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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4 authors.
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Abstract
Manganese-based layered oxides have emerged as promising cathode materials for potassium-ion batteries owing to their low cost, environmental benignity, structural diversity, and high theoretical capacity, yet suffer from poor rate performance. Compositional regulation offers an effective strategy to address this limitation, but traditional trial-and-error approaches are inefficient and often yield suboptimal results. Herein, interpretable machine learning combining Random Forest, high-throughput virtual screening, and Pareto-front optimization of capacities at 50 and 500 mA g
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