ArticleScientific data2025
Dataset exploring the atomic scale structure and ionic dynamics of polyanion sodium cathode materials.
Article in Scientific data, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
What it found
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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.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
2 citing papers in PubMed.
- Intelligent Computing for Future Layered Cathodes in Sodium-Ion Batteries.Small (Weinheim an der Bergstrasse, Germany) · 2026Review
- Dataset exploring the atomic scale structure and ionic dynamics of polyanion sodium cathode materials.Scientific data · 2025Article
Corrections and comments
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Authors and funding
4 authors.
Funding
Abstract
Polyanionic sodium cathode materials exhibit promising electrochemical properties and high stability, making this chemical space worth exploring to enhance the performance of sodium-ion batteries. Given the vast chemical space, fast and efficient computational methods are needed, highlighting the need for machine learning (ML)-guided approaches. To support the ML-driven discovery, we have developed a comprehensive theoretical dataset comprising 113532 DFT-calculated structures with atomic charges and 184612 structures without atomic charges for four polyanion sodium-ion cathode materials: NaTMPO
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.