Advancing high-safety and low-cost all-solid-state batteries with polyanion cathodes: Challenges and recent progress
Bibliographic record
Abstract
While conventional liquid-based lithium-ion batteries (LIBs) have powered electric vehicles (EVs) successfully in the transportation market, the transition to all-solid-state lithium-ion batteries (ASSLIBs) promise transformative benefits, including enhanced safety and significantly higher energy densities. Advancing the adoption of ASSLIBs requires prioritizing low-cost, widely available materials while reducing reliance on critical mined resources. Developing low-cobalt and cobalt-free cathodes, such as polyanion materials, offers a promising and sustainable pathway for the future of EV batteries. This review aims to explore recent advancements in polyanion cathodes for ASSLIBs, highlighting the challenges they face, and the innovative strategies developed to address them. This paper begins by analyzing the crystal structures and properties of polyanion cathodes, establishing their influence on the performance of ASSLIBs. It then focuses on the challenges and corresponding strategies for integrating LiFePO 4 (LFP) cathodes with various solid-state electrolytes (SSEs), including polymer, oxide, composite polymer/oxide, sulfide, and halide-based systems. Additionally, the application of other polyanion cathodes in ASSLIBs is thoroughly examined, providing a comprehensive overview of their potential and advancements. Through this paper, we aim to emphasize the critical importance of developing safe, cost-effective cathodes to accelerate the application of ASSLIBs in next-generation EVs and beyond. • Importance of developing safe and cost-effective cathodes for all-solid-state batteries. • Structures and properties of polyanion cathodes on the performance of all-solid-state batteries. • Challenges and mitigation strategies of polyanion cathodes paired with various solid-state electrolytes.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".