Recent Advances in Emerging Non‐Lithium Metal–Sulfur Batteries: A Review
Bibliographic record
Abstract
Abstract Rechargeable non‐lithium metal–sulfur batteries (MSBs) have gained tremendous attention because of their merits, including a high theoretical capacity, remarkable energy density, and low cost. However, the detrimental issues encountered by non‐lithium MSBs, such as polysulfide shuttle effects, volume expansion and the low electrical conductivity of elemental sulfur, and the serious side reactions between metal anodes and electrolytes, severely restrict their practical applications. To circumvent these issues, numerous effective strategies have been explored and utilized. In this review, the intractable obstacles that prevent the application of non‐lithium MSBs are first summarized. Recent pioneering studies on rechargeable non‐lithium MSBs are reported and discussed in terms of material design, fabrication methods, and electrochemical performance. The emerging characterization techniques used to reveal the working mechanisms of non‐lithium MSBs and the advantages of elaborately designed structures are highlighted. Finally, the remaining issues and possible future areas of research for practical applications are discussed.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.002 |
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".