Cation Additive Enabled Rechargeable LiOH‐Based Lithium–Oxygen Batteries
Bibliographic record
Abstract
Abstract Lithium–oxygen (Li–O2) batteries have attracted extensive research interest due to their high energy density. Other than Li2O2 (a typical discharge product in Li–O2 batteries), LiOH has proved to be electrochemically active as an alternative product. Here we report a simple strategy to achieve a reversible LiOH‐based Li–O2 battery by using a cation additive, sodium ions, to the lithium electrolyte. Without redox mediators in the cell, LiOH is detected as the sole discharge product and it charges at a low charge potential of 3.4 V. A solution‐based reaction route is proposed, showing that the competing solvation environment of the catalyst and Li+ leads to LiOH precipitation at the cathode. It is critical to tune the cell chemistry of Li–O2 batteries by designing a simple system to promote LiOH formation/decomposition.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".