Mn<sup>2+</sup> Ions Confined by Electrode Microskin for Aqueous Battery beyond Intercalation Capacity
Bibliographic record
Abstract
Abstract In aqueous rechargeable zinc–manganese dioxide batteries (ZMBs), some irreversible side reactions, such as Mn 2+ dissolution, often lead to capacity fading over cycling. These side reactions play a crucial role in the capacity and cycle performance of the battery. The implementation of a bionic electrode microskin (EMS) composed of collagen hydrolysate to convert the irreversible side reactions into reversible reactions is reported. The proposed EMS effectively adsorbs and confines the Mn 2+ ions around the cathode through van der Waals forces, hydrogen bonds, and/or ionic interactions, which makes the MnO 2 /Mn 2+ reactions reversible during the charge/discharge process. Such Mn 2+ dissolution reactions, with an ultrahigh theoretical capacity (617 mAh g ‐1 ), contribute a large amount of capacity, ≈44% of the total specific capacity at a low scan rate. Based on these fundamental findings, the assembled ZMBs with an EMS display an unprecedented discharge capacity of 415 mAh g ‐1 at 20 mA g ‐1 , which overcomes the theoretical capacity (308 mAh g ‐1 ) limitation of the Zn 2+ intercalation mechanism. More significantly, the EMS on all α‐, β‐, and γ‐MnO 2 cathodes exhibits similar high capacity beyond the theoretical capacity of Zn intercalation and capacity retention enhancement after 3000 cycles.
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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) | 0.001 | 0.000 |
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".