Interfacial Mechanisms Driving Enhanced MnO₂ Deposition/Dissolution in Electrode-Free Batteries
Bibliographic record
Abstract
Aqueous zinc-manganese batteries operating via MnO 2 electrodeposition/dissolution mechanisms offer promising energy storage capabilities for grid-scale applications. However, they are traditionally realized by acids in electrolytes that compromise zinc anode stability. In this presentation, we discuss the interfacial phenomena enabling high-performance Zn 2+ /Zn||MnO 2 /Mn 2+ batteries through eutectic aqueous-organic electrolytes without external acid addition. The presentation will focus on how these eutectic electrolytes alter the local environment at electrode interfaces, creating localized pH gradients that influence critical electrochemical processes including proton transport and gas evolution suppression. We also demonstrate connections between electrolyte composition and the morphology and phases of deposited MnO 2 . Collectively, these interfacial phenomena significantly improve the battery discharge performance. By understanding and controlling these interfacial factors, our optimized electrolyte system simultaneously enhances MnO 2 /Mn 2+ reversibility at the cathode while promoting stable zinc cycling at the anode. Our battery achieves high coulombic efficiency for extended cycling without external acid addition, advancing zinc-manganese battery development through rational electrolyte design.
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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 | 0.001 |
| 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".