Precipitated Iodine Cathode Enabled by Trifluoromethanesulfonate Oxidation for Cathode/Electrolyte Mutualistic Aqueous Zn–I Batteries
Bibliographic record
Abstract
Abstract Aqueous Zn–I batteries hold great potential for high‐safety and sustainable energy storage. However, the iodide shuttling effect and the hydrogen evolution reaction that occur in the aqueous electrolyte remain the main obstacles for their further development. Herein, the design of a cathode/electrolyte mutualistic aqueous (CEMA) Zn–I battery based on the inherent oxidation ability of aqueous trifluoromethanesulfonate ((OTf)−) electrolyte toward triiodide species is presented. This results in the formation of iodine sediment particles assembled by fine iodine nanocrystals (≈10 nm). An iodine host cathode with high areal iodine loading is realized via a spontaneous absorption process that enriched redox‐active iodine and iodide species from aqueous electrolyte onto nanoporous carbon based current collector. By tuning iodide redox process and suppressing competitive hydrogen evolution reaction, the assembled CEMA Zn–I batteries demonstrate a remarkable capacity retention of 76.9% over 1000 cycles at 0.5 mA cm−2. Moreover, they exhibit a notable rate capability, with a capacity retention of 74.6% when the current density is increased from 0.5 to 5.0 mA cm−2. This study demonstrates the feasibility of using the oxidation effect to repel redox‐active species from the electrolyte to the cathode, paving a new avenue for high‐performance aqueous Zn–I batteries.
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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) | 0.000 | 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".