Investigating the Effects of Modified Interlayer Spacing within Mixed Metal Oxide Cathode Materials for Next-Generation Aqueous Rechargeable Zinc-Ion Batteries
Bibliographic record
Abstract
Aqueous rechargeable zinc-ion batteries (ZIBs) are a promising addition to the current energy storage landscape, particularly supporting the decarbonization of the power sector as a low-cost, high safety alternative to lithium-ion batteries. Unfortunately, the relative infancy of ZIBs means that there are a limited number of reported cathode materials, and a divisive understanding of the operating principles for those which have been reported including Mn- and V-oxides. The large solvation shell of the working cation (Zn2+) imparts several design requirements for cathode material development, specifically the need for sufficient void space for Zn2+ intercalation, further limiting the materials which have been reported. Looking to other well-established battery chemistries, we considered the use of layered mixed metal oxides (MMOs) with Mn due to its known electrochemical activity within the operating voltage of aqueous ZIBs. We developed several MMO cathodes with tuned interlayer distance to achieve the larger void spacing capable of accommodating Zn2+. We investigated the impact of composition on the structural and electrochemical properties of 15+ different MMO materials. We determined that interlayer spacing plays critical role in electrochemical performance and that there is an optimal composition to provide enhanced specific capacity to the battery. Considering the narrow range of reported ZIBs cathodes, in this study we proposed several new materials that expand the scope of viable cathodes for next generation ZIBs and provides direction for future researchers to accelerate new material development for this technology.
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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".