Increasing ionic conductivity in polymer electrodes using oxanorbornene
Bibliographic record
Abstract
Abstract Pendant polymer‐based organic electrodes consisting of redox‐active quinones are promising for the next generation of rechargeable batteries owing to their fast redox kinetics and the structural diversity of their design. Many commercially available norbornene monomers have been popular choices for preparing pendant polymer electrodes, since these monomers enable numerous synthetic routes for attaching redox‐active pendant groups. However, these electrodes often suffer from sluggish lithium‐ion mobility at both the electrode–electrolyte interface and within the bulk of the electrode because of their poor ionic conductivity. This can lead to low cycling stability and rate capability. In this study, we design and compare the performance of redox‐active poly(norbornene) and poly(oxanorbornene) pendant polymer electrodes. The additional oxygen in the repeat unit of poly(oxanorbornene) facilitates conduction of Li‐ions, resulting in improved performance relative to their poly(norbornene) counterparts. Specifically, higher reversible capacities are achieved at high current densities and initial capacity is better retained during prolonged cycling tests. Unlike previous strategies to increase the ionic conductivity of polymer electrodes, our design involves minimal synthetic steps and only contributes to a small increase in additional redox‐inactive mass, offering a versatile platform for high‐performance organic electrode materials. image
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 teacher head, 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".