Pressurized organic electrodes enable practical and extreme batteries
Bibliographic record
Abstract
While organic batteries hold promise for sustainable energy storage, a considerable gap persists between research and application concerning testing conditions and cell cost. Here, we report pressurized organic electrodes tailored for practical applications. Outperforming prior organic electrodes, pressurized organic electrodes excel under challenging/extreme condition including high mass loadings (50–150 mg cm−2), active material fraction (up to 95%), low N/P ratio (0.8–2), and lean electrolyte, delivering high areal/volumetric capacity in full cells. Moreover, pressurized organic electrodes exhibit broad applicability, thriving in diverse battery systems (Li+/NH4+/H+/Na+/Zn2+/Mg2+ ion batteries) and organic materials (molecule, polymer, salt), consistently demonstrating enhanced performance compared with unpressurized ones. The improved capacity, rate, and cycling performance of pressurized electrodes result from pressure-induced structural and property changes in organics including crystal orientation, enhanced π-π interaction, favorable electrode porosity/tortuosity, accelerated chemical reactivity, and boosted electronic conductivity. Along with simple, efficient, green, and cost-effective manufacturing features, pressurized organic electrodes offer a promising route towards organic battery application. Organic batteries are promising for sustainable energy storage but face challenges in performance and cost. Here, authors develop pressurized organic electrodes with high capacity and durability under practical and extreme conditions, advancing organic batteries toward real-world applications.
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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 | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".