Quaternized Graphene Oxide Nanocomposites as Fast Hydroxide Conductors
Bibliographic record
Abstract
Nanocomposites play a key role in performance improvements of hydroxide conductors employed in a wide range of alkaline-electrochemical systems such as fuel cells and metal-air batteries. Graphene oxide (GO) nanosheets are considered to be outstanding nanofillers for polymeric nanocomposites on account of their excellent physicochemical strength and electrochemical properties. In this work, a fast hydroxide conductor was developed on the basis of a chemically modified GO nanocomposite membrane. The high surface area of GO was functionalized with highly stable hydroxide-conductive groups using a dimethyloctadecyl [3-(trimethoxysilyl)propyl]ammonium chloride (DMAOP) precursor, named QAFGO, and then composed with porous polybenzimidazole PBI (pPBI) as a well-suited polymeric backbone. The nanocomposite exhibited outstanding hydroxide conductivity of 0.085 S cm(-1), high physicochemical strength, and electrochemical stability for 21 days. An alkaline fuel cell (AFC) setup was fabricated to determine the functionality of QAFGO/pPBI nanocomposite in an alkaline-based system. The high AFC performance with peak power density of 86.68 mW cm(-2) demonstrated that QAFGO/pPBI nanocomposite membrane has promising potential to be employed as a reliable hydroxide conductor for electrochemical systems working in alkaline conditions.
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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 | 0.001 |
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 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".