Structure and Dynamics in Functionalized Graphene Oxides through Solid-State NMR
Bibliographic record
Abstract
Graphene oxide (GO), a derivative of the supermaterial graphene, has intrinsic proton conductivity, which is similar to Nafion, the most popular proton exchange membrane material currently used in fuel cells. Research into acid-functionalized GOs and determining the role of acidic groups in increasing proton conductivity will help to improve polymer electrolyte membrane performance in fuel cell systems. Multinuclear solid-state NMR (ssNMR) spectroscopy was used to analyze the structure and dynamics of GO and a number of sulfonic acid derivatives of GO, both novel and previously reported. 13 C CP-MAS spectra showed the disappearance of surface-based oxygen groups upon GO functionalization and can be used to identify linker group carbon sites in previously synthesized and novel functionalized GO samples with high specificity. Dehydration of these samples allows the collection of 1 H spectra with resolved acidic proton and water peaks. The effect of dehydration on the proton spectrum is partially reversible through rehydration. Deuteration of the acidic groups in high temperature and acidic conditions was virtually unsuccessful, indicating that only the surface and not the intercalated functional groups play a role in the enhanced proton conductivity of ionomer/functionalized GO composites. Increased surface area and increased delamination of functionalized GO are suggested to be important to improved proton exchange membrane fuel cell performance. This synthesis and method of analysis prove the utility of ssNMR in the study of structure and dynamics in industrially relevant amorphous carbon materials despite the obvious difficulties caused by naturally broad signals and low sensitivity.
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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) | 0.001 | 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".