Theoretical investigation of the use of doped graphene as a membrane support for effective CO removal in hydrogen fuel cells
Why this work is in the frame
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Bibliographic record
Abstract
Carbon monoxide poisoning of the anode catalyst is currently a big problem facing the use of hydrogen fuel cells. This study uses density functional theory to model the interaction between a filter membrane and carbon monoxide to optimise the removal of CO from the H2 feed gas. The membranes studied are graphene/metal surfaces of nickel, platinum and iridium/gold over undoped or boron-, nitrogen- or oxygen-doped graphene. It was found that graphene doping improved the efficiency of the filter membrane in hydrogen fuel cells because addition of a dopant increases metal/graphene binding and causes metal/H2 binding to become negligible while only decreasing metal/CO binding slightly. Platinum and iridium/gold systems show slightly stronger binding to graphene and CO than nickel systems. However, nickel is a non-precious metal, so membranes produced with this active centre could lead to a reduction in the cost of fuel cell production by increasing the lifetime of the platinum anode catalyst.
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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 | 0.001 | 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 it