Enhancement of Electricity Generation by a Microbial Fuel Cell Using a Highly Active Non-Precious-Metal Nitrogen-Doped Carbon Composite Catalyst Cathode
Bibliographic record
Abstract
As microbial fuel cell (MFC) technology continues to gain momentum toward commercialization, the replacement of traditionally used platinum for oxygen reduction with an inexpensive catalyst becomes more important. A nonprecious nitrogen-doped carbon composite catalyst with previous applications in PEM fuel cells is demonstrated for the first time in a single-chamber air cathode MFC with comparisons to a similar platinum-based MFC. The performance of the MFC is compared with a similar MFC using a platinum catalyst and acetate feed. When the platinum is replaced with the catalyst loaded at the surface of the proton exchange membrane (loading density of 1 mg/cm 2 ), MFC operation outperforms a similar platinum-based cell. The synthesized catalyst produced 213.2 ± 13.9 mW/m 2 power density that on average is 151% higher than that for the platinum catalyst. Columbic efficiency was also higher as a result at 6.71 ± 0.88%. A 2-fold increase in the loading density (2 mg/cm 2 ) for the synthesized catalyst resulted in a 305% increase in the generated power compared to the platinum catalyst. This suggests that the nonprecious nitrogen-doped carbon composite is a potentially attractive replacement for conventional platinum as a catalyst for energy production by MFCs.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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".