Polyaniline–Copper Composite: A Non-precious Metal Cathode Catalyst for Low-Temperature Fuel Cells
Bibliographic record
Abstract
Platinum has been used extensively in low-temperature fuel cells (LTFCs), including polymer electrolyte fuel cells and microbial fuel cells (MFCs). Still, its replacement with low-cost alternatives has been a matter of considerable conjecture for some time. This study investigates the possible use of an electrochemically synthesized CP/PANi-Cu cathode as a low-cost replacement for a Pt cathode in MFCs and LTFCs. Thorough and detailed characterization and evaluation of the CP/PANi-Cu cathode was undertaken by electrochemical and advanced surface analytical methods, including scanning electron microscopy (SEM), XPS, FTIR, 4-D X-ray microscopy, and 3D profilometry. Direct comparison of the proposed cathode with a CP/Pt cathode is used to justify its adequacy as a replacement for a platinum cathode. The PANi-Cu coating had a uniform nano-fibrous structure, which enhanced its performance as a cathode. In particular, the incorporation of copper into the coating enhanced its ORR activity. By comparison, the optimum CP/PANi-Cu cathode achieved a 170% higher j 0apparent of 0.088 ± 0.003 mA cm –2 than obtained with a standard CP/Pt cathode with a Pt loading of 0.5 mg cm –2 . Even when a higher Pt loading of 1.5 mg cm –2 was used, the CP/PANi-Cu cathode performance was still slightly better. The superiority of the CP/PANi-Cu cathode was also reflected in the obtained R ct value of 1.456 Ω cm –2 compared with 3.95 and 1.485 Ω cm –2 obtained with the CP/Pt cathode, which has a Pt loading of 0.5 and 1.5 mg cm –2, respectively. The results obtained by SEM, XPS, FTIR, 4D X-ray microscopy, and 3D profilometry confirmed the unique nature, composition, and presence of copper in the CP/PANi-Cu composite. The results of this study clearly demonstrate that the proposed CP/PANi-Cu cathode can be adopted as a suitable low-cost replacement for a Pt cathode in LTFCs.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".