Electrochemical Impedance Study and Performance of PdNi Nanoparticles as Cathode Catalyst in a Polymer Electrolyte Membrane Fuel Cell
Bibliographic record
Abstract
The carbon-dispersed bimetallic PdNi was prepared by borohydride reduction method using PdCl2 and NiCl2 as precursors in a THF solution. The PdNi loading (mg cm-2) and PdNi weight percentage /carbon Vulcan (PdNi wt%) were optimized, by using the Simplex method. At optimum condition of PdNi loading and PdNi wt% the Electrode Membrane Assembly Performance was evaluated, using the PdNi electrocatalyst as cathode and Pt-Etek carbon cloth (0.5 mg cm-2) as anode. The maximum power density (122 mWcm-2) was attained with 45% of PdNi wt%, at 30 psi and 80 °C. On the other hand, the electrochemical impedance spectroscopy (EIS) was used to investigate the catalytic activity and the mechanism of the Oxygen Reduction Reaction (ORR) on PdNi, in 0.5M H2SO4. The Nyquist and Bode spectra of PdNi electrocatalyst present one or two time constants depending on the electrode potential, E applied. The time constants were associated to the O2 to H2O multi-electron charge transfer reaction (n=4e-) and reduction of H2O2 to produce H2O (n=2e-). The Tafel slope (- b=0.066 Vdec-1) and the charge transfer coefficient (α=0.89) were obtained from the impedance spectra, at optimum condition of PdNi loading and PdNi wt%.
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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) | 0.000 | 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 | 0.001 | 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 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".