Transient Potential Induced Dissolution of Metal Biporlar Plates Used in Proton Exchange Membrane Fuel Cell
Bibliographic record
Abstract
Corrosion of metallic bipolar plates (BPPs) under the aggressive working conditions is the major issue that impedes its application in proton exchange membrane fuel cells (PEMFCs). Transient potential is generated during the different operating conditions of PEMFCs such as start-up/shut-down(SU/SD), and dynamic loading stages. Transient potential-induced corrosion is a serious problem encountered by BPPs. To investigate the influence of transient potentials on corrosion of BPPs, potential pulses with different amplitudes are applied to specimens. Also, a novel zirconium oxynitride coating is prepared via atomic layer deposition to improve the stability of BPPs. Results show that transient potentials generated at passive and transpassive potential regions are both detrimental to the stability of BPPs. For the uncoated samples, a larger potential fluctuation in the passive region could induce a much higher frequency of passive film breakdown than that generated by a smaller potential fluctuation during the cyclic pulse tests. In the transpassive region, upon increasing transient potentials, the passive film formed on surface enters the potential dependent dissolution region, leading to severe intergranular corrosion after a certain cycles of pulse tests. The zirconium oxynitride coated samples present improved performance in both normal potentiostatic polarization and transient potential conditions. The enhanced corrosion resistance of coated samples is attributed to the continuous formation of protective oxide layer which has a wider band gap than passive films formed on uncoated samples. Therefore, the coated sample enters the transpassive potential region at a more positive potential and thus exhibits much lower dissolution rate. Moreover, the Mott-Schottky plots suggests that the defect density of the coated samples is much lower than the uncoated counterpart, and the deterioration of uncoated sample performance under different transient potentials is related to the passive film disorder degree. From our study, transient potentials would accelerate the degradation of BPPs, and the development of bipolar plates coated with dense protective surface films could help mitigate the dissolution induced by the transient potentials, thus improving stability and durability of BPPs. Specially, a layer of coating with a wider band gap between Fermi level and valance band is beneficial to reduce the dissolution in the transpassive potential region.
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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 | 0.000 | 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 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".