Exploring the engineered electroplating process for coating of gold on the inner structure of porous transport layer (PTL): Performance evaluation of coating in simulated PEM electrolyzer
Bibliographic record
Abstract
During prolonged operation of PEM water electrolyzer (PEMWE) in an acidic environment, the formation of TiO 2 on the surface of the Ti-PTL causes passivation, resulting in an increase in the cell voltage. Herein, the Ti-PTL treatment involved three steps: electrochemical etching to remove surface oxides, electrostriking to form an Au underlayer and electroplating to apply a protective top layer of Au. The Au was uniformly distributed on the top of the surface and inner structure of Ti-PTL under the optimized rotation speed of 50 rpm, denoted by Au/Ti felt [R = 50]. The Ti-PTL treatment under optimized rotation presented a more effective anticorrosive coating in simulated conditions of a PEMWE compared to treatments without rotation and those with high rotation of 200 rpm. In PEMWE cell, the Au/Ti felt [R = 50] PTL demonstrated a voltage reduction of 124 mV compared to Au/Ti felt [R = 0] at 2.0 A/cm 2 . The corrosion study and durability measurements were conducted using a homemade simulated flow corrosion cell. 3D printing was employed to fabricate non-metallic bipolar plates (BPs) that included a simulated flow field structure at the PTL/BP interface. This approach paves the way to independently observe the impact on cell voltage caused by the degradation of the PTL. • Development of engineered electroplating method to coat inner structure of the PTL. • Optimized rotation of substrate during electroplating offered uniform gold coating. • 3D printed non-metallic BPs were assembled to create simulated BPs/PTL interface. • Conducted the comprehensive ex-situ and in-situ characterizations. • Optimized rotating Au coated PTL offered PEMWE performance of 1.742 V at 2.0 A/cm 2 .
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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) | 0.000 | 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 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".