An experimental approach to reduce precious metal loading on porous transport layer by using magnetron sputtering method for PEMWE application
Bibliographic record
Abstract
• Multi-layered NbPt coating was sputtered on the Ti-based porous transport layer. • Electrochemical behavior of co-deposited and multi-layered NbPt coatings were compared. • Multi-layered NbPt coating enhanced Galvanic protection and electrochemical stability. • Multi-layered NbPt coating exhibited higher durability over commercial sample. The extravagant cost of Pt-coated porous transport layers (PTLs) had augmented the already high price of stack components in Proton exchange membrane water electrolyzers (PEMWE). To curtail this high cost, there is a pressing need to replace the expensive Pt coatings with cost-effective materials on Ti PTLs. Hence an attempt is being made to reduce the Pt loading by sputtering co-deposited and multi-layered NbPt coatings on Ti PTLs. The findings showed that the multi-layered NbPt coating exhibited superior corrosion resistance, enhanced durability, and higher conductivity than its co-deposited counterpart under ex-situ environment of PEMWE. The multi-layered NbPt coating was subsequently compared with commercial Pt-coated PTL under both ex-situ and in-situ operating conditions. It was revealed that the multi-layered NbPt coated PTL showcased longer durability and similar ICR compared to the commercial PTL under ex-situ conditions. During the in-situ testing, multi-layered NbPt coating with thin layer of Pt (50 nm), performed (2.050 V @2.0 A/cm 2 ) equivalently to the commercial Pt (200 nm) coating (2.044 V @2.0 A/cm 2 ), making it a viable PTL coating alternative.
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 | 0.001 | 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".