Designing catalyst layer morphology for high-performance water electrolysis using synchrotron X-ray nanotomography
Bibliographic record
Abstract
The limited availability of iridium in the Earth’s crust poses severe challenges to establishing gigawatt-scale electrolyzers that are needed for energy storage; this problem urgently calls for reduced iridium loadings. Reducing iridium loadings requires catalyst structure optimization, but to date, little attention has been paid to the characterization of electron, proton, and mass transport in the catalyst layer, particularly at the nanoscale. We present the 3D nanoscale pore structure of iridium-based catalyst layers via synchrotron full-field transmission X-ray microscopy (TXM) and perform pore network modeling to determine effective transport properties in water electrolyzers. We observe a wide range of pore sizes in the catalyst layer, constituting pathways that facilitate mass transport. Increasing the thickness of the ionomer layer that covers the catalyst particles significantly increases protonic conductivity at the cost of reducing the open pore space and electrical conductivity, both of which are detrimental to electrolyzer performance.
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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".