Highly Accelerated Mass Transport within Jungle-Gym-Type Ir Electrocatalyst for Water Electrolyzers
Bibliographic record
Abstract
Hydrogen is an efficient and clean energy carrier, as well as a fuel for transportation and various other applications. Polymer electrolyte membrane water electrolysis (PEMWE) has shown to be a promising method for producing pure hydrogen without significant additional compression.[1] However, understanding the relationship between nanostructure and activity is one of the current challenges faced by water electrolysis for analyzing and improving IrOx-based catalysts for the OER. Herein, in order to confirm the effect of controlling the nanostructure, jungle-gym-structured Ir OER catalysts were fabricated using solvent-assisted nanotransfer printing (S-nTP). They are composed of vertically stacked nanowire array with a periodicity. They showed 4 higher mass activity than that of iridium black powder(2-4 nm in diameter). To measure the electrochemically active surface area, the integrated surface charge was calculated from the cyclic voltammetry in the range of 1.0 – 1.4 V vs RHE. The jungle-gym-type Ir catalyst recorded 2.3 times higher integrated surface charge compared to that of iridium black powder. If the mass activity is normalized by the integrated surface charge, turnover frequency (TOF) can be calculated, which is associated with the specific current density per electrochemically active surface area. [2] TOF values 1.8 times higher than iridium black were observed in the case of jungle-gym-structured one. The efficiency of the catalyst utilization has been maximized due to the novel structure, achieving a high ratio of surface area to the mass of the structure as high as that of Ir Black catalysts. Moreover, the jungle-gym nanostructure within the catalyst layer enhanced the intrinsic activity of the catalyst due to the accelerated mass transport within the catalyst layer. Reference [1] Aricò, A. S., et al. "Polymer electrolyte membrane water electrolysis: status of technologies and potential applications in combination with renewable power sources." Journal of Applied Electrochemistry2 (2013): 107-118. [2] Abbott, Daniel F., et al. "Iridium oxide for the oxygen evolution reaction: correlation between particle size, morphology, and the surface hydroxo layer from operando XAS." Chemistry of Materials18 (2016): 6591-6604.
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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 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".