Nickel‐based anodes in anion exchange membrane water electrolysis: a review
Bibliographic record
Abstract
Abstract BACKGROUND Anion exchange membrane water electrolysis (AEMWE) is a promising technology for efficiently producing low‐cost hydrogen (H 2 ). Of the two half‐cell reactions in AEMWE, the oxygen evolution reaction (OER) is kinetically sluggish, requiring an electrocatalyst to promote the reaction. Nickel (Ni) is a promising non‐noble metal catalyst for OER due to its low cost, high stability, and activity in alkaline media. In an AEMWE, Ni particles form a catalytic layer bound together using an anion exchange ionomer (AEI), which also serves to provide hydroxide ion transport throughout the layer. RESULTS In this review, reports of lab synthesized Ni particle‐based anode catalytic layers with AEIs, used specifically in AEMWE devices, are summarized from 2015 onwards to highlight the recent research and development of active Ni‐based AEMWE anodes. The synthesis and electrode fabrication method for the anodes is analyzed to offer a perspective on the feasibility of industrial scale AEMWE. As ionomeric binders are an important component of AEMWE anodes, the ionomer type and loading used with the Ni‐based particles is also summarized with a focus on how those parameters affect catalytic performance. CONCLUSION The literature analysis performed in this work demonstrates the potential of the AEMWE process and provides recommendations for future work on furthering the current understanding of the interactions between the various components of the system. Additionally, it is recommended that future research efforts be focused on further understanding how developed materials perform in a working AEMWE device. © 2022 Society of Chemical Industry (SCI).
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".