Bibliographic record
Abstract
Porous electrodes for PEM electrolyser and fuel cell technologies are optimized primarily to provide a high specific surface area for the desired electrochemical reactions. However, the increase in surface area comes at the cost of increased voltage losses due to the transport of reactant and product species through the porous medium. In gas evolving electrolyzer electrodes, the formation and transport of gas bubbles plays an important role: on the one hand, gas in the pores replaces the electrolyte phase, thus hindering ion transport and reducing the effective ionic conductivity in the porous electrode; on the other hand, gas bubbles cover and deactivate a portion of the internal surface area. The impacts of gas formation and removal must be accounted for in the design of electrolyzer electrodes. The focus of the presented work is on the fundamental understanding of the relationships between structure, properties and performance of porous gas-evolving electrodes. The approach combines a macro-scale performance model of the electrode with a micro-scale model of gas evolution. At the macro-scale, a classic porous electrode model describes the transport of ions, electrons and produced oxygen using effective medium theory and accounting for the gas phase volume and distribution. The micro-scale model describes the formation and growth of gas bubbles based on chemical energy considerations. It can explain the experimentally found high oversaturation that is necessary to nucleate bubbles [1]. Additionally, the size of the bubble nucleus in the experiment was estimated. The model was used to study the influence of structural parameters on the operation of porous electrodes and to establish guidelines for an enhanced electrode design. It was found that the transport regime of the dissolved gas, viz. diffusion control vs. transfer control at the liquid-gas interface, determines the bubble growth law. Applications of the model to gas evolving porous electrodes in electrolyzers with liquid electrolyte as well as polymer electrolyte electrolyzers (PEEC) will be discussed. [1] Chen, Q., Luo, L. and White, H. S. Electrochemical generation of a hydrogen bubble at a recessed platinum nanopore electrode. Langmuir 31, 4573–4581 (2015). Figure 1: Bubble growth on an artificial nucleation site at 20 mA/cm2. Comparison of model results with experimental data from C. Brussieux et al., Electrochimica Acta 56 (2011) 7194-7201. Deviation at large bubble radii due to deformation of the bubbles before detachment, which is neglected in the model. Figure 1
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 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 | 0.001 |
| 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 | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 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".