Modeling and Optimization of Porous Electrodes for Alkaline Oxygen Evolution
Bibliographic record
Abstract
The oxygen evolution reaction (OER) plays an important role in many industrial applications like electrolytic water splitting or regenerative fuel cell systems. So far, IrO2 and RuO2 are the benchmark OER catalysts, owing to their high catalytic activity. However, these precious metals are costly and their supply is not sustainable, which makes them unsuitable for large-scale applications. Hence, research efforts have been devoted to the development of low-cost OER catalysts on the basis of first-row transition metals and their oxides. Especially nickel- and cobalt based composites show promising OER catalytic activity. Strategies to further enhance OER activity of the transition metal-based catalysts to levels comparable to the benchmark IrO2 and RuO2 catalysts pursue the design and fabrication of nanoporous catalyst structures and the use of catalyst nanoparticles immobilized on carbon nanomaterial substrates. Porous electrode structures offer high specific surface area available for reaction. However, this increase in surface area comes at the cost of additional transport losses of reactants and products through the porous medium. In this context, gas evolution 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. Limited ion transport leads to transport losses and defines a reaction penetration depth, beyond which the porous electrode becomes inactive. On the other hand, the gas covers part of the internal surface area, rendering it inactive. In order to maximize the activity of a porous gas evolution electrode, its structure needs to be optimized. To do so, the current work attempts to gain a fundamental understanding of the relationships between structure, properties and performance of the porous electrode. Our 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 gas phase is modeled by a micro-scale model describing the formation, growth and transport of gas bubbles in the porous medium. The model is applied in practice to a regenerative zinc fuel cell system for energy storage. In this system, energy is released in an alkaline zinc air fuel cell by oxidizing zinc suspended in alkaline solution. The system can be recharged by regenerating the zinc on the cathode of the regenerator unit, as shown in Fig. 1. On the anode of this regenerator unit, the OER takes place, which imposes one of the major losses in the system. The presented work uses this system as a concrete example for the development of a general theory for gas evolving porous electrodes and aims at verifying this theory by targeted experiments on this practical system. The model can then be used to optimize the structure of the electrode in order to optimize the performance of the regenerator. Figure 1
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| 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 | 0.002 | 0.000 |
| 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".