Investigation of Electrocatalyst and Ionomer Interaction in Anion Exchange Membrane Water Electrolysis
Bibliographic record
Abstract
Anion exchange membrane water electrolysis (AEMWE) is a type of electrolysis that involves the use of an anion exchange membrane (AEM) to separate the anode and cathode compartments. During the electrolysis process, water is split into hydrogen gas (H2) at the cathode and oxygen gas (O2) at the anode. AEMWE is an emerging technology that has the potential to play a significant role in the production of green hydrogen, which is a promising energy carrier for a variety of applications, including fuel cells and transportation. One of the benefits of AEMWE is that it can be used with a variety of water sources, including seawater and wastewater. Additionally, AEMWE has the potential to be more energy-efficient and cost-effective than other types of water electrolysis because it can operate at lower voltages and use cheap Ni-based materials [1]. Recently, there has been a significant amount of interest in the development of anion exchange ionomers (AEI) that conduct hydroxide ions [2]. We recently investigated the PPO-LC-TMA ionomer (poly(2,6-dimethyl-1,4-phenylene oxide) [3] backbone with amine-functionalized by trimethyl amine) [4] as an ionomer for Ni-based catalysts in AEMWE. Commercial Aemion, Fumion, and Nafion AEI were compared to the lab-synthesized ammonium-enriched anion exchange ionomer PPO-LC-TMA as an anode catalyst layer for oxygen evolution reaction (OER). Cyclic voltammetry results showed that the NiFe catalyst layer with PPO-LC-TMA AEI showed higher Ni(OH)2/NiOOH peak current density, while current density obtained over Ni90Fe10 catalysts was 11%, 17%, and 39% for Nafion, Fumion, and Aemion AEI, respectively [5]. This resulted in increased OER activity of Ni90Fe10 with PPO-LC-TMA AEI and a lower overpotential of 151 mV at 10 mA cm-2 in 1 M KOH. Ex-situ Raman spectroscopy of as prepared and spent catalytic layer confirmed that the electrode transitioned to the Ni-OOH phase after polarization. NiFe anode catalytic layers were tested in a 5 cm2 single-cell alkaline membrane water electrolysis (AEMWE) with varying amounts of PPO-LC-TMA (7, 15, and 25 wt %). AEMWE results revealed that 25 wt% PPO-LC-TMA is the best ionomer loading, achieving a cell voltage of 1.941 V at 600 mA cm-2 in 1 M KOH at 50°C. Both three-electrode electrochemical cell and alkaline membrane water electrolysis (AEMWE) tests revealed that the PPO-LC-TMA ionomer stabilized NiFe catalyst and improved its performance compared to Fumion and Nafion ionomers. These results will be presented and discussed, along with details of electrochemical and physical characterizations. References E. Cossar, F. Murphy, E.A. Baranova, J Chem Technol Biotechnol, 97 (2022) 1611–1624. Wright, A. G.; Fan, J.; Britton, B.; Weissbach, T.; Lee, H.-F.; Kitching, E. A.; Peckham, T. J.; Holdcroft, S. Energy Environ. Sci. 9 (2016) 2130−2142. A.R. Nallayagari, E. Sgreccia, L. Pasquini, M Sette, P. Knauth and M. L. Di Vona ACS Appl. Mater. Interfaces, 14, 41 (2022) 46537–46547. R.-A. Becerra-Arciniegas, R. Narducci, G. Ercolani, E. Sgreccia, L. Pasquini, M. L. Di Vona, and P. Knauth, J. Phys. Chem. C, 124, 2 (2020) 1309–1316. E. Cossar, F. Murphy, J. Walia, A. Weck, E.A. Baranova, ACS Applied Energy Materials, 5 (2022) 9938−9951.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 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".