ClimateOpenAlex
Heuristic editor, no API keyVerdict: RoutineBenchmarking Faradaic Efficiency and O2 Quantification during Water Oxidation under Mild Conditions Using a 3D-Printed Cell and Clark Electrode
Abstract Producing green hydrogen via water electrolysis offers a potential pathway for achieving a sustainable energy transition.
Key numbers
- 5.7% FE
VerdictCompetent work. Briefs at most.
Abstract
Abstract Producing green hydrogen via water electrolysis offers a potential pathway for achieving a sustainable energy transition. Despite its potential, it is limited by the sluggish kinetics of OER, which motivates the development of efficient catalysts. In addition, the field still lacks standardized and reproducible approaches for evaluating catalyst faradaic efficiency (FE) and monitoring the oxygen production. Therefore, we present a 3D-printed electrochemical cell coupled with a Clark sensor for in situ oxygen quantification during OER, while measurement uncertainties were examined to confirm the precision and reproducibility of the methodology. The effects of electrolyte concentration (0.1, 0.5, and 1.0 mol L–1 KNO3), different electrolytes (KNO3 and PBS), electrode surface area (0.071 and 0.195 cm2), and applied constant current (1, 5, and 10 mA) were investigated. Statistical validation demonstrated high reproducibility and robustness. At 10 mA in 0.1 mol L–1 KNO3 using a 0.071 cm2 electrode area, Pt exhibited higher oxygen evolution and FE (4.55 ± 0.5 mg L–1, 85.6 ± 10.8%) than GC (2.32 ± 0.3 mg L–1, 43.6 ± 6.1%). The methodology was subsequently applied to Prussian blue (FePBA), and its respective cobalt and nickel Prussian blue analogues (CoPBA and NiPBA, respectively). Among the investigated materials, NiPBA exhibited the highest OER activity (0.40 ± 0.03 mg L–1 with 76.5 ± 5.7% FE), and was comparable to CoPBA, while both outperformed FePBA at 1 mA. A trend in the NOP was observed among the PBAs, following the order NiPBA ≥ CoPBA > FePBA. This approach provides a reproducible platform for dissolved oxygen quantification and the standardized benchmarking of OER electrocatalysts.
The editor's rubric
| Dimension | Level | Weight | What that level means |
|---|---|---|---|
| Leverage | ███░░ 3 | 16% | A method or resource many groups across the field will adopt within a year. |
| Magnitude | ███░░ 3 | 20% | Large gain: roughly 2x, or a clear new state of the art on a hard, unsaturated problem. |
| Evidence | ███░░ 3 | 20% | Solid: multiple benchmarks or cohorts, ablations, fair baselines, released code or data. |
| Novelty | ██░░░ 2 | 10% | A new combination of known ideas. |
| Trajectory | ██░░░ 2 | 14% | Some room to improve with obvious engineering. |
| Stakes | ██░░░ 2 | 20% | Benefits a professional community (practitioners, clinicians, engineers). |
Editor’s rationale
Heuristic triage from title and abstract text only, not a reading of the paper. Cues found: method (we propose); breadth (programmable); gains (outperforms); verification (error bars, independent replication); scale (efficient); stakes (energy). Red flags: derivative (comparative study).
How the score was computed
- Merit
- 5.1 / 10
- Adjusted merit
- 4.5 / 10
- Attention
- 0%
- Freshness
- 85%
- Citations0 (reference 15, via openalex, Oct 10, 2026, 07:29 UTC)