Ex-Situ Investigation of Activated Stainless Steel As Oxygen Evolution Reaction Electrode in Alkaline Media
Bibliographic record
Abstract
Transition metal mixed oxides have been considered as promising catalysts for OER in alkaline media due to high catalytic activity, possible long lifetime and cheap alternatives to precious metal oxides [1-3]. Increasing research interest has been dedicated to Ni-based OER catalysts in particular, which possesses all desired qualities for a catalyst including being earth-abundant and have theoretically high catalytic activity [1]. Iron impurities in nickel hydroxide was found to lower OER overpotential in Ni-based alkaline batteries [4, 5], which paved the way for NiFe catalysts as active OER electrocatalysts in water electrolysis [5-9]. Large use of Ni-rich materials is becoming an increasing difficulty in alkaline electrolysis, and the search for cheaper bulk materials has recently been intensified. In particular, cheaper stainless steels being a source of both Fe and Ni have shown promise as OER electrode. However, the as-received stainless steel has low OER activity and some surface treatment, enriching the surface with nickel is necessary. In this work, we activate as-received 316 stainless steel bulk material by electrooxidation at 1.72 V vs RHE in KOH electrolyte at room temperature. We study the effect of electrolyte pH during activation as well as oxidation time. The electrode surface layer is studied using XPS, GDOES and SEM, while the surface activity is studied electrochemically using potential step and linear sweep voltammetry in a three-electrode Teflon cell. The active surface area was assessed using cyclic voltammetry. Reaction order and Tafel slope are determined to specify the reaction mechanism. We show that surface treatment of 316 stainless steel in the highest concentration of KOH (7.5 M) gives the highest activity for a minimum of 240 minutes oxidation time. Longer oxidation times did not improve electrochemical activity. Surface analysis by XPS, SEM and GDOES show a significant increase in surface Ni after activation, which was correlated to the improved activity. The surface content of Ni increased in general with increasing electrolyte pH during activation. SEM indicates small crystals on the surface, which could be due to precipitation of dissolved species on the activated samples. The best pretreatment performed in this study leads to an overvoltage of 320 mV at 10 mA cm-2. Krasil’shchikov reaction pathway is assigned as the OER reaction mechanism corresponding to the measured reaction order and Tafel slope. All the samples have the same Tafel slope. Repetitive polarization curves after 24h chronoamperometry indicate negligible change in performance with time. This indicates that the activated stainless steel is a promising electrode material for oxygen evolution. Han, L., S. Dong, and E. Wang, Transition‐metal (Co, Ni, and Fe)‐based electrocatalysts for the water oxidation reaction. Advanced materials, 2016. 28(42): p. 9266-9291. Singh, R., J. Singh, and A. Singh, Electrocatalytic properties of new spinel-type MMoO4 (M= Fe, Co and Ni) electrodes for oxygen evolution in alkaline solutions. international journal of hydrogen energy, 2008. 33(16): p. 4260-4264. Song, F., et al., Transition metal oxides as electrocatalysts for the oxygen evolution reaction in alkaline solutions: an application-inspired renaissance. Journal of the American Chemical Society, 2018. 140(25): p. 7748-7759. Conway, B. and P. Bourgault, The electrochemical behavior of the nickel–nickel oxide electrode: Part I. Kinetics of self-discharge. Canadian Journal of Chemistry, 1959. 37(1): p. 292-307. Lyons, M.E. and M.P. Brandon, The oxygen evolution reaction on passive oxide covered transition metal electrodes in aqueous alkaline solution. Part 1-Nickel. Int. J. Electrochem. Sci, 2008. 3(12): p. 1386-1424.
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How this classification was reachedexpand
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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 | 0.000 |
| 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 | 0.000 | 0.000 |
| Open science | 0.000 | 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
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