Crystalline and amorphous cobalt-based metal oxides for water oxidation reaction – structure, composition, morphology and electrochemical
Bibliographic record
Abstract
Cu, Ni, and Fe-substituted cobalt-based amorphous materials (CoOx, CuCo2Ox, Ni0.5Cu0.5Co2Ox, Fe0.1Cu0.9Co2Ox, and Fe0.1Ni0.9Co2Ox) were prepared by thermal decomposition method and employed as electrocatalysts for oxygen evolution reaction (OER). These materials were characterized by scanning electron microscopy (SEM), energy dispersive X-ray spectroscopy (EDX), X-ray diffraction (XRD), transmission electron microscopy (TEM), high-resolution transmission electron microscopy (HR-TEM) and X-ray photoelectron spectroscopy (XPS). CuxCo3-xO4 (0 ≤ x ≤ 1), NixCu1-xCo2O4 (0 ≤ x ≤ 0.75) and FeyCux-yCoxO4 (x=1, 1.5 and y = 0.1, 0.15) were also by thermal decomposition method. Surface area measurements were performed using cyclic voltammetry (CV) and electrochemical impedance spectroscopy (EIS). The catalytic activity of spinel oxides and amorphous metal oxides for OER was analyzed by CV, while kinetic studies were carried out using a rotating disc electrode (RDE). \n\nTEM and HR-TEM analysis were performed on polarized and nonpolarized CuCo2O4. The study clearly indicates that the as-prepared CuCo2O4 possesses a higher degree of crystallization compared to the polarized sample. The crystallite size of the samples measured by TEM and XRD analysis is very similar. Surface area measurements indicate that the incorporation of Cu and Ni increased the surface area of amorphous and crystalline samples. The incorporation of Fe increased the surface area of the amorphous samples, while an opposite trend was observed in the case of spinel oxides. XPS analysis indicates that the surface of both amorphous and crystalline samples contains different species and the metal ions exist in different oxidation states. Catalytic activity was measured as a function of geometric and real surface area. Both amorphous and spinel oxides were found to be active for OER. However, when corrected for real surface area, spinel oxides provided much higher current density compared to amorphous samples. Our study indicates that spinel oxides outperform amorphous samples for OER.
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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 | 0.000 |
| 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 | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".