Influence of MgO on the Electrochemical Performance of Nickel Electrode in Alkaline Aqueous Electrolyte
Bibliographic record
Abstract
β-nickel hydroxide (β-Ni(OH)2) was prepared using precipitation method. Magnesium oxide (MgO) was synthesized by solu-tion combustion method using magnesium nitrate as oxidizer and urea as a fuel. The effects of MgO additive on the structure and electro-chemical performance of β-Ni(OH)2 electrode are examined. The structure and property of the MgO added β-Ni(OH)2 were characterized by X-ray diffraction (XRD), thermal gravimetric-differential thermal analysis (TG-DTA), Scanning electron microscopy (SEM), and Energy Dispersive X-ray (EDX) analysis. The results of the TG-DTA studies indicate that the MgO added β-Ni(OH)2 contains adsorbed water mol-ecules and anions. Partial substitution of MgO for graphite to β-nickel hydroxide is found to exhibit improvement in the electrochemical activity. Anodic peak potential (Epa) and cathodic peak potential (Epc) values are found to decrease remarkably after the incorporation of MgO into the β-Ni(OH)2 electrode. Further, addition of MgO is found to enhance the reversibility of the electrode reaction. Compared with β-Ni(OH)2 electrode, MgO substituted β-Ni(OH)2 electrode is found to exhibit higher proton diffusion coefficient. These findings suggest that the MgO substituted β-Ni(OH)2 electrode possess improved electrochemical properties such as enhanced reversibility of electrode reaction and higher proton diffusion coefficient and thus can be recognized as a promising candidate for the battery electrode applications.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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 teacher head, 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".