Optimization of the Preparation Conditions of Sol-Gel Derived Ni-Co Oxide Films
Bibliographic record
Abstract
In this work, sol‐gel (SG) oxide films were formed by dip‐coating Pt substrates from Ni, Co, and mixed Ni‐Co sols. After withdrawing the substrate at a constant rate, the films were dried between 100 and 400°C for various periods of time (15 min to 1 h). Based primarily on the cyclic voltammetric behavior of the SG‐formed Ni‐Co films after drying at high temperatures, it is suggested that both the Ni and Co sites undergo redox reactions in 1 M NaOH solutions. This also explains the high charge efficiency and charge density of SG‐derived, Co‐containing Ni oxide films. Careful optimization of the experimental variables in the SG film preparation route indicated that the use of 50:50 Ni‐Co sols, a withdrawal rate of 6 cm/min, and drying at 250°C for 1 h yields films which display the highest charge density, the most rapid redox kinetics, and good stability to prolonged potential cycling. In addition, the charge capacity of the optimized 50:50 Ni‐Co SG oxide films can be increased further by the deposition of multilayers. The redox kinetics of the optimized coatings in 1 M NaOH solution were superior to those for Ni‐Co oxide films of comparable charges, but formed in other ways. Diminished reaction rates resulted when higher film drying temperatures were used (denser films) and when thicker, multilayered films were formed. © 2000 The Electrochemical Society. All rights reserved.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 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 | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".