Structural, Morphological and Optical Properties of (NiO)1-x(Co3O4)x Composite Thin Films Prepared by Chemical Spray Pyrolysis Technique
Bibliographic record
Abstract
The aim of the study is to produce thin films of (NiO)1-x(Co3O4)x using spray pyrolysis technique.Different volume ratios of NiO, Co3O4 were taken to form thin films with volume ratios of (0,25, 50, 75, and 100) %.The films were deposited on a glass substrate at a temperature of 400.Energy dispersive X-ray spectroscopy (EDX), the analysis revealed the prominent presence of the components Ni, O, and Co, X-ray diffraction (XRD), these films showed a crystal structure of the films was identified to be polycrystalline, with cubic structure for nickel oxide in the planes ( 111), ( 200), ( 202) and ( 222), field emission scanning electron microscopy (FESEM), It can be noted thin films have a common surface shape comprising many randomly placed chunks or aggregates of Co3O4 on the top surface of the films, and ultraviolet-visible (UV-Vis) spectrophotometers.Were these the analytical techniques used in the study to look into the composition, structure, morphology, and optical properties of the thin films.The films have polycrystalline cubic structures.The surface morphology of (NiO)1-x(Co3O4)x films show aggregates or masses of Co3O4 and NiO randomly distributed on the upper surface of the films with increasing Co3O4 concentration.The (NiO)1-x(Co3O4)x films have a surface morphology containing aggregates or clusters of Co3O4 and NiO randomly dispersed on the top surface.The optical properties and optical constants of the prepared (NiO)1-x(Co3O4)x films were investigated in the spectral range of 300-1100nm.In general, the absorbance increases with increasing Co3O4 concentration.The direct energy gap decreases with increasing Co3O4 concentration, and its value is within (3.75 to 2.1) eV.These results are good for sensor applications.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.003 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| 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
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".