Green Chemistry Approach to Co₃O₄ Synthesis: A Suitable Candidate for Optoelectronics and Energy Storage Devices
Bibliographic record
Abstract
Among spinel-type oxides, Co3O4 is noteworthy in energy storage, particularly in solar cells, because of its ability to absorb sunlight across the visible spectrum. This property is associated with its low band gap, making it appropriate for optoelectronic systems. Therefore, it is crucial to provide cost-effective and scalable preparation methods for Co3O4 synthesis. In this study, nano Co3O4 was easily synthesized via a one-pot method, which was a cost-effective and solid-state (solvent-free) approach under “green chemistry” conditions. The structural analyses verified that the most stable phase of cobalt oxide (Co₃O₄) was formed, with nanospheres having particle sizes lower than 50 nm. The nano Co3O4 revealed {111} surface planes, which could be the positive aspect of the synthesized sample due to their performance for oxidation reactions. As well, the synthesized Co3O4 demonstrated a relatively high specific surface area of 53.94 m²/g and a mesoporous structure with pore size distribution ranging from 2 to 50 nm, which can be effective for energy-related systems. The electroactivity of the obtained Co3O4 was confirmed using cyclic voltammetry, revealing a charge transfer resistance equal to 218 (Ω). The charge transfer process involving Co(II) ↔ Co(III) and multiple oxidation states makes Co3O4 a promising candidate for pseudocapacitor, catalyst, and support materials. Optical transitions of the as-synthesized Co3O4 were discovered in two solvents. Band gap energies of Co3O4 obtained by the Tauc plots (1.94 eV) and electrochemical measurement (1.83 eV), confirm its suitability as an efficient material with high electron-hole separation for employment in optoelectrical devices. Additionally, the synthesized Co3O4 shows a ferromagnetic behavior with high thermal stability up to 800 °C.
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 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) | 0.001 | 0.001 |
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".