Exploring the diverse applications of sol–gel synthesized CaO:MgAl2O4 nanocomposite: morphological, photocatalytic, and electrochemical perspectives
Bibliographic record
Abstract
Abstract A nanocomposite of CaO:MgAl2O4 was synthesized through a straightforward and cost-effective sol–gel method. The investigation of the novel CaO:MgAl2O4 nanocomposite encompassed an examination of its morphological and structural alterations, as well as an exploration of its photocatalytic activities and electrochemical characteristics. XRD analysis revealed a nanocomposite size of 24.15 nm. The band gap, determined through UV studies, was found to be 3.83 eV, and scanning electron microscopy (SEM) illustrated flake-like morphological changes in the CaO:MgAl2O4 samples. TEM, HRTEM, and SAED studies of a CaO:MgAl2O4 nanocomposite would reveal important details about its morphology, crystallography, and nanostructure. Photocatalytic activity was quantified by studying the degradation of Acid Red-88 (AR-88) dye in a deionized solution, achieving a 70% dye degradation under UV irradiation in 120 min. Plant growth examinations were carried out using dye degraded water to test its suitability for agriculture. The electrochemical energy storage and sensing applications of the prepared nanocomposite were examined using CaO:MgAl2O4 modified carbon paste electrode through cyclic voltammetry (CV) and electrochemical impedance spectroscopy (EIS). In conclusion, the synthesized CaO:MgAl2O4 nanocomposite demonstrated promising morphological and structural characteristics, efficient photocatalytic activity, and potential applications in electrochemical energy storage, highlighting its versatility for various technological and environmental applications. Graphical abstract
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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".