Enhanced adsorption performance of CuO‐Al<sub>2</sub>O<sub>3</sub> composite derived from cotton template
Bibliographic record
Abstract
Biomorphic CuO‐Al2O3 nanomaterials were fabricated via a facile and low‐cost complex‐precipitation route using cotton as a template. The as‐obtained materials were characterized by X‐ray diffraction (XRD), Fourier transform infrared spectra (FTIR), field emission scanning electron microscopy (FESEM), transmission electron microscopy (TEM), N2 adsorption‐desorption analysis, and thermogravimetry differential thermal analysis (TG‐DTA). It was found that the as‐prepared biomorphic CuO‐Al2O3 retained the tubular morphology of cotton and a diameter of about 4–5 µm. The maximum adsorption capacity for methyl blue (MB) was achieved at 97.04 mg/g which is higher than that of many other previously reported adsorbents, and that of as‐prepared CuO‐Al2O3 without a cotton template. Furthermore, the isotherms and kinetics of the adsorption process for MB were determined and analyzed in detail, and were found to obey the Freundlich isotherm model and pseudo‐second‐order kinetics. The as‐prepared biomorphic CuO‐Al2O3 sample using this facile synthetic approach is very promising for the removal of organic contaminants from wastewater.
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) | 0.000 | 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".