Transformation of <i>Mytella falcata</i> residual shell into <scp>CaAl</scp> / <scp>LDH</scp> adsorbent: Removal of methyl orange and methylene blue dyes
Bibliographic record
Abstract
Abstract This study analyzed the viability of using malacoculture residue ( Mytella falcata ) to produce layered double hydroxides (LDHs) and for its subsequent use as an adsorbent. The CaAl/LDH‐RE material was produced with calcium oxide from the residue and the CaAl/LDH‐AP was produced with a commercial reagent. Both were used to remove methyl orange (MO) and methylene blue (MB) dyes. The CaAl/LDH‐RE presented a surface area of 28.54 m 2 g −1 , being 65.62% larger than the CaAl/LDH‐AP material (17.23 m 2 g −1 ). The adsorbents showed mesopores distributed on a surface formed by plates in the form of hexagonal sheets arranged in an overlapping manner. The dosage of 0.05 g L −1 obtained the removal of 95% and 97% for MO, while for MB it was 94% and 93% using the adsorbents LDH/CaAl‐AP and LDH/CaAl‐RE, respectively. The system reached equilibrium at 90 min for MO and 120 min for MB. The pseudo‐second order model well represented the kinetic data reaching 11.36 mg g −1 (CaAl/LDH‐RE) and 8.42 mg g −1 (CaAl/LDH‐AP) for MO, and 4.47 mg g −1 (CaAl/LDH‐RE) and 4.14 mg g −1 (CaAl/LDH‐AP) for MB. The Freundlich model better represented the isothermal data, where the temperature exerted little influence. Adsorbents showed similar removal percentages in real and synthetic matrices. The LDH/CaAl‐RE can be applied in up to 3 cycles, maintaining its adsorption capacity. These results corroborate the use of MFW to produce CaAl/LDH‐RE, which can be used for the efficient removal of organic pollutants in an aqueous solution.
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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) | 0.001 | 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 | 0.000 |
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".