Adsorption of methylene blue onto carbons made of residues from the biodiesel industry
Bibliographic record
Abstract
The performance of carbons produced from the cold-pressed cake of Raphanus sativus (L.var.), a residue from the biodiesel industry, was evaluated for the adsorption of methylene blue (MB) from synthetic aqueous solutions.The study has focused on the following three topics: (i) physical and textural characterization of the carbon, (ii) batch investigation of equilibrium and kinetics of MB adsorption at room temperature, and (iii) analysis of MB adsorption mechanism onto such carbonaceous structures.Regarding the fi rst topic, carbon was characterized using several methods such as Brunauer-Emmett-Teller (BET), Barrett-Joyner-Halenda (BJH), scanning electron microscopy (SEM), and Raman spectroscopy.A microporous carbon was found thus indicating that MB adsorption may occur predominantly at the surface of the carbon.Regarding the second topic, equilibrium tests revealed that Langmuir-based maximum MB uptake capacity was 19.8 mg g -1 and that MB kinetics onto carbon was best described by a pseudo second-order model.Data fi tting analysis confi rmed that MB adsorption onto such carbons was predominantly superfi cial.And fi nally, regarding the third topic, MB adsorption may probably occur by bonding of monomer MB through the central nitrogen atom of its molecule and through sulfur atom while MB bonding through amino nitrogen atom does not seem probable.The study reveals that carbons made of R. sativus are suitable materials for the removal of dyes from aqueous solutions, mainly if fi ner fraction of carbons is used, because MB adsorption was found to be predominantly superfi cial.
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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 | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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 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".