Mechanism of Biosorption of Heavy Metals by <i>Mucor rouxii</i>
Bibliographic record
Abstract
Abstract Fungi such as Aspergillus niger and Mucor rouxii are capable of removing heavy metals from aqueous solutions. The role various functional groups play in the cell wall of M. rouxii in metal biosorption of lead, cadmium, nickel and zinc was investigated in this paper. The biomass was chemically treated to modify the functional carboxyl, amino and phosphate groups. These modifications were examined by means of infrared spectroscopy. It was found that an esterification of the carboxyl groups and phosphate and a methylation of the amine groups significantly decreased the biosorption of the heavy metals studied. Thus, the carboxylate, amine and phosphate groups were recognized as important in the biosorption of metal ions by M. rouxii biomass. The role the lipids fraction play was not significant. The study showed that Na, K, Ca and Mg ions were released from the biomass after biosorption of Pb, Cd, Ni and Zn, indicating that ion exchange was a key mechanism in the biosorption of metal ions by M. rouxii biomass.
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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) | 0.001 | 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".