Sorption and Desorption Studies on Toxic Metals From Brewery Effluent Using Eggshell as Adsorbent
Bibliographic record
Abstract
The adsorption capacity of eggshell in removing Pb2+, Ni2+, Mn2+, Zn2+ and Co2+ from standard solution and consolidated brewery effluent was investigated in this study. The sorption process dependent on pH, contact time, initial metal ion concentration and sorbent dosage with pH 7.0 being the optimum value, and maximum sorption was attained within the first 60 minutes. The equilibrium sorption data followed the Langmuir and Freundlich isotherms with R2 ranges of 0.834 – 0.993 and 0.939 – 0.998 respectively. The kinetic data were best described with pseudo second order kinetic. Desorption of sorbed metal ions was efficient with 3.0 mol/L NaOH. The affinity of metal ion sorption was in the order of Co2+ > Pb2+ > Ni2+ > Zn2+ > Mn2+. The percentage adsorptions of Mn2+ and Zn2+ from the brewery effluent were 95.86% and 44.29% respectively, while the corresponding percentage desorption of Mn2+ and Zn2+ were 19.94% and 35.48% respectively.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.001 | 0.005 |
| Scholarly communication | 0.000 | 0.007 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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 teacher head, 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".