Assessment of Remediation of Municipal Wastewater Using Activated Carbon Produced from Sewage Sludge
Bibliographic record
Abstract
This study evaluates the potential to synthesize an adsorbent for wastewater remediation applications from an anaerobic digestion by-product synthesized using biomaterials and a less energy-intensive process. The synthesized sludge-based granular activated carbon (GAC) was used to adsorb Cr(VI) and Cd(II) in a batch reactor stirred for 24 h at 25 °C. The surface chemistry of the material was assessed porosity with BET, SEM for morphology, EDS-XRF for elemental analysis, and functional groups on these materials using FTIR and TGA for thermal profile. SBET of the SAC was discovered to be 481.370 m2/g with a VT of 0.337 cm3/g, respectively 9.02 and 2.23 times greater than raw sludge. The modification to SAC shows a dramatic increase in performance from 40% to 98.9% equilibrium adsorption rate. The maximum or equilibrium removal (99.99%) of Cr(VI) and Cd(II) was achieved by 0.8 and 1.4 g SAC dosage, respectively. Thus, it can be concluded that activation of sewage sludge was effective in enhancing the surface area and pore volume which made it suitable for AMD remediation application.
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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 | 0.001 | 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".