Chromium removal from electroplating waste using palm oil fuel ash
Bibliographic record
Abstract
This laboratory-scale study investigated the use of palm oil fuel ash (POFA) as an adsorbent to remove hexavalent chromium (Cr) from electroplating waste water as well as the potential of POFA as an admixture in a cement-based stabilisation and solidification (S/S) process. Results indicated that POFA was very effective in removing chromium, exceeding the 99·5% level in all experimental runs. Overall, adsorption improved as the POFA particle size decreased and the concentration of the reagent (ferrous chloride) added increased. Regarding the S/S tests, both the compressive strength and the chromium leachability of the solidified samples were found to be optimal at the lower explored ranges of POFA and ash-sludge mix ratio (0·25/0·25), water-to-solids ratio (0·7) and POFA particle size (<75 µm). Furthermore, both the compressive strength and the chromium leaching concentration of the solidified sludge samples were much lower than 5 mg/l (under most conditions tested), which satisfied the required Thai standards, either for application as a construction material or for secure landfill disposal.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 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 | 0.001 |
| 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 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".