Simultaneous Removal of Lignin and 2,4-Dichlorophenol in Pulp and Paper Mill Wastewater Using a Supervibration-photocatalytic Reactor
Bibliographic record
Abstract
Advanced photocatalytic degradation of lignin and 2,4-dichlorophenol (2,4-DCP) was studied. The method used a newly developed supervibration-photocatalytic reactor based on the photocatalytic process combined with a supervibration agitator. Effects of operating conditions such as initial pH, UV intensity and supervibration frequency on removal efficiency were investigated. From the results obtained, removal efficiencies of lignin and 2,4-DCP were similar pattern. UV intensity and supervibration frequency in a low initial pH increased removal efficiencies of lignin and 2,4-DCP. The optimum operating condition for a supervibration-photocatalytic reactor was found at initial pH 5, 25.2mW/cm2 UV intensity and 50Hz supervibration frequency. Under the optimum treatment condition, the reactor could simultaneously remove lignin and 2,4-DCP up to 75.1% and 94.1%, respectively within 420min.
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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".