Biomass waste-derived porous carbon efficient for simultaneous removal of chlortetracycline and hexavalent chromium
Bibliographic record
Abstract
The simultaneous removal of mixed containments of antibiotics and heavy metals is still a big challenge in wastewater treatment. Herein, we report the successful synthesis of N-doped porous carbon (abbreviated as NC) from straw waste through the Maillard reaction to activate sp 3 -sp 2 conversion efficient for the simultaneous removal of chlortetracycline (CTC) and hexavalent chromium (Cr(VI)). In 200 min, 96.9% of Cr(VI) was reduced into Cr(III) and 93.1% of CTC was oxidatively degraded. Reactive substances (e.g., h + , e −1 , ⋅OH, and ⋅O 2 - ) were verified for the photocatalytic reactions. Besides, the possible degradation intermediates of CTC were analyzed with ultra performance liquid chromatography-mass spectrometry (UPLC-MS/MS), and the mechanism of photocatalytic degradation of CTC was then proposed. The synthesized bifunctional NC materials could also be applied for the similar system; this will open the door for promising practical applications.
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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".