Nitrogen-Doped Carbon Materials as Metal-Free Catalyst for the Dechlorination of Trichloroethylene by Sulfide
Bibliographic record
Abstract
A new method for trichloroethylene (TCE) dechlorination is proposed using sulfide (HS– and S2–) as reductant under the mediation of nitrogen-doped carbon materials (NCMs). About 99% of the TCE was converted to acetylene after 200 h using this method. Dechlorination of TCE in the NCMs–sulfide system (NCSS) followed pseudo-first-order kinetics. Pyridinic N (N6) on surface of the NCMs appeared to play a critical role in NCSS as shown by the good linear relationship between the surface content of N6 and kobs. Nucleophilic substitution was suggested as the first step in TCE dechlorination, and the nucleophilic reagent was identified as a sulfur intermediate with C–S–S–H as the functional group. The generation of C–S–S–H could be ascribed to the interaction between positively charged carbon atoms in N6 and negative charged sulfide. This work is the first to demonstrate that sulfide combined with NCMs can produce active substances that are effective in TCE dechlorination and the findings will assist in the development of strategies that use natural sulfide as reductant for detoxicating organic chloroethene contaminants.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.002 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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".