Degradation of chlorinated butenes and butadienes in granular iron columns
Bibliographic record
Abstract
Manufacturing facilities for production of chlorobutyl rubber have the potential to release a mixture of at least 5 chlorinated butenes and butadienes including trans-1,4-dichlorobutene-2 (1,4-DCB-2), 3,4-dichlorobutene-1 (3,4-DCB-1), 2,3,4-trichlorobutene-1 (TCB), 2-chlorobutadiene-1,3 (chloroprene) and 2,3-dichlorobutadiene-1,3 (DCBD) into groundwater environment. To evaluate the potential of using granular iron in the remediation of the above contaminants, a series of column experiments were conducted. Degradation of all 5 compounds followed pseudo-first-order kinetics. The three chlorinated butenes degraded much faster (surface area normalized half-lives, t(1/2)', ranged from 1.6 to 5.2 min m2/mL) than the 2 chlorinated butadienes (t(1/2)' ranged from 102 to 197 min m2/mL). All contaminants fully dechlorinated by granular iron to 1,3-butadiene as a common reaction intermediate that then degraded to a mixture of relatively non-harmful end products consisting of 1-butene, cis-2-butene, trans-2-butene and n-butane. Based on the kinetic data, product distributions, and chlorine mass balances, reaction pathways for these compounds are proposed. For the chlorinated butenes, 3,4-DCB-1 and TCB, undergo reductive beta-elimination reactions resulting in 1,3-butadiene and chloroprene intermediates. Dechlorination of 1,4-DCB-2 to 1,3-butadiene occurs through a reductive elimination similar to reductive beta-elimination. For dechlorination of the two chlorinated butadienes, chloroprene and DCBD, dechlorination occurs through a hydrogenolysis pathway. The common non-chlorinated intermediate, 1,3-butadiene, undergoes catalytic hydrogenation resulting in a mixture of butane isomers and n-butane. The results suggest that granular iron is an effective material for treatment of groundwater contaminated with these compounds.
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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 | 0.000 |
| 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) | 0.000 | 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".