1,1,2,2-Tetrachloroethane Reactions with OH<sup>-</sup>, Cr(II), Granular Iron, and a Copper−Iron Bimetal: Insights from Product Formation and Associated Carbon Isotope Fractionation
Bibliographic record
Abstract
Despite widespread implementation of zero-valent iron remediation schemes, the manner and order of chemical bond cleavage in iron-mediated organohalide transformations remains imperfectly understood. We present insights from carbon isotope fractionation for the dehalogenation of 1,1,2,2-tetrachloroethane (1,1,2,2-TeCA) and 1,1,1-trichloroethane (1,1,1-TCA) by various reactants. Elimination of HCl by OH- gave isotope fractionation in 1,1,2,2-TeCA of Euro = -25.6 per thousand, KIE(c) = 1.02 to 1.03 per carbon center, consistentwith a concerted (E2) mechanism. In contrast, 1,1,1-TCA reduction by Cr(II), Fe(0), and Cu-plated iron (Cu/Fe) resulted in Euro = -13.6 per thousand to -15.8 per thousand indicating the initial involvement of a single C-Cl bond (KIE(c) approximately 1.03). 1,1,2,2-TeCA reduction by Cr(II), Fe(0), and Cu/Fe yielded Euro = -18.7 per thousand, -19.3 per thousand, and -17.0 per thousand, respectively. In the two latter cases, depletion of the minor product TCE by 26 per thousand indicated its formation via nonreductive dehydrohalogenation. The major 1,1,2,2-TeCA reduction products, cis- and trans-DCE, differed by 2.3 per thousand +/- 1.0 per thousand in Cr(II) systems, but were equivalent in Fe(0) and Cu/Fe systems. In contrast, the ratio of cis-DCE to trans-DCE concentration was 2.5 for reduction with Cr(II) and Fe(0), but -3.8 with Cu/Fe. Complementary isotope and concentration data therefore suggest differences in the transition state geometry and/ or reaction intermediates in each reductant system.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".