Enantioselective Analytical- and Preparative-Scale Separation of Hexabromocyclododecane Stereoisomers Using Packed Column Supercritical Fluid Chromatography
Bibliographic record
Abstract
Hexabromocyclododecane (HBCDD) is an additive brominated flame retardant which has been listed in Annex A of the Stockholm Convention for elimination of production and use. It has been reported to persist in the environment and has the potential for enantiomer-specific degradation, accumulation, or both, making enantioselective analyses increasingly important. The six main stereoisomers of technical HBCDD (i.e., the (+) and (-) enantiomers of α-, β-, and γ-HBCDD) were separated and isolated for the first time using enantioselective packed column supercritical fluid chromatography (pSFC) separation methods on a preparative scale. Characterization was completed using published chiral liquid chromatography (LC) methods and elution profiles, as well as X-ray crystallography, and the isolated fractions were definitively identified. Additionally, the resolution of the enantiomers, along with two minor components of the technical product (δ- and ε-HBCDD), was investigated on an analytical scale using both LC and pSFC separation techniques, and changes in elution order were highlighted. Baseline separation of all HBCDD enantiomers was achieved by pSFC on an analytical scale using a cellulose-based column. The described method emphasizes the potential associated with pSFC as a green method of isolating and analyzing environmental contaminants of concern.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".