Liquid chromatography/tandem mass spectrometry for analysis of 1,2‐dibromo‐4‐(1,2‐dibromoethyl)cyclohexane (TBECH) and 1,2,5,6‐tetrabromocyclooctane (TBCO)
Bibliographic record
Abstract
Although the two flame retardants 1,2-dibromo-4-(1,2-dibromoethyl)cyclohexane (TBECH) and 1,2,5,6-tetrabromocyclooctane (TBCO) have been widely used, a selective instrumental method of analysis for these compounds has not been developed to date. In this study, we demonstrate the feasibility to utilize liquid chromatography/tandem mass spectrometry (LC/MS/MS) for the separation and analysis of α- and β-TBCO and α-, β-, γ-, and δ-TBECH. Acetone was initially used in a tetrahedron solvent system for LC optimization. A simple isocratic elution allowed near-baseline separation of these compounds. Different ionization approaches and mechanisms were investigated. The mass spectrometric transition of [M + O(2)](-) => Br(-) (459.8 => 78.9) was a selective detection method for the target analytes. Good instrument detection limits (5 pg for γ-/δ-TBECH, 125 pg for α-/β-TBECH, and 30 pg for α-/β-TBCO with 2.0 µL injection) were obtained. Excellent linearity up to 50 ng/µL (R(2) >0.999) was also achieved. This method has been applied to environmental samples (surface water) for screening purposes with recoveries ranging from 76-92% (CV%: 5-8%). This method shows significant improvement over previous methods.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.002 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.005 |
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".