Validation of a Solvent-Free Sampler for the Determination of Low Molecular Weight Aliphatic Isocyanates Under Thermal Degradation Conditions
Bibliographic record
Abstract
During the thermal degradation of 1,6-hexamethylenediiso- cyanate-based (HDI) car paint, the eight most abundant isocyanates generated are isocyanic acid, methyl isocyanate, ethyl isocyanate, propyl isocyanate, butyl isocyanate, pentyl isocyanate, hexyl isocyanate, and 1,6-hexamethylenediisocyanate. For the first time, a method using solvent-free samplers is proposed and validated for the simultaneous sampling of all these isocyanates. The sampling efficiency during thermal degradation of car paint can be affected by the formation of dust and aerosols and by the emission of many chemicals, such as isocyanic acid, anhydrides, amines, and alcohols that consume the reagent or interfere in the derivatization procedure. Sampling was performed using cassettes containing two 1-(2-methoxyphenyl)piperazine (MOPIP)-coated glass fiber filters (MFs) (approximately 4.9 mg per filter) and compared with bubblers containing 15 mL of MOPIP solution in toluene (1.0 mg/mL(-1)) and with bubblers backed with MFs. A DIN 53436 laboratory scale furnace was used to generate the isocyanates under thermal degradation conditions. For an aliphatic isocyanate concentration of approximately 42 microg(NCO) m(-3), no significant difference in sampling efficiency was observed between the three techniques studied, thus confirming the sampling efficiency of the MFs. The samples were analyzed using high-performance liquid chromatography coupled with electrospray/tandem mass spectrometry. Quantification was performed in daughter mode monitoring (MOPIP+H)(+) fragments. For concentrations between 0.013 microg(NCO) mL(-1) and 0.52 microg(NCO) mL(-1) for the monoisocyanates, and between 0.026 microg(NCO) mL(-1) and 1.04 microg(NCO) mL(-1) for the HDI, the correlation coefficients were in the 0.9974-0.9996 range (n = 18). Analytical reproducibility and precision were better than 95.4% and 94.9%, respectively, for all the isocyanates. The instrumental detection limits, defined as three times the standard deviation measured at the lowest point on the calibration curve were in the 1.8-3.0 ng(NCO) mL(-1) range (n = 8), which corresponds to about 0.37-0.60 microg(NCO) m(-3) for a 15-L air sample when the filters are desorbed in 3 mL.
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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 | 0.003 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".