Speciation of Alkyllead and Inorganic Lead by Derivatization with Deuterium-Labeled Sodium Tetraethylborate and SPME-GC/MS
Bibliographic record
Abstract
A method for full speciation and determination of alkyllead and inorganic lead(II) in aqueous samples was developed. This was accomplished by in situ derivatization with deuterium-labeled sodium tetraethylborate NaB(C2D5)4 (DSTEB). The derivatization was carried out directly in the aqueous sample and the derivatives were extracted from the headspace by a solid-phase microextraction (SPME) fiber. The extracted analytes were then transferred to a GC/MS or a GC/FID for separation and detection. The research presented demonstrates that SPME and the derivatization reagent DSTEB can be used successfully for the speciation of Pb2+, Pb(CH3)3+, Pb(C2H5)3+, and Pb(C2H5)4 in water samples. All derivatives, Pb(C2D5)4, (CH3)3Pb(C2D5), (C2H5)3Pb(C2D5), and Pb(C2H5)4, are separated using an SBP-5 column. This method was applied to monitor degradation of tetraethyllead in water. This is the first report of ethylation by DSTEB for full speciation of methyllead, ethyllead, and inorganic lead compounds. This approach can be extended to other organometallic compounds as demonstrated for ethyltin speciation. This full speciation method will aid in monitoring occurrence, pathways, toxicity, and biological effects of these compounds in the environment. It is easily adopted for field analysis.
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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 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| 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".