Mass Spectrometric Analysis of Bisphenol A Desorption from Titania Nanoparticles: Ammonium Acetate, Fluoride, Formate, and Hydroxide as Chemical Desorption Agents
Bibliographic record
Abstract
Bisphenol A (BPA) is a widely used chemical in several consumer products and a well-studied environmental toxicant, and therefore, its accurate measurement is highly demanded. However, the co-presence of nanoparticles as an emerging class of contaminants could result in inaccurate determination of BPA due to binding of BPA onto nanoparticle surface. In this study, mass spectrometry (MS) was used to investigate desorption of BPA bound on the surface of titania (TiO2) nanoparticles in water. Ammonium acetate, fluoride, formate, and hydroxide were evaluated as chemical agents for their desorption capabilities. The percentages of recovery, adsorption, and desorption were determined by this new method without requiring any prior separation of nanoparticles from BPA. MS analysis demonstrated the desorption of BPA by 10–20 mM of ammonium hydroxide for a mixture of 5 µg/mL BPA and 10 µg/mL TiO2 nanoparticles, with a desorption efficiency of 72 ± 1%. Due to adsorption of BPA onto the nanoparticle surface that was inefficient for electrospray ionization, the resulting abundance of target ions could be reduced in the detection of BPA by mass spectrometry. As such, these findings collectively promise an accurate determination of the total BPA concentration in water whether it exists in the free or bound form. Efficient desorption of contaminants from the surface of nanoparticles would improve the accuracy of the contaminant analysis by mass spectrometry.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".