Identification of Weak and Strong Organic Acids in Atmospheric Aerosols by Capillary Electrophoresis/Mass Spectrometry and Ultra-High-Resolution Fourier Transform Ion Cyclotron Resonance Mass Spectrometry
Bibliographic record
Abstract
A novel approach using a combination of capillary electrophoresis/mass spectrometry (CE/MS) and off-line Fourier transform ion cyclotron resonance mass spectrometry (FTICR-MS) revealed the structural details of acidic constituents of atmospheric organic aerosol. Both techniques utilized electrospray ionization (ESI), a soft ionization method, to facilitate the analysis of complex mixtures of organic compounds. CE/ESI-MS using an UltraTrol LN-precoated capillary and acidic background electrolytes at different pH values (2.5 and 4.7) was used to differentiate between weak (carboxylic) and strong (sulfonic) organic acids. On the basis of the electrophoretic mobility, m/z constraints from CE/ESI(-)-MS, and elemental composition information retrieved from off-line FTICR-MS, a variety of aliphatic and aromatic carboxylic acids (CHO-bearing molecules), nitrogen-containing carboxylic acids (CHON-bearing molecules), organosulfates (CHOS-bearing molecules), and (nitrooxy)organosulfates (CHONS-bearing molecules) were tentatively identified in the Oasis-HLB-extracted urban PM(2.5) (particulate matter with an aerodynamic diameter of <2.5 μm). The chemical known/unknown structures of detected compounds were confirmed by the semiempirical Offord model (effective mobility linearly correlated to Z/M(2/3)). The majorities of the identified compounds are products of atmospheric reactions and are known contributors to secondary organic aerosols.
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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 | 0.000 | 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".