Quantitative High-Resolution Mapping of Phenanthrene Sorption to Black Carbon Particles
Bibliographic record
Abstract
Sorption of hydrophobic organic contaminants such as polycyclic aromatic hydrocarbons (PAHs) to black carbon (BC) particles has been the focus of numerous studies. Conclusions on sorption mechanisms of PAH on BC were mostly derived from studies of sorption isotherms and sorption kinetics, which are based on batch experiments. However, mechanistic modeling approaches consider processes at the subparticle scale, some including transport within the pore-space or different spatial pore-domains. Direct evidence based on analytical techniques operating at the submicrometer scale for the location of sorption sites and the adsorbed species is lacking. In this work, we identified, quantified, and mapped the sorption of PAHs on different BC particles (activated carbon, charcoal and diesel soot) on a 25-100 nm scale using scanning transmission X-ray microscopy (STXM). In addition, we visualized the pore structure of the particles by transmission electron microscopy (TEM) on the 1-10 nm-scale. The combination of the chemical information from STXM with the physical information from TEM revealed that phenanthrene accumulates in the interconnected pore-system along primary "cracks" in the particles, confirming an adsorption mechanism.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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 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".