Improved sizing of soot primary particles using mass-mobility measurements
Why this work is in the frame
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Bibliographic record
Abstract
The properties and impacts of aggregated aerosol particles (i.e., soot, metal oxide fumes) depend on their morphology, as characterized by fractal dimension, prefactor, and primary particle diameter. The morphology may be measured directly by time-consuming ex situ microscopy or rapid but indirect in situ methods. Previously, it was found that particle mass and mobility measurements could be used for the estimation of the primary particle diameter of zirconia aggregates, using plausible assumptions related to the fractal structure (specifically, prefactor and exponent ). Since the formation and growth of zirconia aggregates are different from carbon soot, here we compare primary particle diameters measured directly from transmission electron microscopy analysis of soot particles with the diameters estimated from mass–mobility measurements. Performing extensive measurements on soot emissions from two reciprocating engines over a range of operating conditions, we found that there are no universal values of and that can be used for all conditions. However, new optimized values of and are estimated here for soot particles. The variation of the primary particle diameter with particle size is also taken into consideration and is shown to be essential to obtain physically realistic results. Using optimized values of and , the average primary particle sizing error is reduced for all soot types. This suggests that with some calibration, in situ sizing of the primary particle diameter, using mass and mobility measurements, can provide useful accuracy.Copyright © 2016 American Association for Aerosol Research
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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 | 0.002 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it