A novel miniature inverted-flame burner for the generation of soot nanoparticles
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Lab-scale soot nanoparticle generators are used by the aerosol research community to study the properties of soot over a broad range of particle size distributions, and number and mass concentrations. In this study, a novel miniature inverted-flame burner is presented and its emitted soot particles were characterized. The burner consisted of two co-annular tubes for fuel and co-flow air and the flame was enclosed by the latter. The fuel used was ethylene. A scanning mobility particle sizer (SMPS) and an aerodynamic aerosol classifier (AAC) were used to measure mobility and aerodynamic size distribution of soot particles, respectively. Particle morphology was studied using transmission electron microscopy (TEM). The elemental carbon (EC) and organic carbon (OC) content of the soot were measured using thermal-optical analysis (TOA). The burner produced soot particles with mobility diameter range of 66–270 nm, aerodynamic diameter range of 56–140 nm, and total concentration range of 2 × 105–1 × 107 cm−3. TEM images showed that most soot particles were sub-micron soot aggregates. Some soot superaggregates, typically larger than 2 µm in length, were observed and their abundance increased with ethylene flow rate. TOA showed that the concentration of EC in the generated soot increased with ethylene flow rate, and the soot was observed to have high EC fraction at high ethylene flow rates. The miniature inverted-flame burner was demonstrated to produce soot nanoparticles over a range of concentrations and sizes with high EC content, making it a practical device to study soot nanoparticle properties in different applications.Copyright © 2019 American Association for Aerosol Research
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 |
| 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