Visualization and image analysis of droplet puffing and micro-explosion in spray-flame synthesis of iron oxide nanoparticles
Why this work is in the frame
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Bibliographic record
Abstract
Abstract Combusting metal precursor-laden droplets, required in spray-flame synthesis of nanomaterials, are known to undergo a rapid and disruptive disintegration, i.e., puffing and micro-explosion. In this work, imaging with high spatiotemporal resolution and image-analysis routines were developed to investigate droplet disruption in spray-flame synthesis of metal oxides. Droplet shadowgraphs were imaged on a high-speed camera. The solvent was a mixture of 35 vol% ethanol and 65 vol% 2-ethylhexanoic acid which (in some cases) was mixed with a 0.2 mol/l iron(III) nitrate nonahydrate precursor. Photometric and morphological processing identified in-focus features, estimated their size, velocity, and circularity, and discriminated regular, spherical droplets from disrupting ones. While solely regular droplets were found in the spray flame of pure solvent, with the precursor/solvent mixture, disrupting droplets were found in addition to the regular droplets. Disruption events were phenomenologically classified into puffing, comprising droplet deformation and local eruption, and micro-explosion, the violent disintegration of the droplet into multiple fragments. Puffing was found to occur much more frequently than micro-explosions. Disrupting droplets had a 32% smaller Sauter mean diameter than regular droplets, indicating that disruptions are beneficial for rapid spray evaporation. At 40 and 50 mm heights above the burner, about 8 and 6%, respectively, of the in-focus droplets are disrupting per millimeter axial distance. Thus, throughout their lifetime in the spray flame, all precursor-laden droplets are expected to experience disruption. Graphical abstract
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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 | 0.000 | 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) | 0.000 | 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