Electron paramagnetic resonance of sonicated powder suspensions in organic solvents
Bibliographic record
Abstract
The chemical effects of the acoustic cavitation generated by ultrasound translates into the production of highly reactive radicals. Acoustic cavitation is widely explored in aqueous solutions but it remains poorly studied in organic liquids and in particular in liquid/solid media. However, several heterogeneous catalysis reactions take place in organic solvents. Thus, we sonicated trimethylene glycol and propylene glycol in the presence of silica particles (SiO2) of different sizes (5–15 nm, 0.2–0.3 µm, 12–26 µm) and amounts (0.5 wt% and 3 wt%) at an ultrasound frequency of 20 kHz to quantify the radicals generated. The spin trap 5,5-dimethyl-1-pyrrolin–N-oxide (DMPO) was used to trap the generated radicals for study by electron paramagnetic resonance (EPR) spectroscopy. We identified the trapped radical as the hydroxyalkyl radical adduct of DMPO, and we quantified it using stable radical 2,2,6,6-tetramethyl-1-piperidinyloxy (TEMPO) as a quantitation standard. The concentration of DMPO spin adducts in solutions containing silica size 12–26 µm was higher than the solution without particles. The presence of these particles increased the concentration of the acoustically generated radicals by a factor of 1.5 (29 µM for 0.5 wt% of SiO2 size 12–26 µm vs 19 µM for 0 wt%, after 60 min of sonication). Ultrasound produced fewest radicals in solutions with the smallest particles; the concentration of radical adducts was highest for SiO2 particle size 12–26 µm at 0.5 wt% loading, reaching 29 µM after 60 min sonication. Ultrasound power of 50.6 W produced more radicals than 24.7 W (23 µM and 18 µM, respectively, at 30 min sonication). Increased temperature during sonication generated more radical adducts in the medium (26 µM at 75 °C and 18 µM at 61 °C after 30 min sonication). Acoustic cavitation, in the presence of silica, increased the production of radical species in the studied organic medium.
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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 | 0.001 |
| 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".