Massive generation of metastable bulk nanobubbles in water by external electric fields
Bibliographic record
Abstract
Nanobubbles (NBs) are nanoscopic gaseous domains than can exist on solid surfaces or in bulk liquids. They have attracted substantial attention due to their long-time (meta)stability and a high potential for real-world applications. Using an approach not previously investigated, we exploit surface-electrostatic NB formation and stabilization via application of external electric fields in gas-liquid systems, with the marked result of massively increased gas uptake into the liquid in NB form. The de facto gas solubility enhancement (over many months) ranges from 2.5-fold for oxygen to 30-fold for methane vis-à-vis respective Henry's law values for gas solubility; the more hydrophobic the gas, the more spectacular the increase. Molecular dynamics simulations reveal that the origin of NBs' movement lies in dielectrophoresis, while substantial NB stabilization arises from a surface-polarization interaction.
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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".