Fluidization characterization of nano‐powders in the presence of electrical field
Bibliographic record
Abstract
Alternating electric field was used as an external assistance method to enhance the quality of fluidization of nanoparticles. The electric field was applied to the bed using two parallel electrodes, one grounded and AC voltage applied to the other. Varying electric field strength in the range of 0–1 kV/cm was used in the experiments. Hydrophilic TiO 2 nanopowder was used as the bed material. The bed was fluidized with either pure nitrogen or nitrogen containing isopropanol vapour. It was found that increasing the alternating electric field strength decreases the minimum fluidization velocity, bubble size, and agglomerate size. Adding isopropanol vapour to the fluidizing gas decreases the minimum fluidization velocity, bubble size, and agglomerate size, compared to fluidization with dry nitrogen, at the same field strength. It is shown that increasing the alternating electric field strength increases the voidage of the bed at minimum fluidization and decreases the voidage of agglomerates.
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How this classification was reachedexpand
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 | 0.000 |
| 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) | 0.000 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".