DEP actuation of emulsion jets and dispensing of sub-nanoliter emulsion droplets
Bibliographic record
Abstract
Liquid Dielectrophoresis (L-DEP) has been successfully leveraged at microscopic scales and shown to provide a controllable means of on-chip precision dispensing and manipulation of sub-nanoliter single emulsion droplets. In this paper, we report on the dynamics of a DEP actuated emulsion jet prior to break-up and compare its characteristic behavior based on the lumped parameter model of Jones et al. (R. Ahmed and T. B. Jones, J. Micromech. Microeng., 2007, 17, 1052). Furthermore, features and aspects of these emulsion jets, their break-up and formation of sub-nanoliter emulsion droplets is studied in further detail. Applications of the proposed scheme in dispensing encapsulated sub-nanoliter droplets is envisioned in various fields including microTAS, on-chip handling and storage of cells and other biological samples for longer duration in controlled environments as well as solving the more general encapsulation issues in surface microfluidic devices. Scalability of the proposed scheme is shown by producing controlled sample-oil single emulsion droplets (aqueous samples in oil) in the range of 50-400 picoliters.
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.
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".