Electrodilatometry of Liquids, Binary Liquids, and Surfactants
Bibliographic record
Abstract
When a liquid is subjected to high electric field, its volume change (ΔV) can be increased or decreased depending upon the liquid under investigation. A new technique has been developed from our laboratory to measure the relative volume change per E2 and is known as “Electrodilatometry (ED)” which may be expressed as: $$ R = \frac{{V - V_0 }} {{V_0 }}\frac{1} {{E^2 }} = \frac{{\Delta V}} {{V_0 }}\frac{1} {{E^2 }} $$ , where R is known as “Electrodilatometric Effect (EDE)”, V and V0 are the volume of liquid with and without the field, respectively. ED is one of the nonlinear effects such as electro-optic Kerr effect, the electrostriction, dielectrophoresis, nonlinear dielectric effect (NDE). Ed is found to be very sensitive to hydrogen-bonded liquids. It has been applied to study pure liquids, binary mixtures, alcohols, and non-ionic surfactants such as Triton X-100. The signs of EDE (R), Kerr constant (B) and NDE (Δε/F2) are compared and contrasted. A few models have been used to calculate R with limited success. Not only can ED be used with smaller molecules but it should also be a potential tool to study polymer solutions and supramolecular assemblies.
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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) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.002 | 0.003 |
| 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; both teacher heads agree on what is shown here.
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".