Oiling-out Crystallization on Solid Surfaces Controlled by Solvent Exchange
Bibliographic record
Abstract
Oiling-out, also termed as liquid-liquid separation (LLPS), is a phenomenon well observed in cooling crystallization when the solution becomes cloudy due to the formation of a second liquid phase. One of the methods to control LLPS is solvent exchange where surface droplets are produce in bottom up approach. In this process, a good solvent for oil is displaced by a poor one, leading to oil nanodroplet nucleation and subsequent growth. The nanodroplets are immobilized on the surface therefore dynamics of the droplet formation and growth from LLPS can be monitored with time and quantitatively studied. We investigated oiling-out of a model component (Beta-alanine) in the mixture of isopropanol and water. The aqueous solution is displaced by isopropanol in a microchamber at controlled flow conditions. We followed the solute-rich droplet on the various substrates during the process of oiling-out. We expect that this study will give us new understanding on the dynamics of oiling-out phenomenon and the crystallization process. The knowledge may be valuable for controlling the oiling-out crystallization in the processes, separation, and purification of crystals for pharmaceutical use and other applications such as the use in functional surfaces and crystal shape engineering.
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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) | 0.007 | 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".