Oiling‐Out Crystallization of Beta‐Alanine on Solid Surfaces Controlled by Solvent Exchange
Bibliographic record
Abstract
Abstract In this work, the solvent‐exchange crystallization processes of beta‐alanine in mixture of isopropanol and water on solid surfaces are reported. As the antisolvent isopropanol displaces the alanine solution pre‐filled in a microchamber, liquid–liquid phase separation occurs at the mixing front. The alanine‐rich subphase forms surface microdroplets that subsequently crystallize with during the solvent exchange. It is found that the flow rates and solid surfaces have significant influence on the droplet size, growth rate, and crystal size and morphology. At fast flow rates, the droplets solidify rapidly, forming spherical‐cap structures resembling the shape of droplets, in contrast to crystal microdomains or thin films formed at slow flow rates. On a highly hydrophilic surface, the crystals form thin film without droplets formation. It is further demonstrated that by the solvent exchange, the crystals, generated by using a stock solution with a very low concentration of the precursor, can be used as seeds to facilitate crystallization in bulk solution. The results suggest that the solvent exchange has the potential to be an effective approach for controlling oiling‐out crystallization, and to be wider applied in, such as, separation and purification of many food, medical, and therapeutic ingredients.
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 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".