Role of Precipitating Solute Curvature on Microdrops and Nanodrops during Concentrating Processes: The Nonideal Ostwald–Freundlich Equation
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Bibliographic record
Abstract
The microdrop concentrating process, which is one of the manipulations in the microdrop platform of microfluidic technologies, is a useful technique, especially in biological applications. This process may encounter a solute precipitation within the droplet if the solute reaches its solubility limit. In the case of very small solid precipitates, the solid particle size will affect the solubility limit, and the Ostwald-Freundlich equation (OFE) describes this dependency. Including the OFE in analysis affects the design parameters for this type of system and the system's thermodynamic stability. Here, by means of Gibbsian surface thermodynamics, we provide the thermodynamic description and stability analysis of this system considering the role of the Ostwald-Freundlich equation. Previously we have investigated the stability of the system without considering the OFE, which is equivalent to using a constant solubility limit. Herein it is shown that the OFE significantly affects the results for nanometer drop sizes and that various stability behaviors are possible.
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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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
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Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
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