On the role of crystal-liquid interfacial energy in determining scaling, nucleation and crystal growth in membrane distillation crystallisation
Bibliographic record
Abstract
While the interfacial energy (σ) of a solute contributes toward the excess surface free energy requirement for nucleation, its role in determining scaling, nucleation and crystal growth processes within membrane distillation has yet to be described. Highly soluble salts (low σ) are generally understood to possess a low nucleation energy, where the limited relative supersaturation ( Δ c / c ∗ ) can favour a heterogeneous primary nucleation mechanism. This was indicated by scaling, which is generally presumed to occur in response to the membrane substrate lowering the critical Gibbs free energy requirement for nucleation (ΔG∗). For less soluble salts (high σ), primary nucleation was not observed until Δ c / c ∗ exceeded a threshold of 1. It was postulated that the excess chemical potential available was sufficient to favour homogeneous primary nucleation in the bulk solution, which mitigates scale formation on the membrane. In-situ characterisation methods also established how nucleation rate and crystal size could be directly attributed to the σ, which is compatible with the crystallisation literature on aqueous salts within a comparable range of solubilities. While crystallisation tends to be controlled by a combination of thermodynamic and kinetic processes, this study illustrates how interfacial energy (a thermodynamic quantity) can be used to anticipate nucleation and crystal growth mechanisms in membrane crystallisation. • Non-invasive tools are used to characterise nucleation on membrane and in bulk. • Crystal-liquid interfacial energy is related to nucleation rate and induction time. • The probability for nucleation on the membrane is correlated to nucleation theory. • Classical membrane scaling is more relevant for highly soluble salts. • Nucleation rate and crystal size are also correlated to the solubility of the salt.
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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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| 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".