Clustering in nondemixing mixtures of repulsive particles
Bibliographic record
Abstract
Using classical density functional theory (DFT), we investigate the phase behavior of binary mixtures, in which the interactions between all particles are described by ultrasoft, repulsive potentials. In the pure case, one of the species, species 2, forms clusters, and freezes into a cluster crystal at sufficiently high density, while the other, species 1, does not cluster and remains liquid at all densities of interest. For some mixtures, DFT predicts two instabilities in the liquid with respect to modulations of differing periodicities. One instability results from the cluster-crystal forming tendency of species 2. In concentrated species 2 mixtures, we find species 1 clusters in response to species 2 cluster formation, eventually freezing either on, or between the species 2 lattice sites. The second instability arises when the interaction between unlike species is either more favorable, or less favorable, than the interaction between like species; when less favorable, the particles form a highly delocalized cluster crystal. We examine the structure of the liquid and crystal phases. In addition, we explore the effect of the cross-interaction potential on the structure of the cluster crystal.
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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) | 0.000 | 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".