Controlling structure of materials derived from spinodally decomposing liquids
Bibliographic record
Abstract
Arresting morphological evolution of spinodally decomposing heterogeneous mixtures via the addition of colloidal particles has resulted in the discovery of new classes of bicontinuous materials, viz., bicontinuous interfacially jammed emulsion gels (bijels) and most recently bicontinuous intraphase jammed emulsion gels (bipjels). Here, we demonstrate how the extent of particle wettability and particle–particle interactions govern the ultimate structure formed. We present the multi-phase lattice Boltzmann method (LBM) integrated with a discrete particle model with two particle–particle collision models, the classic hard-sphere model and a new bonding collision model, to predict the final state of spinodally decomposing fluid mixtures containing solid particles. We show that the elastic collision model yields either the formation of emulsions or bijels, while only the bonding collision model on particles with preferential wettability for one phase can predict bipjels formation. In the case of bipjels, a delicate balance between the dynamics of evolving interface and the strength of particle–particle aggregates is required to restrict the interfacial motion. These results are consistent with experimental findings, suggesting that the presence of smaller particles with high particle–particle interactions can yield the formation of bipjels and consequent isolation of hierarchically porous materials.
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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".