Phase behavior of blocky charge lattice polymers: Crystals, liquids, sheets, filaments, and clusters
Bibliographic record
Abstract
Motivated by the idea that intrinsically disordered proteins (IDPs) condense into liquidlike droplets within cells, we carry out Monte Carlo simulations of a polymer lattice model to study the relationship between charge patterning and phase separation. Polymer chains containing neutral, positively charged, and negatively charged monomers are placed on a cubic lattice. Only nearest-neighbor interactions between charges are considered. We determine the phase diagram for a systematically varied set of sequences. We observe homogeneous fluids, liquid condensation, cluster phases, filaments, and crystal states. Of the six sequences we study, three form crystals at low temperatures. The other three sequences, which have lower charge densities, instead collapse into gel-like networks or unconnected finite clusters. Longer neutral patches along the sequence sterically limit the size and shape of low-energy structures, which is analogous to the effect of charge or limited valence in attractive colloids. Only one sequence clearly exhibits liquid behavior; this sequence has a reduced tendency to individually fold and crystallize compared to others of similar charge density and draws parallels to real IDP behavior.
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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".