Bibliographic record
Abstract
The structural and dynamical properties of macromolecules in confining or crowded environments are different from those in simple bulk liquids. In this paper, both the conformational and diffusional dynamics of globular polymers are studied in solutions containing fixed spherical obstacles. These properties are studied as a function of obstacle volume fraction and size, as well as polymer chain length. The results are obtained using a hybrid scheme that combines multiparticle collision dynamics of the solvent with molecular dynamics that includes the interactions among the polymer monomers and between the polymer beads and obstacles and solvent molecules. The dynamics accounts for hydrodynamic interactions among the polymer beads and intermolecular forces with the solvent molecules. We consider polymers in poor solvents where the polymer chain adopts a compact globular structure in solution. Our results show that the collapse of the polymer chain to a compact globular state is strongly influenced by the obstacle array. A nonmonotonic variation in the radius of gyration with time is observed and the collapse time scale is much longer than that in simple solutions without obstacles. Hydrodynamic interactions are important at low obstacle volume fractions but are screened at high volume fractions. The diffusion of the globular polymer chain among the obstacles is subdiffusive in character on intermediate time scales where the dynamics explores the local structure of the heterogeneous environment. For large polymer chains in systems with high obstacle volume fractions, the chain adopts bloblike conformations that arise from trapping of portions of the chain in voids among the obstacles.
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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 | 0.001 |
| 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 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| 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 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".