Efficient Modeling of High-Generation Dendrimers in Solution Using Dynamical Self-Consistent Field Theory
Bibliographic record
Abstract
We extend dynamical self-consistent field theory (dSCFT) to large, nonlinear polymer chains to simulate the evolution of high-generation dendrimers in a solvent. Because the number of beads N within these bead–spring dendrimers is very large, we introduce a numerical technique to efficiently analyze the Rouse modes of the dendrimer through a decomposition of the dendrimer into many smaller subchains, achieving a significant improvement, from O ( N 2 ) to O ( N ), in the scaling of the simulation time for the Rouse motion of the dendrimer. By adjusting the strength of the interaction between dendrimer and solvent beads, we obtain qualitative and quantitative agreement with the core-chain morphology, 22 nm radius, and high degree of hydration measured experimentally using small-angle neutron scattering for 11-generation, glucose-based phytoglycogen dendrimers in water, validating dSCFT in this context.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".