Visualization of Bivariate Sequence Length–Chain Length Distribution in Free Radical Copolymerization
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Bibliographic record
Abstract
Copolymer properties and processability depend on copolymer microstructure, i.e., copolymer composition and monomer unit arrangements along the copolymer chains. To predict the ultimate properties of copolymers, one needs complete information on the length and position of sequences of each monomer type in every chain. A versatile kinetic Monte Carlo code is developed and applied for the simulation of typical free radical copolymerizations. The code allows explicit monitoring of every growing chain during the course and at the end of polymerization, can account for comonomer systems of any arbitrary reactivity ratios ( r 1 and r 2 ) over the full range of monomer composition. Meanwhile, it eliminates the need for solving arrays of differential equations arising from deterministic modeling approaches. Since the code virtually synthesizes billions of copolymer molecules and keeps in storage information on each and every copolymer chain in the system, it allows for detailed statistical analysis. The simulator visualizes the bivariate sequence length–chain length distribution for typical copolymerization systems and examples with: r 1 < 1 and r 2 < 1; r 1 > 1 and r 2 < 1; ( r 1 × r 2 ) = 1; and r 1 = r 2 = 1, and is also applied successfully to an experimental scenario described in the literature.
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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 | 0.001 |
| 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 | 0.000 |
| 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 it