Dynamic Monte Carlo Simulation of ATRP with Bifunctional Initiators
Bibliographic record
Abstract
Abstract A dynamic Monte Carlo model was developed to simulate ATRP with bifunctional initiators in a batch reactor. Model probabilities were calculated from polymerization kinetic parameters and reactor conditions. The model was used to predict monomer conversion, average molecular weight, polydispersity and the complete CLD as a function of polymerization time. The Monte Carlo model was compared with simulation results from a mathematical model that uses population balances and the method of moments. We also compared polymerizations with monofunctional and bifunctional initiators to illustrate some of the advantages of using bifunctional initiators in ATRP. In addition, we used the model to investigate the effect of the control volume and several polymerization conditions on simulation time, monomer conversion, molecular weight averages and CLD. Our results indicate that computational times can be reduced without sacrificing the quality of the results if we run several simulations with small control volumes rather than one single simulation with a large control volume. magnified image
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| 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) | 0.002 | 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".