A Molecular Weight Distribution Polydispersity Equation\nfor the ATRP System: Quantifying the Effect of Radical Termination
Bibliographic record
Abstract
Polydispersity\nquantifies the breadth of polymer molecular weight distribution, making\nit an important and frequently quoted chain microstructural property\nfor characterization. An explicit expression of such an important\nvariable is desirable for ease of calculation, correlation with experiment\ndata, and/or parameter estimation. A review of published literatures\nshows that great efforts have been put forth by many researchers to\nderive these equations for various polymerization mechanisms. In atom\ntransfer radical polymerization (ATRP), polydispersity depends on\nthree factors: monomer conversion, number of monomer addition per\nactivation/deactivation cycle, and amount of dead chains. The existing\nexpressions available in the literature only account for, at most,\ntwo of these three factors, with the contribution from dead chains\ncommonly neglected. This assumption results in polydispersity monotonically\ndecreasing with conversion, which is often not observed in experiments.\nIn this work, a new equation for polydispersity, which accounts for\ncontributions of all the three aforementioned factors, is proposed.\nThe validity of assumptions involved in the derivation is evaluated\nby comparing the polydispersity profiles to those simulated by the\nmethod of moments. In addition, this new equation is used to correlate\nseveral experiment data sets for verification, namely from ATRP of\n2-hydroxyethyl methacrylate, methyl methacrylate, and <i>N</i>-isopropylacrylamide, showing better agreement than the existing\nequation. Although the equation derived here is strictly applicable\nto homogeneous (bulk and solution) normal ATRP, with further effort\nit may be extended to other types of ATRP as well as NMP and RAFT\nsystems.
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How this classification was reachedexpand
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) | 0.007 | 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 teacher head, 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".