Kinetic Prediction of Functional Group Distributions in Thermosensitive Microgels
Bibliographic record
Abstract
A kinetic model accounting for the copolymerization of up to four comonomers is applied to predict both chain and radial functional group distributions in carboxylic-acid-functionalized poly(N-isopropylacrylamide) (NIPAM)-based microgels. The model can accurately predict the experimentally observed radial distributions of functional monomers in microgels prepared using a variety of different carboxylic-acid-functionalized monomers with significantly different hydrophobicities, copolymerization kinetics, and reactivities, without requiring the use of adjustable parameters. Multimodal distributions can both be predicted and experimentally generated by copolymerizing two -COOH-containing monomers with widely different reactivities. Chain distributions and monomer block formation can also be probed using the kinetic model, allowing for qualitative predictions of the potentiometric titration behavior of the microgels. The kinetic model reported herein therefore provides the first available analytical method for semiquantitatively predicting and controlling functional group distributions in bulk-polymerized microgel systems.
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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) | 0.001 | 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 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".