Chain Length and Grafting Density Dependent Enhancement in the Hydrolysis of Ester-Linked Polymer Brushes
Bibliographic record
Abstract
Poly(N,N-dimethylacrylamide) (PDMA) brushes with different grafting density and chain length were grown from an ester group-containing initiator using surface-initiated polymerization. Hydrolysis of the PDMA chains from the surface was monitored by measuring thickness of the polymer layer by ellipsometry and extension length by atomic force microscopy. It was found that the initial rate of cleavage of one end-tethered PDMA chains was dependent on the grafting density and chain length; the hydrolysis rate was faster for high grafting density brushes and brushes with higher molecular weights. Additionally, the rate of cleavage of polymer chains during a given experiment changed by up to 1 order of magnitude as the reaction progressed, with a distinct transition to a lower rate as the grafting density decreased. Also, polymer chains undergo selective cleavage, with longer chains in a polydisperse brush being preferentially cleaved at one stage of the hydrolysis reaction. We suggest that the enhanced initial hydrolysis rates seen at high grafting densities and high chain lengths are due to mechanical activation of the ester bond connecting the polymer chains to the surface in association with high lateral pressure within the brush. These results have implications for the preparation of polymers brushes, their stability under harsh conditions, and the analysis of polymer brushes from partial hydrolysates.
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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 | 0.001 | 0.000 |
| 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 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".