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Record W2761445323 · doi:10.1002/pola.28879

Designing catechol‐end functionalized poly(DMAm‐<i>co</i>‐NIPAM) by RAFT with tunable LCSTs

2017· article· en· W2761445323 on OpenAlexafffund
Olabode O. Oyeneye, William Z. Xu, Paul A. Charpentier

Bibliographic record

VenueJournal of Polymer Science Part A Polymer Chemistry · 2017
Typearticle
Languageen
FieldChemistry
TopicAdvanced Polymer Synthesis and Characterization
Canadian institutionsWestern University
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsLower critical solution temperatureCopolymerRaftCatecholPolymer chemistryChemistryReactivity (psychology)PolymerOrganic chemistry

Abstract

fetched live from OpenAlex

ABSTRACT Providing catechol‐end functionality to controlled structure lower critical solution temperature (LCST) copolymers is attractive, given the versatility of catechol chemistry for tethering to nanostructures. Controlled polymer chain lengths with catechol RAFT end groups are of interest to provide tunable LCST behavior to nanoparticles, although these polymerizations are relatively unexplored. Herein, the reactivity ratios for the RAFT copolymerization of N,N ‐dimethylacrylamide (DMAm) and N ‐isopropylacrylamide (NIPAM) pairs based on catechol‐end RAFT agents using an in situ NMR technique were first determined. Several catechol‐end poly(DMAm‐ co ‐NIPAM) samples were then prepared using the RAFT agent to provide copolymer. The reactivity ratios for the DMAm‐NIPAM pair were r DMAm = 1.28–1.31 and r NIPAM = 0.48–0.51. All the poly(DMAm‐ co ‐NIPAM) samples were found to have M n values ≤ 26 kDa and Ð &lt; 1.08 with LCST values ranging from 31 to 92°C, while maintaining a short range of glass transition temperature ( T g = 118–137°C). The difference in LCST values for the catechol functionalized poly(DMAm‐ co ‐NIPAM) based on 0.5 wt% aqueous buffered solutions at pH 5.5 and 8.5 was found to be &lt;3.0°C. These conditions are suitable for subsequent catechol‐induced coordination and nucleophilic addition chemistry for covalent and noncovalent linkages during subsequent post‐modification. © 2017 Wiley Periodicals, Inc. J. Polym. Sci., Part A: Polym. Chem. 2017 , 55 , 4062–4070

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.056
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0020.002
Scholarly communication0.0010.002
Open science0.0020.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0050.000

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.

Opus teacher head0.013
GPT teacher head0.259
Teacher spread0.245 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designBench or experimental
Domainnot available
GenreEmpirical

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".

Quick stats

Citations7
Published2017
Admission routes2
Has abstractyes

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