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Record W3197035865 · doi:10.1021/acs.macromol.1c00952

Making Hydrophilic Polymers Thermoresponsive: The Upper Critical Solution Temperature of Copolymers of Acrylamide and Acrylic Acid

2021· article· en· W3197035865 on OpenAlexafffund
Guillaume Beaudoin, Anne Lasri, Chuanzhuang Zhao, Benoît Liberelle, Grégory De Crescenzo, X. X. Zhu

Bibliographic record

VenueMacromolecules · 2021
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicHydrogels: synthesis, properties, applications
Canadian institutionsPolytechnique MontréalUniversité de Montréal
FundersCanada First Research Excellence FundNatural Sciences and Engineering Research Council of CanadaCanada Research Chairs
KeywordsUpper critical solution temperatureCopolymerAcrylic acidMolar massLower critical solution temperaturePolymer chemistryAcrylamideHydrogen bondChemistryPolymerCarboxylic acidProtonationChemical engineeringOrganic chemistryMolecule

Abstract

fetched live from OpenAlex

Homopolymers of acrylamide and acrylic acid are known to be hydrophilic and soluble in water. Their copolymers are soluble in water at neutral pH but can be turned into polymers possessing an upper critical solution temperature (UCST) behavior when the carboxylic acid groups are protonated (pH < 3). At temperatures below the UCST, the formation of interchain hydrogen bonds between the acid and amide groups makes the copolymers insoluble. These hydrogen bonds are disrupted when the temperature is heated above the critical temperature (Tc), exhibiting a UCST behavior. In this study, linear water-soluble random copolymers of acrylamide and acrylic acid of different compositions and molar masses have been synthesized. The thermoresponsive properties of the copolymers were studied to elucidate the effects of their composition, molar mass, and concentration by measuring their cloud point temperatures (Tcp) in acidic buffer solutions to keep the carboxylic acid groups in the protonated state. The effects of pH and added salts or urea were also studied.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
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 score0.014
Threshold uncertainty score0.564

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.014
GPT teacher head0.268
Teacher spread0.254 · 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.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations47
Published2021
Admission routes2
Has abstractyes

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