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Record W2047039858 · doi:10.1002/app.24300

Adjustable temperature sensor with double thermoresponsiveness based on the aggregation property of binary diblock copolymers

2006· article· en· W2047039858 on OpenAlexaff
Kai Wu, Linqi Shi, Wangqing Zhang, Yingli An

Bibliographic record

VenueJournal of Applied Polymer Science · 2006
Typearticle
Languageen
FieldMaterials Science
TopicConducting polymers and applications
Canadian institutionsUniversité de Montréal
Fundersnot available
KeywordsCopolymerEthylene glycolPEG ratioLower critical solution temperaturePolymer chemistryMaterials scienceChemical engineeringPolymer

Abstract

fetched live from OpenAlex

Abstract This article presents a new and promising way to design a temperature sensor, which is based on the micellization or aggregation behavior of binary diblock copolymers of poly(ethylene glycol)‐ b ‐poly( N ‐isopropylacrylamide) (PEG‐ b ‐PNIPAM) and poly(ethylene glycol)‐ b ‐poly(4‐vinylpyridine) (PEG‐ b ‐P(4‐VP)). The temperature sensor presents both a lower critical response temperature (LCRT) and an upper critical response temperature (UCRT), where the thermoreversible aggregating of PEG‐ b ‐P(4‐VP) and H 2 SO 4 is used to control the LCRT, and the thermoreversible micellization of PEG‐ b ‐PNIPAM is used to control the UCRT. Furthermore, the LCRT can be altered by changing the H 2 SO 4 concentration, and the UCRT can be adjusted by altering the PEG‐ b ‐PNIPAM concentration. © 2006 Wiley Periodicals, Inc. J Appl Polym Sci 102: 3144–3148, 2006

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 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 score0.004
Threshold uncertainty score0.370

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.011
GPT teacher head0.225
Teacher spread0.213 · 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

Citations12
Published2006
Admission routes1
Has abstractyes

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