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Record W2068840980 · doi:10.1021/la049955b

Preparation, Characterization, and Solution Viscosity of Polystyrene-<i>block</i>-polyisoprene Nanofiber Fractions

2004· article· en· W2068840980 on OpenAlexaff
Xiaohu Yan, Guojun Liu, Hexian Li

Bibliographic record

VenueLangmuir · 2004
Typearticle
Languageen
FieldChemistry
TopicAdvanced Polymer Synthesis and Characterization
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsCyclohexaneTetrahydrofuranPolystyreneSolventPolymer chemistryIntrinsic viscosityMicelleChemistryDimethylacetamidePersistence lengthPolymerAnalytical Chemistry (journal)Materials scienceAqueous solutionOrganic chemistry

Abstract

fetched live from OpenAlex

A polystyrene-block-polyisoprene (PS-b-PI) sample with 130 styrene and 370 isoprene units was synthesized and characterized. The diblock formed mostly cylindrical micelles in N,N-dimethylacetamide with a PI core and a PS corona. The PI core of the micelles was cross-linked by S2Cl2 to yield nanofibers. The nanofibers were shortened by ultrasonication to yield fractions withweight-average length (Lw) between approximately 900 and approximately3400 nm. Transmission electron microscopy and light scattering were used to characterize the fractions. The zero-shear intrinsic viscosity data [eta] of the fractions were obtained in tetrahydrofuran (THF), THF/N,N-dimethylformamide (DMF), and THF/cyclohexane (CHX), where THF is a good solvent for both the corona and the core, DMF solubilizes only the corona, and CHX is a theta solvent for the corona chains at 34.5 degrees C. The [eta] data of the fractions were treated by the Bohdanecky method derived from the Yamakawa-Fujii-Yoshizaki (YFY) theory for wormlike polymer chains and yielded the persistence length lP and the hydrodynamic diameters dh for the nanofibers. The reasonable dh values and the reasonable trend of dh variation with solvent quality change establish unambiguously the validity of YFY theory.

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 score0.025
Threshold uncertainty score0.552

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 studies0.0000.000
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 head0.007
GPT teacher head0.237
Teacher spread0.230 · 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

Citations36
Published2004
Admission routes1
Has abstractyes

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