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Record W2027654986 · doi:10.1002/app.11164

Comparison of various solvents for determination of intrinsic viscosity and viscometric constants for cellulose

2002· article· en· W2027654986 on OpenAlexaff
Mohammad Reza Kasaai

Bibliographic record

VenueJournal of Applied Polymer Science · 2002
Typearticle
Languageen
FieldMaterials Science
TopicAdvanced Cellulose Research Studies
Canadian institutionsUniversité Laval
Fundersnot available
KeywordsIntrinsic viscosityCelluloseViscositySolventDissolutionChemistryPolymerReduced viscosityReaction rate constantThermodynamicsPolymer chemistryAnalytical Chemistry (journal)Organic chemistryKinetics

Abstract

fetched live from OpenAlex

Abstract Different solvents used to determine the intrinsic viscosity and the viscometic constants, a and K, published in the literature for cellulose, were compared. The various parameters affecting the viscometric constants were also evaluated. The main conclusions obtained from the experimental data available in the literature are that (1) the intrinsic viscosities in various solvents are ordered as follows: [η]LiCl/DMAc > [η]NH3/NH4SCN ≥ [η]FeTNa > [η]CED > [η]Cadoxen > [η]Cuoxam; (2) the reported intrinsic viscosities and molecular weights for cellulose are lower than the true value due to degradation of cellulose in the solvents; (3) the rate of degradation was the smallest in LiCl/DMAc and NH3/NH4SCN, moderate in cadoexn and FeTNa, and the highest in CED and cuoxam; (4) the plot of log K versus exponent a was linear and inversely related; (5) the curve was used for estimation of the constant K for cellulose in a solvent (NH3/NH4SCN) with a known exponent a; and (6) among various reported solvents, LiCl/DMAc and NH3/NH4SCN are advantageous over other solvents because of a complete dissolution of the polymer with a negligible reduction in its intrinsic viscosity. © 2002 Wiley Periodicals, Inc. J Appl Polym Sci 86: 2189–2193, 2002

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.007
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.003
Threshold uncertainty score0.013

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.007
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0030.003
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.001

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 head0.045
GPT teacher head0.345
Teacher spread0.300 · 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 source (direct Gemma or distilled Codex), 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

Citations56
Published2002
Admission routes1
Has abstractyes

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