MétaCan
Menu
Back to cohort
Record W2013453250 · doi:10.1021/la046962r

An NMR Study of Translational Diffusion and Structural Anisotropy in Magnetically Alignable Nonionic Surfactant Mesophases

2005· article· en· W2013453250 on OpenAlexaff
Anand Yethiraj, Donatella Capitani, Nicholas E. Burlinson, E. Elliott Burnell

Bibliographic record

VenueLangmuir · 2005
Typearticle
Languageen
FieldChemistry
TopicSurfactants and Colloidal Systems
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsChemistryNonionic surfactantPulmonary surfactantAnisotropyLiquid crystalDiffusionCrystallographyNuclear magnetic resonanceMaterials scienceBiochemistry

Abstract

fetched live from OpenAlex

The diffusion of both water and surfactant components in aqueous solutions of the nonionic surfactant "C12E6"--which includes hexagonal, cubic, lamellar, and micellar mesophases--has been studied by pulsed-field-gradient NMR. Diffusion coefficients were measured in unaligned samples in all of these phases. They were also obtained in the hexagonal and lamellar phases in oriented monodomain samples that were aligned by slow cooling from the micellar phase in an 11.7 T magnet. Measured water and soap diffusion coefficients in the NMR-isotropic cubic and (high-water-content) micellar phases as well as diffusion anisotropy measurements in the magnetically aligned hexagonal phase were quantitatively consistent with the constituent structures of these phases being identical surfactant cylinders, with only the fraction of surface-associated water varying with the water-soap molar ratio. The values of the water and soap diffusion coefficients in the oriented lamellar phase suggest an increase in defects and obstructions to soap diffusion as a function of increasing water content, while those in the low-water-content micellar phase rule out the presence of inverse micelles.

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)0.000
metaresearch head score (Gemma)0.000
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 score0.001
Threshold uncertainty score0.002

Distilled classifier scores by category (both heads)

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 head0.008
GPT teacher head0.249
Teacher spread0.241 · 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

Citations31
Published2005
Admission routes1
Has abstractyes

Explore more

Same venueLangmuirSame topicSurfactants and Colloidal SystemsFrench-language works237,207