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Record W2063281067 · doi:10.1021/ma0213605

NMR Self-Diffusion of Molecular and Macromolecular Species in Dextran Solutions and Gels

2003· article· en· W2063281067 on OpenAlexafffund
Sungjong Kwak, Michel Lafleur

Bibliographic record

VenueMacromolecules · 2003
Typearticle
Languageen
FieldPhysics and Astronomy
TopicNMR spectroscopy and applications
Canadian institutionsUniversité de Montréal
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsDextranMicelleDiffusionPulsed field gradientChemistrySelf-diffusionSelf-healing hydrogelsMacromoleculeMolecular diffusionChemical engineeringChromatographyMoleculeAqueous solutionPolymer chemistryThermodynamicsPhysical chemistryOrganic chemistryBiochemistry

Abstract

fetched live from OpenAlex

To provide insights into the diffusion properties of micelles in hydrogels and, in general, of solutes in dextran gels, self-diffusion coefficients of small organic solutes and large micelles were measured in dextran solutions and gels, using pulsed-field gradient NMR. The self-diffusion of the solutes was shown to be slower in dextran solutions than in D 2 O and even slower in dextran gels. The extent of the diffusion reduction was more pronounced for higher dextran concentrations. For a series of molecules with a molecular weight between 46 and 78, the self-diffusion coefficient in dextran gels (20% w/w) corresponded, on average, to about 0.39 of the values measured in bulk water. This hindered diffusion was mainly associated with the obstacles created by the polysaccharide segments. There was no evidence in the diffusion measurements of interaction between dextran and solutes capable of hydrogen bonding. The reduction of diffusion in dextran solutions and gels was very drastic in the case of micelles. For Triton X-100, the self-diffusion coefficient in dextran gel was about 7% of that observed in water. The values were, in fact, on the same order of the dextran chain diffusion coefficient. This finding suggests that these large macroassemblies can hardly move in dextran gels.

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 score0.330
Threshold uncertainty score0.644

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 head0.254
Teacher spread0.247 · 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

Citations32
Published2003
Admission routes2
Has abstractyes

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