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Record W4366825719 · doi:10.3390/colloids7020036

Rheology of Pickering Emulsions Stabilized and Thickened by Cellulose Nanocrystals over Broad Ranges of Oil and Nanocrystal Concentrations

2023· article· en· W4366825719 on OpenAlexaff
Saumay Kinra, Rajinder Pal

Bibliographic record

VenueColloids and Interfaces · 2023
Typearticle
Languageen
FieldMaterials Science
TopicAdvanced Cellulose Research Studies
Canadian institutionsUniversity of Waterloo
Fundersnot available
KeywordsCreamingRheologyConsistency indexEmulsionChemical engineeringNanocelluloseShear thinningNanocrystalline materialMaterials scienceNanocrystalCelluloseAqueous solutionPickering emulsionChemistryComposite materialOrganic chemistryNanotechnology

Abstract

fetched live from OpenAlex

The rheology of oil-in-water (O/W) emulsions, stabilized and thickened by cellulose nanocrystals, also referred to as nanocrystalline cellulose (NCC), was investigated over broad ranges of NCC and oil concentrations. The NCC concentration was varied from 1.03 to 7.41 wt% based on the aqueous phase. The oil concentration of the emulsion was varied from approximately 10 to 70 wt%. The emulsions produced were highly stable with respect to creaming and coalescence. The emulsions were non-Newtonian in that they exhibited strong shear-thinning behavior. The rheological data were described adequately by a power-law model. The consistency index (K) and the flow behavior index (n) of the emulsions were strongly dependent on the NCC and oil concentrations. At a fixed oil concentration, the consistency index increased whereas the flow behavior index decreased with the increase in NCC concentration. A similar behavior was observed when the NCC concentration was fixed and the oil concentration was increased; that is, the consistency index increased whereas the flow behavior index decreased.

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 score0.002
Threshold uncertainty score0.469

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 studies0.0000.001
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 head0.015
GPT teacher head0.284
Teacher spread0.268 · 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
Published2023
Admission routes1
Has abstractyes

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