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Record W2003771764 · doi:10.1515/hf.2005.016

Cellulose microfibrils: A novel method of preparation using high shear refining and cryocrushing

2004· article· en· W2003771764 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueHolzforschung · 2004
Typearticle
Languageen
FieldMaterials Science
TopicAdvanced Cellulose Research Studies
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsBiocompositeMaterials scienceCellulosePolymerComposite materialPolylactic acidShearing (physics)FibrilOptical microscopeMicrofibrilChemical engineeringScanning electron microscopeChemistryComposite number

Abstract

fetched live from OpenAlex

Abstract This paper describes a novel technique to produce cellulose microfibrils through mechanical methods. The technique involved a combination of severe shearing in a refiner, followed by high-impact crushing under liquid nitrogen. Fibers treated in this way were subsequently either freeze-dried or suspended in water. The fibers were characterized using SEM, TEM, AFM, and high-resolution optical microscopy. In the freeze-dried batch, 75% of the fibrils had diameters of 1 μm and below, whereas in the water dispersed batch, 89% of the fibrils had diameters in this range. The aspect ratio of the microfibrils ranged between 15 and 55 for the freeze-dried fibrils, and from 20 to 85 for the fibrils dispersed in water. These measurements suggest that the microfibrils have the potential to produce composites with high strength and stiffness for high-performance applications. The microfibrils in water were compounded with polylactic acid polymer to form a biocomposite. Laser confocal microscopy showed that the microfibrils were well dispersed in the polymer matrix.

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.

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)0.001
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 score0.154
Threshold uncertainty score0.682

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
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 head0.049
GPT teacher head0.358
Teacher spread0.309 · 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