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MORPHOLOGICAL, PHYSICAL AND THERMAL CHARACTERIZATION OF MICROFIBRILLATED CELLULOSE

2018· article· en· W2885428991 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

VenueRevista Árvore · 2018
Typearticle
Languageen
FieldMaterials Science
TopicAdvanced Cellulose Research Studies
Canadian institutionsUniversity of Waterloo
Fundersnot available
KeywordsPulp (tooth)Zeta potentialCrystallinityCelluloseMaterials scienceCellulose fiberCellulosic ethanolComposite materialPulp and paper industryChemical engineeringFiberNanotechnology

Abstract

fetched live from OpenAlex

ABSTRACT The aim of this study was to characterize microfibrillated cellulose (MFC) produced with a Masuko Sangyo Super Masscolloider using bleached and unbleached pulp of Eucalyptus spp. The MFC was characterized regarding morphology (TEM), crystallinity, viscosity, zeta potential and thermal properties (TGA). Regardless of the fiber type, the processing dramatically reduced the dimensions of the material, so as to obtain structures with nanometric dimensions. MFC produced with unbleached pulp preserved the original brown color of the pulp, which may be advantageous for some applications in the packaging sector, while films produced with bleached pulp were more translucent. The MFC showed lower values of viscosity and crystallinity index in relation to cellulosic pulp. The zeta potential was influenced by the type of fiber used. The main thermal transitions in MFC occurred after 200 ºC, demonstrating the potential of this material forhigh-temperature applications.

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)0.000
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 score0.010
Threshold uncertainty score0.346

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 head0.020
GPT teacher head0.288
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