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Record W4387140622 · doi:10.3390/coatings13101705

Nanocellulose Coating on Kraft Paper

2023· article· en· W4387140622 on OpenAlexaff
Elaine Cristina Lengowski, Eraldo Antonio Bonfatti Júnior, Leonardo C. Simon, Graciela Inês Bolzón de Muñiz, Alan Sulato de Andrade, Aleffe Neves Leite, Emilly Laize Souza de Miranda Leite

Bibliographic record

VenueCoatings · 2023
Typearticle
Languageen
FieldMaterials Science
TopicAdvanced Cellulose Research Studies
Canadian institutionsUniversity of Waterloo
FundersFundação de Amparo à Pesquisa do Estado de Mato Grosso
KeywordsNanocelluloseMaterials scienceCoatingUltimate tensile strengthComposite materialKraft paperPulp (tooth)Coated paperPorosityKraft processThermal stabilityCelluloseTear resistanceFood packagingChemical engineeringChemistry

Abstract

fetched live from OpenAlex

Paper is a biodegradable material, but in food packaging, its hygroscopicity and porosity can cause food contamination due to the exchange of gasses and liquids with the environment. Therefore, it is important to use biodegradable materials for paper coatings, such as nanocellulose, which is chemically compatible with paper but less hygroscopic. The objective of this study was to evaluate the effectiveness of nanofibrillated cellulose (NFC) as a paper coating. NFC produced from bleached eucalyptus pulp was used as a coating on kraft paper sheets produced from Pinus pulp. To prepare the coating, two thicknesses of wet nanocellulose (1 mm and 2 mm) were tested, and two nanocellulose films made with the same thicknesses were evaluated. The morphological, physical, mechanical, and thermal properties of the composites were investigated. The presence of NFC improved the surface of the paper by filling the pores; consequently, the density and barrier properties were also improved. All mechanical properties were improved, with the highest increases observed for bursting and tensile strength; however, the films showed low bursting index values and null values for the tearing index. The thermal stability of the paper with NFC coatings met the minimum requirements for food packaging.

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)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
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 score0.018
Threshold uncertainty score0.995

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
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)0.0010.005

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 head0.034
GPT teacher head0.307
Teacher spread0.274 · 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.

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

Citations19
Published2023
Admission routes1
Has abstractyes

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