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Record W3009399591 · doi:10.1038/s41598-020-60507-3

Comparison Of Mechanical And Chemical Nanocellulose As Additives To Reinforce Recycled Cardboard

2020· article· en· W3009399591 on OpenAlexaff
José Luis Sanchez-Salvador, Ana Balea, M. Concepción Monte, Carlos Negro, Meaghan Miller, James A. Olson, Ángeles Blanco

Bibliographic record

VenueScientific Reports · 2020
Typearticle
Languageen
FieldMaterials Science
TopicAdvanced Cellulose Research Studies
Canadian institutionsUniversity of British Columbia
FundersMinisterio de Economía y CompetitividadUniversidad Complutense de MadridInstituto Nacional de Investigación y Tecnología Agraria y Alimentaria
KeywordsNanocelluloseSoftwoodPulp (tooth)Materials scienceKraft processKraft paperPulp and paper industryCelluloseComposite materialcardboardFlocculationPapermakingStarchNanofiberUltimate tensile strengthChemistryOrganic chemistry

Abstract

fetched live from OpenAlex

Recycling cycles cause a decrease in mechanical paper properties due to cellulose fiber degradation. The use of cellulose micro/nanofibers (CMF/CNF) to reinforce paper strength has been well studied, although it has been found to have negative effects on drainage. However, the application of CMF/CNF as paper reinforcement is affected by the nanocellulose type. Thus in this study mechanical and chemical treatments in CNF production were compared. Old corrugated container (OCC) pulp used to produce recycled cartonboard was reinforced with 1) CMF from never-dried northern bleached softwood kraft pulp (NBSK) highly refined in a 16-inch low consistency refiner at 1200 rpm and 25 kW of net power; and 2) CNF from NBSK pulp treated by TEMPO-mediated oxidation and homogenization at 600 bars. CMF/CNF and OCC were pulped at the same time and handsheets formed with cationic starch (CS) as retention system. Mechanical, drainage and flocculation properties were evaluated and compared. Data were also compared with other sources of TEMPO CNF. Results show an improvement in mechanical properties, drainage and flocculation when OCC is reinforced with CMF obtained with LCR. Therefore, high fibrillation was not necessary to improve mechanical paper or cardboard properties.

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)0.002
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 score0.016
Threshold uncertainty score0.619

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.002
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 science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.037
GPT teacher head0.333
Teacher spread0.296 · 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

Citations79
Published2020
Admission routes1
Has abstractyes

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