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Record W2774216140 · doi:10.1021/acs.iecr.7b04135

TEMPO-Oxidized Waste Cellulose as Reinforcement for Recycled Fiber Networks

2017· article· en· W2774216140 on OpenAlexafffund
Lei Dai, Jie Chen, Bo Yang, Yanqun Su, Le Chen, Zhu Long, Yonghao Ni

Bibliographic record

VenueIndustrial & Engineering Chemistry Research · 2017
Typearticle
Languageen
FieldMaterials Science
TopicAdvanced Cellulose Research Studies
Canadian institutionsUniversity of New Brunswick
FundersCanada Research Chairs
KeywordsCelluloseUltimate tensile strengthPulp (tooth)Cellulose fiberRaw materialLigninFiberMaterials scienceContainer (type theory)ChemistryChemical engineeringComposite materialOrganic chemistry

Abstract

fetched live from OpenAlex

Lignocellulosic recyclable packaging material is in high demand, because of the emergence of e-commerce. Old corrugated container (OCC) pulp is the main raw material in China for manufacturing packaging boxes/bags, but its strength needs improvement. In this project, waste cellulose in the form of used printing paper was oxidized using 2,2,6,6-tetramethylpiperidine-1-oxyl radical (TEMPO) concept so that more carboxyl groups were introduced. The TEMPO-oxidized waste cellulose (TOWC) having a carboxyl content of 1.451 mmol/g was then used as reinforcement for the OCC fiber networks. The TOWC addition to the OCC fiber networks at different mass ratios of 5%, 10%, and 15% on its strength properties was studied. The results showed that the addition of TOWC remarkably improved the tensile and other strength properties, which can be explained by the improved hydrogen bonding and interpenetrating capacity of fiber networks, thanks to the increased carboxyl groups and fibrillation after the TEMPO oxidation.

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)0.003
metaresearch head score (Gemma)0.008
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
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 score0.057
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.008
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0020.001
Research integrity0.0000.001
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 head0.106
GPT teacher head0.375
Teacher spread0.269 · 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

Citations13
Published2017
Admission routes2
Has abstractyes

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