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Record W2983847153 · doi:10.1515/npprj-2019-0027

Optimization of the process variables for treating cellulose fiber with NaOH/urea aqueous solution for improved water retention value and paper strength

2019· article· en· W2983847153 on OpenAlexaff
Yingju Miao, Chunzuo Yan, Yingchun Miao, Qingming Jia, Yonghao Ni, Tingcong Sun, Shaozhong Han

Bibliographic record

VenueNordic Pulp & Paper Research Journal · 2019
Typearticle
Languageen
FieldMaterials Science
TopicAdvanced Cellulose Research Studies
Canadian institutionsUniversity of New Brunswick
FundersKey Supported Discipline of Guizhou ProvenceNational Natural Science Foundation of China
KeywordsUreaSodium hydroxideAqueous solutionUltimate tensile strengthSwellingCelluloseMaterials scienceNuclear chemistryFiberPulp (tooth)SodiumAnalytical Chemistry (journal)ChemistryComposite materialChromatographyOrganic chemistryMetallurgy

Abstract

fetched live from OpenAlex

Abstract Cellulose fibers swell significantly in NaOH/urea solutions, and swelling increases with a decrease in temperature and an addition of urea. The combined effects of the factors of a pretreatment procedure (sodium hydroxide concentration, urea concentration, temperature, and time) and post-treatment conditions (medium, stirring speed, and time) of preparing fibers on the properties of pulp and the resulting paper sheets were investigated and optimized using single factor experiments. The optimum sodium hydroxide concentration (1 %), urea concentration (8 %), precooling temperature 0 °C, pretreatment time (12 h), post-treatment medium (7 % ( NH 4 ) 2 SO 4 {({\mathrm{NH}_{4}})_{2}}{\mathrm{SO}_{4}} ), post-treatment stirring speed (1500 rpm), and time (30 min) were obtained. Under the optimal conditions, the water retention values and tear, tensile, and burst indexes increased about 54 %, 277 %, 394 %, and 98 %, respectively. This work demonstrates that this technical route can effectively improve fiber swelling capacity and paper strength.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.001
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0000.000
Research integrity0.0010.001
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 head0.023
GPT teacher head0.313
Teacher spread0.290 · 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 source (direct Gemma or distilled Codex), 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

Citations1
Published2019
Admission routes1
Has abstractyes

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