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Record W4237404146 · doi:10.15376/biores.7.1.99-111

A comparison between the effects of ozone and alkaline peroxide treatments on TMP properties and subsequent low consistency refining

2011· article· en· W4237404146 on OpenAlexafffund
Xue Feng Cheng, James A. Olson, Rodger P. Beatson

Bibliographic record

VenueBioResources · 2011
Typearticle
Languageen
FieldMaterials Science
TopicAdvanced Cellulose Research Studies
Canadian institutionsBritish Columbia Institute of TechnologyUniversity of British Columbia
FundersNatural Sciences and Engineering Research Council of CanadaOntario Power AuthorityCentre for Energy Advancement through Technological InnovationBC Hydro
KeywordsOzonePeroxidePulp (tooth)Ultimate tensile strengthRefining (metallurgy)Pulp and paper industryMaterials scienceChemistryComposite materialOrganic chemistryMetallurgyDentistry

Abstract

fetched live from OpenAlex

As part of a program to reduce electrical energy consumption in the refining process, the effects of the ozone and alkaline peroxide treatments on fibre and handsheet properties, prior and subsequent to low consistency (LC) refining, were assessed and compared by applying different levels of ozone and a range of peroxide and alkali charges to a primary stage hemlock thermomechanical pulp (TMP). Both highly alkaline peroxide treatments and ozone treatments decreased the specific energy required for strong mechanical pulp. The improvement in pulp strength through alkaline peroxide treatment mainly resulted from pulp surface changes caused by generation of acid groups. The highly alkaline peroxide treatments significantly increased pulp brightness but did not promote the further fibrillation during the subsequent LC refining. On the other hand, ozone treatments provided tensile strength increases, along with small brightness enhancements for the dark hemlock TMP, and increased the tensile gains obtained through LC refining. The effects of ozone treatments on tensile strength before and after LC refining were the result of pulp surface modifications, fibre swelling, and loss of fibre wall integrity due to non-selective chemical attack. High levels of ozone treatment caused tear strength to decrease during subsequent LC refining.

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)0.000
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 score0.033
Threshold uncertainty score0.335

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 head0.082
GPT teacher head0.293
Teacher spread0.211 · 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

Citations9
Published2011
Admission routes2
Has abstractyes

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