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Record W2008791643 · doi:10.1002/cjce.20382

Use of zeolites in stabilising alkaline peroxide solutions and their application in the bleaching of a TMP pulp

2010· article· en· W2008791643 on OpenAlexvenueno aff
Moses Wekesa, Yonghao Ni

Bibliographic record

VenueThe Canadian Journal of Chemical Engineering · 2010
Typearticle
Languageen
FieldEngineering
TopicMetal Extraction and Bioleaching
Canadian institutionsnot available
Fundersnot available
KeywordsPeroxideSilicateDecompositionChemistryHydrogen peroxideAlkali metalSodium silicateManganeseInorganic chemistryChemical engineeringOrganic chemistry

Abstract

fetched live from OpenAlex

Abstract Silicate‐based chemistry is a common industrial practice to improve peroxide bleaching, however, the transition metal ion‐induced peroxide decomposition is still inevitable. In this study, we investigated the potential to further decrease the peroxide decomposition by adding zeolites to the silicate‐based peroxide system. The peroxide decomposition results showed that the combined effect of zeolites and sodium silicate is more effective than sodium silicate alone in decreasing the manganese‐induced peroxide decomposition. Two types of zeolites, X and Y, were studied. The bleaching experiments showed that an improved peroxide bleaching performance was obtained by adding Y‐zeolites to the conventional peroxide process.

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)0.000
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.545
Threshold uncertainty score0.382

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 integrity0.0000.001
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 head0.016
GPT teacher head0.197
Teacher spread0.181 · 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

Citations3
Published2010
Admission routes1
Has abstractyes

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