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Record W2372459288

Kinetic study on thermal decomposition of flax fibers with model-free and Coats-Redfern model fitting kinetic approaches

2010· article· en· W2372459288 on OpenAlexaff
Guiying Xu, Sun Guogang

Bibliographic record

VenueHuagong xuebao · 2010
Typearticle
Languageen
FieldEngineering
TopicThermochemical Biomass Conversion Processes
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsActivation energyKinetic energyThermal decompositionDecompositionThermodynamicsMaterials scienceAtmospheric temperature rangeKineticsRange (aeronautics)Raw materialChemistryPhysical chemistryComposite materialOrganic chemistryPhysics
DOInot available

Abstract

fetched live from OpenAlex

TG analysis was used to investigate the thermal decomposition of flax fibers which are a potential gasification feedstock.10 mg flax shive samples with the particles between 0.60 and 0.85 mm was linearly heated to 550℃ at heating rates of 10,20,30,50 K·min-1,respectively,under high-purity nitrogen.Coats-Redfern model fitting method and model-free methods include Kissinger method and three isoconversional methods(Friedman,Flynn-wall-Ozawa,Vyazovkin and Wight methods)were used to estimate the apparent activation energy of the fax fibers.With the three isoconversional methods,it can be concluded that the activation energy increases with increasing conversion.The four model free methods indicated activation energies in the range of 155—175 kJ·mol-1.Activation energies by Coats-Redfern model fitting method was about 175 kJ·mol-1,close to the values by model free method.These activation energy values provide the basic data for the thermo-chemical utilization of the flax fibers.

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 score0.003
Threshold uncertainty score0.006

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 communication0.0000.001
Open science0.0010.000
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 head0.019
GPT teacher head0.214
Teacher spread0.195 · 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

Citations6
Published2010
Admission routes1
Has abstractyes

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