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Record W4408503677 · doi:10.1002/cjce.25669

Study of potassium salts on sawdust pyrolysis: Kinetics and thermodynamic parameters using isoconversional and Criado's master plot methods

2025· article· en· W4408503677 on OpenAlexafffundvenue
Milad Ja Lilian, Quan He, Yulin Hu

Bibliographic record

VenueThe Canadian Journal of Chemical Engineering · 2025
Typearticle
Languageen
FieldEngineering
TopicThermochemical Biomass Conversion Processes
Canadian institutionsDalhousie UniversityUniversity of Prince Edward Island
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsSawdustThermogravimetric analysisEnthalpyGibbs free energyPyrolysisActivation energyChemistryPotassium carbonatePotassiumThermodynamicsKineticsMaterials scienceNuclear chemistryOrganic chemistry

Abstract

fetched live from OpenAlex

Abstract In this study, the effect of potassium salts on sawdust pyrolysis with respect to kinetics and thermodynamic parameters was investigated. Kinetic triplet (activation energy, pre‐exponential factor, and reaction mechanism) and thermodynamic properties (enthalpy change, entropy change, and Gibbs free energy) were determined using isoconversional and Criado's master plot methods, respectively. Thermogravimetric analysis (TGA) was carried out in N 2 environment at 5, 25, and 50°C/min from 30 to 800°C. A series of analytical techniques were utilized to fully characterize the raw materials. Analysis of TGA data was performed using isoconversional model. The results suggested that the addition of potassium carbonate showed catalytic effect on the thermal degradation of sawdust by affecting the kinetic triplets and thermodynamic properties. However, the presence of potassium chloride in sawdust pyrolysis is a complex and either promoting or deterring effect was primarily dependent on the degree of conversion.

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 score0.003

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
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 head0.017
GPT teacher head0.238
Teacher spread0.221 · 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

Citations2
Published2025
Admission routes3
Has abstractyes

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