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Record W2950815074 · doi:10.3390/ma12121946

Surface Chemical Changes of Sugar Maple Wood Induced by Thermo-Hygromechanical (THM) Treatment

2019· article· en· W2950815074 on OpenAlexafffund
Qilan Fu, Alain Cloutier, Aziz Laghdir, Tatjana Stevanović

Bibliographic record

VenueMaterials · 2019
Typearticle
Languageen
FieldEngineering
TopicLignin and Wood Chemistry
Canadian institutionsService de Recherche et d'EXpertise en Transformation des Produits ForestiersUniversité Laval
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsLigninLevoglucosanCellulosePyrolysisX-ray photoelectron spectroscopyDepolymerizationFourier transform infrared spectroscopyChemical compositionChemical structureChemistrySugarAttenuated total reflectionMaterials scienceDecompositionHemicelluloseChemical engineeringOrganic chemistryInfrared spectroscopy

Abstract

fetched live from OpenAlex

The aim of this study was to investigate the effects of heat and steam on the chemical properties of thermo-hygromechanical (THM)-densified sugar maple wood. The THM densification process was performed at two different temperatures (180 °C and 200 °C) with and without steam. The functional groups, surface chemical composition and internal structure and components of the control and densified samples were investigated using attenuated total reflection Fourier transform infrared (ATR-FTIR), X-ray photoelectron (XPS) spectroscopy and pyrolysis gas chromatography-mass spectrometry (Py-GC/MS). The obtained results suggest that the THM densification treatment resulted in significant chemical changes on the wood surface. The results of the ATR-FTIR spectra confirmed the decomposition of hemicelluloses and the relative increase of cellulose and lignin contents on the wood surface. The Py-GC/MS and XPS results show an increase of the oxygen/carbon atomic (O/C) ratio, which indicated that chemical substances containing oxygenated functionality were formed through the densification process. The densification treatment favored the depolymerization of hemicelluloses and cellulose as indicated by an increased anhydrous sugar (levoglucosan) release during the pyrolysis process. Densification also facilitated the cleavage of the lignin side chains, resulting in increased phenyl units with short chains released during the pyrolysis 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)0.000
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 score0.001
Threshold uncertainty score0.685

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 studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.011
GPT teacher head0.205
Teacher spread0.194 · 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

Citations19
Published2019
Admission routes2
Has abstractyes

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