Traitement solvothermique superficiel de la biomasse lignocellulosique dans les liquides ioniques–hygroscopicité, morphologie et propriétés mécaniques
Bibliographic record
Abstract
Le traitement thermique superficiel du bois permet de rehausser ses propriétés hydrophobe, antifongique et anti‐gonflement contribuant à le mettre à l'abri des aléas naturels. Nous avons étudié la pertinence d'un traitement solvothermique d'éprouvettes de bois d'épinette noire imprégnées de liquides ioniques hydrophile ([EMIM][OTf]) et hydrophobe ([HMIM][TF2N]) comparativement à un traitement thermique simple sous balayage à l'azote. Les éprouvettes ont été soumises à des tests d'adsorption d'humidité, d'absorption d'eau, de gonflement, et de propriétés mécaniques après des traitements réalisés dans les gammes de température et de temps suivantes: [180 °C–260 °C] et [30 min–4 h]. Les tests ont montré une diminution notable de la teneur ultime en humidité et de prise d'eau liquide lorsque les échantillons de bois sont préalablement imprégnés de liquide ionique hydrophobe et que la température de traitement reste inférieure à 200 °C. Cependant, les tests de propriétés mécaniques ont montré que les modules d'élasticité et de rupture des éprouvettes affichaient une tendance à la baisse avec l'augmentation de la température et du temps de traitement. L'imprégnation de liquide ionique ne changeait rien à ce comportement même si en général une fragilisation accrue des éprouvettes pouvait être notée à cause de la solubilisation partielle des principaux composants de bois. Surface heat treatment of wood improves its hydrophobic, antifungal, and anti‐swelling properties, and strengthens its resistance to the vagaries of natural exposure. We investigated the relevance of a superficial solvothermal treatment of wood specimens impregnated with hydrophilic ([EMIM][OTf]) and hydrophobic ([EMIM][OTf]) ionic liquids which we compared to a conventional heat treatment under nitrogen atmosphere over the following treatment temperature and time ranges: [180 °C – 260 °C] and [30 min – 4 h]. The treated specimens were subjected to moisture adsorption, water absorption, swelling, and mechanical properties testing. The results revealed a notable decrease in ultimate moisture content and water uptake of the samples, provided they were impregnated with a hydrophobic ionic liquid before heat treatment at temperatures less than 200 °C. However, the mechanical properties testing showed that the elastic and rupture moduli of specimens decreased with increasing treatment temperature and time irrespective of using ionic liquids. However, the impregnated samples suffered in general increased breakability which was ascribed to partial solubilization of wood components in the ionic liquid.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".