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Record W2899240226

Evaluation of Bio/pMDI Wood Adhesives

2018· dissertation· en· W2899240226 on OpenAlexfundno aff
Che Zhang

Bibliographic record

VenueUWSpace (University of Waterloo) · 2018
Typedissertation
Languageen
FieldEngineering
TopicLignin and Wood Chemistry
Canadian institutionsnot available
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsAdhesivePolymer scienceMaterials scienceNanotechnology
DOInot available

Abstract

fetched live from OpenAlex

With the increasing concerns about formaldehyde emissions from wood-based panels and the demands of the sustainable products, the potential of synthetic wood resins derived from biomass resources has sparked enormous interest. To date, extensive efforts have been devoted to investigating the mechanism, the properties, and the modification approach of the bio-adhesives. To overcome the limitations of pure bio-adhesives (low reactivity, low moisture resistance, and biodegradation), many approaches have been developed to partially replace the bio-polymer with synthetic thermosetting adhesives. In this project, a functional experimental grade binder, made from the reactive extrusion modification process of biopolymers with other reagents, is used as a co-binder in combination with polymeric methylene diphenyl diisocyanate (pMDI) resin, to study the resulting performance of the system for wood adhesive applications. \nTo evaluate the influence of the experimental grade biopolymer binder on the performance of the pMDI adhesive, a pMDI adhesive blended with water was first investigated. The effect of water content on emulsion morphology and viscosity was characterized. For bonded samples, formulations obtaining the highest bonding strength of the water/pMDI adhesives was determined by comparing the pull-off stress and the lap-shear stress. To further improve the bonding performance, the wood substrate was modified by the silane coupling agent, (3-aminopropyl) triethoxysilane (APTES). The penetration depth of pMDI in the different wood substrates (neat wood, 1wt% APTES-treated wood, 3wt% APTES-treated wood) was accurately determined. These studies indicate that both strong interactions between the adhesives and wood substrate, and a certain level of penetration of the adhesives, are required for the good bonding performance of the water/pMDI adhesives. \nThe biopolymer/pMDI adhesives were prepared and investigated based on the protocols from the industry partner Ecosynthetix. By comparing the biopolymer/pMDI adhesives with the water/pMDI adhesives, the effect of the biopolymer to the pMDI was determined. The biopolymer can work as a thickener, emulsifier of the system to reduce the dosage of pMDI. In terms of bonding performance, the bonding strength of the biopolymer/pMDI adhesive is comparable with the highest stress achieved by water/pMDI resin, indicating the experimental grade biopolymer can be applied as an effective wood adhesive binder to partially replace pMDI without reducing the overall bonding performance.

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 score0.002
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.012
GPT teacher head0.205
Teacher spread0.193 · 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

Citations0
Published2018
Admission routes1
Has abstractyes

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