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Record W2327308655 · doi:10.1021/ie501282x

Synthesis and Characterization of Biobased Melamine Formaldehyde Resins from Bark Extractives

2014· article· en· W2327308655 on OpenAlexaff
Yubo Chai, Yong Zhao, Ning Yan

Bibliographic record

VenueIndustrial & Engineering Chemistry Research · 2014
Typearticle
Languageen
FieldMaterials Science
TopicThermal and Kinetic Analysis
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsBark (sound)MelaminePinus contortaMountain pine beetleDendroctonusFormaldehydeChemistryCuring (chemistry)SolventSoftwoodPulp and paper industryOrganic chemistryMaterials sciencePolymer chemistryComposite materialBark beetleBotany

Abstract

fetched live from OpenAlex

In this study, bark alkaline extractives from the mountain pine beetle ( Dendroctonus ponderosae Hopkins) infested lodgepole pine ( Pinus contorta Dougl.) was used to partially replace 30 wt % of melamine in formulating the biobased bark extractive–melamine formaldehyde (MF) resin. Results showed that the addition of the bark extractives and the type of solvent system used for resin formulation significantly affected the initial molecular weight, molecular structure, viscosity, curing behavior, postcuring thermal stability, and bonding performance of the resulting resins. The bark extractive–MF resins exhibited similar dry and wet bonding strengths to the laboratory made control MF resins formulated in the same type of solvent system. The liquid-state 13 C NMR study showed that bark extractives were reactants and incorporated into the resulting biobased MF resin structures. Bark extractives obtained from the mountain pine beetle infested lodgepole pine showed promise as a suitable partial replacement for melamine in MF resin formulations.

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)0.000
metaresearch head score (Gemma)0.000
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 score0.002

Distilled classifier scores by category (both heads)

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 head0.042
GPT teacher head0.273
Teacher spread0.231 · 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

Citations27
Published2014
Admission routes1
Has abstractyes

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