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Record W2338771374 · doi:10.1177/0892705716632856

Synthesis and characterization of lignin–melamine–formaldehyde resin

2016· article· en· W2338771374 on OpenAlexaff
Amadou Diop, Kokou Adjallé, Benjamin Boëns, Daniel Montplaisir, Simon Barnabé

Bibliographic record

VenueJournal of Thermoplastic Composite Materials · 2016
Typearticle
Languageen
FieldEngineering
TopicLignin and Wood Chemistry
Canadian institutionsUniversité du Québec à Trois-Rivières
Fundersnot available
KeywordsFourier transform infrared spectroscopyDifferential scanning calorimetryFormaldehydeLigninMelamineMelamine resinThermogravimetric analysisPolymer chemistryMaterials scienceCuring (chemistry)Yield (engineering)Amine gas treatingNuclear chemistryChemistryOrganic chemistryChemical engineeringComposite material

Abstract

fetched live from OpenAlex

Lignin–melamine–formaldehyde (LMF) resin was prepared by three steps: (i) tosylation of lignin, (ii) synthesis of lignin-melamine (LM) copolymer, and (iii) formation of methylol LM. The synthesized resins were characterized by Fourier transform infrared (FTIR) spectroscopy and phosphorous 31 nuclear magnetic resonance analysis. The curing parameters of LMF resin were determined by differential scanning calorimetry (DSC) and thermal gravimetric analysis. The yield of tosylation is 80%. The FTIR spectrum of tosylated lignin shows the presence of two new bands at 1171 and 1370 cm −1 . The formation of the LM was demonstrated by the disappearance of both bands and appearance of the absorbances at 3115, 3312, 3415, and 3470 cm −1 corresponding to the stretching vibrations of primary and secondary amine. The peaks observed at 147.0 and 148.5 ppm are attributed to the new aliphatic hydroxyl groups formed by the methylolation of LM. One exothermic peak was observed in the DSC analysis indicating a one cross-linking reaction.

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 score0.002
Threshold uncertainty score0.006

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)0.0020.001

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 head0.004
GPT teacher head0.173
Teacher spread0.169 · 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

Citations12
Published2016
Admission routes1
Has abstractyes

Explore more

Same venueJournal of Thermoplastic Composite MaterialsSame topicLignin and Wood ChemistryFrench-language works237,207