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Record W2980095606 · doi:10.1002/open.201900263

Modification of Kraft Lignin with Dodecyl Glycidyl Ether

2019· article· en· W2980095606 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueChemistryOpen · 2019
Typearticle
Languageen
FieldEngineering
TopicLignin and Wood Chemistry
Canadian institutionsLakehead University
FundersCanada Research ChairsCanada Foundation for Innovation
KeywordsLigninChemistryThermogravimetric analysisEtherDifferential scanning calorimetryAlkylThermal stabilityKraft paperOrganic chemistryFourier transform infrared spectroscopyGraftingPolymer chemistryChemical engineeringPolymer

Abstract

fetched live from OpenAlex

Kraft lignin (KL) is extensively produced in industry but is mainly burned as fuel. To broaden its use, KL was grafted with dodecyl glycidyl ether to alter its thermal properties. The reaction of KL with dodecyl glycidyl ether (DGE) was analyzed using nuclear magnetic resonance (NMR), Fourier infrared spectroscopy (FT-IR) and elemental analysis. Alternatively, KL was methylated to mask its phenolic hydroxy groups to investigate how phenolic hydroxy groups impact the grafting of the alkyl chain of DGE onto lignin (methylated Kraft lignin, MKL). The methylation facilitated the molecular weight enhancement and thermal stability reduction of Kraft lignin via grafting with DGE. The influence of grafting alkyl chains on the structural and thermal properties of KL and MKL was studied using thermogravimetric analysis and differential scanning calorimetry analysis. Our data suggest that, due to their high molecular weights and lower glass transition temperatures, the produced lignin derivatives may be promising feedstocks for composite production.

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.

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 score0.146
Threshold uncertainty score0.450

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)0.0000.000

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 head0.006
GPT teacher head0.195
Teacher spread0.189 · 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