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Record W2023304701 · doi:10.1021/ef030118b

Colloidal Properties of Bio-oils Obtained by Vacuum Pyrolysis of Softwood Bark. Characterization of Water-Soluble and Water-Insoluble Fractions

2004· article· en· W2023304701 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.

Bibliographic record

VenueEnergy & Fuels · 2004
Typearticle
Languageen
FieldChemistry
TopicPetroleum Processing and Analysis
Canadian institutionsUniversité Laval
Fundersnot available
KeywordsThermogravimetric analysisLigninPyrolysisChemistryDifferential scanning calorimetrySoftwoodChemical engineeringViscosityRheologyMaterials scienceOrganic chemistryComposite material

Abstract

fetched live from OpenAlex

Crude bio-oils obtained via the pyrolysis of bark residues are dark, viscous, and sticky materials that visually appear similar to homogeneous liquids. However, microscopic tests revealed the presence of tridimensional compounds (agglomerates) and solid particles that are dispersed in the continuous bio-oil medium. These materials are responsible for the increase in bio-oil viscosity, the non-Newtonian flow behavior, the poor combustion properties, the corrosiveness, and the increase in the plugging frequency of the nozzles. Thermogravimetric analysis (TGA), differential scanning calorimetry (DSC) tests, and rheology have been used to evaluate the colloidal properties of the bio-oils. The generic composition of the bio-oil, obtained by extracting water-insoluble materials (i.e., the lignin-derivative compounds), has been determined. The extraction produced a yield of lignin-derivative compounds of 29 wt %. The chemical composition of the water-soluble materials, as well as the molecular weight distribution of the water-insoluble components, has also been determined.

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 score0.007
Threshold uncertainty score0.557

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 head0.007
GPT teacher head0.190
Teacher spread0.184 · 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