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Solubility of Lignin and Acetylated Lignin in Organic Solvents

2017· article· en· W2588064525 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

VenueBioResources · 2017
Typearticle
Languageen
FieldEngineering
TopicLignin and Wood Chemistry
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsLigninSolubilityOrganic chemistrySoftwoodKraft paperChemistrySolventHildebrand solubility parameterMaterials science

Abstract

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The solubility of four lignin samples and their acetylated forms was determined in a series of organic solvents to investigate the relationship between solubility and the solubility parameter. The solubility parameter of lignin samples and acetylated lignin was calculated based on the number of atoms or groups on lignin units. Lignin samples were obtained by isolating lignin from lignocellulosic bioethanol residues (Lignin 1 [L1]), isolating lignin from kraft hardwood black liquor (Lignin 2 [L2]), commercial kraft softwood lignin (Lignin 3 [L3]), and commercial soda non-wood lignin (Lignin 4 [4]). The solubility of lignin in organic solvents was not predictable due to poor correlation between the solubility of lignin and its solubility parameter. However, the solubility of lignin in an organic solvent depended on the molecular weight and the aliphatic hydroxyl number of the lignin. L2, with a lower molecular weight than other lignin samples, had the highest solubility in organic solvents, and L3, with highest aliphatic hydroxyl number, had the lowest solubility in organic solvents. All acetylated lignins were soluble in most of the organic solvents. Furthermore, the molecular weights of the soluble parts of all four lignins in ethyl acetate were found to be lower than the original lignins.

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 score0.140
Threshold uncertainty score0.400

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 head0.008
GPT teacher head0.206
Teacher spread0.198 · 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