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Record W4241423236 · doi:10.26434/chemrxiv.7312070.v2

Synthesis of High Molecular Weight Chitosan from Chitin by Mechanochemistry and Aging

2018· preprint· en· W4241423236 on OpenAlexaff
Thomas Di Nardo, Caroline Hadad, Albert Nguyen Van Nhien, Audrey Moores

Bibliographic record

VenueChemRxiv · 2018
Typepreprint
Languageen
FieldMaterials Science
TopicNanocomposite Films for Food Packaging
Canadian institutionsMcGill University
Fundersnot available
KeywordsChitinChitosanMagic angle spinningSolventViscometerChemical engineeringPolymer chemistryChemistryMaterials scienceOrganic chemistryNuclear magnetic resonance spectroscopyComposite materialViscosity

Abstract

fetched live from OpenAlex

We report herein a novel path, relying on a combination of mechanochemitry and aging, to afford high molecular weight chitosan with minimal use of energy and solvent. We demonstrate that this method is versatile and applicable to a number of chitin sources, including crude crustaceans and insect shells, yielding deacetylation up to 98% and molecular weights up to 20,770 kDa. Chitin deacetylation yields were measured by magic angle spinning nuclear magnetic resonance. Chitin and chitosans molecular weights were calculated by viscometry using an ionic liquid as a solvent. The effect of amorphization of chitin, and aging conditions, including humidity levels and temperatures were studied.

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 score0.003

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 integrity0.0000.001
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 head0.005
GPT teacher head0.211
Teacher spread0.206 · 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

Citations1
Published2018
Admission routes1
Has abstractyes

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