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Molecular Characteristics of Chitosan and Structure of its Films Formed from Water Solutions of Acetic and Hydrochloric Acids

2016· article· en· W2513478237 on OpenAlexvenueno aff
N. G. Bel’nikevich, E. Yu. Rosova, И. И. Малахова, Z. F. Zoolshoev, Elena Popova Elena Popova, Natalia Saprykina, Galina Galina Elyashevich

Bibliographic record

VenueJournal of Research Updates in Polymer Science · 2016
Typearticle
Languageen
FieldMaterials Science
TopicNanocomposite Films for Food Packaging
Canadian institutionsnot available
FundersRussian Foundation for Basic Research
KeywordsHydrochloric acidCrystallinityChitosanAcetic acidMaterials scienceMoleculePolymer chemistryAmorphous solidChemical engineeringOrganic chemistryChemistryComposite material

Abstract

fetched live from OpenAlex

Molecular characteristics of chitosan in diluted water solutions of acetic and hydrochloric acids were studied by viscometry, dynamic light scattering, and thin layer chromatography. Chitosan molecules were found to undergo destruction in the solutions of hydrochloric acid and its mixtures with acetic acid. The structure of the chitosan films cast from these solvents was studied by DSC, TGA, and SEM. As shown by electron microscopic data, all the films had an amorphous-crystalline structure but the films prepared from chitosan solutions in diluted hydrochloric acid were characterized by a higher degree of crystallinity. It was supposed that a lower molecular mass of chitosan molecules in the hydrochloric acid solutions results in more extended conformations providing a higher capability of self-organization and formation of regular supermolecular structure. The difference in crystal modification in structure of the films cast of these acids was observed. It was found that the films prepared from the mixtures of acids had a spherulite structure and the crystal modification like ones cast from hydrochloric acid, but with a lower degree of crystallinity.

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 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)0.001
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 score0.664

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.002
Scholarly communication0.0000.001
Open science0.0010.001
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 head0.017
GPT teacher head0.299
Teacher spread0.282 · 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 teacher head, 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

Citations2
Published2016
Admission routes1
Has abstractyes

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