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Record W4395684551 · doi:10.3390/polym16091211

Study of Cellulose Dissolution in ZnO/NaOH/Water Solvent Solution and Its Temperature-Dependent Effect Using Molecular Dynamics Simulation

2024· article· en· W4395684551 on OpenAlexaff
Lamiae Bourassi, Meriem El Mrani, Mohammed Merzouki, Rania Abidi, Haytham Bouammali, Boufelja Bouammali, Larbi El Farh, Rachid Touzani, Allal Challioui, Mohamed Siaj

Bibliographic record

VenuePolymers · 2024
Typearticle
Languageen
FieldMaterials Science
TopicAdvanced Cellulose Research Studies
Canadian institutionsUniversité du Québec à Montréal
Fundersnot available
KeywordsCelluloseDissolutionAqueous solutionChemical engineeringSolventSolubilitySodium hydroxideMaterials scienceHydrogen bondMolecular dynamicsPolymerContext (archaeology)ZincBiopolymerMoleculeChemistryOrganic chemistryComposite materialComputational chemistry

Abstract

fetched live from OpenAlex

Cellulose is a biopolymer with numerous advantages that make it an ecological, economical, and high-performing choice for various applications. To fully exploit the potential of cellulose, it is often necessary to dissolve it, which poses a current challenge. The aqueous zinc oxide/sodium hydroxide (ZnO/NaOH/Water) system is a preferred solvent for its rapid dissolution, non-toxicity, low cost, and environmentally friendly nature. In this context, the behavior of cellulose chains in the aqueous solution of ZnO/NaOH and the impact of temperature on the solubility of this polymer were examined through a molecular dynamics simulation. The analysis of the root means square deviation (RMSD), interaction energy, hydrogen bond curves, and radial distribution function revealed that cellulose is insoluble in the ZnO/NaOH solvent at room temperature (T = 298 K). Decreasing the temperature in the range of 273 K to 268 K led to a geometric deformation of cellulose chains, accompanied by a decrease in the number of interchain hydrogen bonds over the simulation time, thus confirming the solubility of cellulose in this system between T = 273 K and T = 268 K.

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 score0.195
Threshold uncertainty score0.549

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 head0.017
GPT teacher head0.317
Teacher spread0.300 · 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

Citations6
Published2024
Admission routes1
Has abstractyes

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