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Record W2802124745 · doi:10.1002/adsu.201800026

The Effect of Polymorphism on the Kinetics of Adsorption and Degradation: A Case of Hydrogen Chloride Vapor on Cellulose

2018· article· en· W2802124745 on OpenAlexaff
Elina Niinivaara, Shiek Abdullah Abdul Arshath, Kaarlo Nieminen, Alexander Bismarck, Eero Kontturi

Bibliographic record

VenueAdvanced Sustainable Systems · 2018
Typearticle
Languageen
FieldMaterials Science
TopicAdvanced Cellulose Research Studies
Canadian institutionsMcMaster University
FundersEngineering and Physical Sciences Research CouncilUniversität WienAcademy of Finland
KeywordsCelluloseChemistryAqueous solutionAdsorptionReactivity (psychology)PolymerKineticsPolymorphism (computer science)HydrolysisCrystallinityChloridePolymer chemistryMoleculeHydrogen bondHydrogen chlorideInorganic chemistryChemical engineeringOrganic chemistryCrystallography

Abstract

fetched live from OpenAlex

Abstract Control of the reactivity of natural polymers – such as semicrystalline cellulose – through polymorphic transitions is a potent, yet underexplored tool in modern polymer science. Here, the degradation behavior of three artificial cellulose polymorphs (cellulose II, IIII, and IIIII) in the presence of hydrogen chloride vapor is explored. While the ultimate results of hydrolyses correspond to those found for aqueous HCl, the kinetic scission models exhibit a unique trend for each polymorph, unlike those reported for aqueous acid or enzymatic hydrolyses. In addition to the polymorphic distinctions, these atypical trends are attributed to the nonequilibrium in the hydrolysis set up and the irregular adsorption of HCl molecules to the substrate surfaces. The results point to a new way of approaching the reactivity of natural polymers where polymorphism is regarded as one of the parameters for the kinetics and outcome of chemical reactions.

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 score0.002
Threshold uncertainty score0.004

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 integrity0.0000.000
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 head0.010
GPT teacher head0.267
Teacher spread0.256 · 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

Citations11
Published2018
Admission routes1
Has abstractyes

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