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Record W1990189726 · doi:10.1021/bm034519+

Effect of Sulfate Groups from Sulfuric Acid Hydrolysis on the Thermal Degradation Behavior of Bacterial Cellulose

2004· article· en· W1990189726 on OpenAlexaff
Maren Roman, William T. Winter

Bibliographic record

VenueBiomacromolecules · 2004
Typearticle
Languageen
FieldMaterials Science
TopicAdvanced Cellulose Research Studies
Canadian institutionsMcGill University
Fundersnot available
KeywordsSulfuric acidHydrolysisSulfateCelluloseThermogravimetric analysisChemistryThermostabilityInorganic chemistryNuclear chemistryOrganic chemistry

Abstract

fetched live from OpenAlex

When used as fillers in polymer composites, the thermostability of cellulose crystals is important. Sulfate groups, introduced during hydrolysis with sulfuric acid, are suspected to diminish the thermostability. To elucidate the relationship between the hydrolysis conditions, the number of sulfate groups introduced, and the thermal degradation behavior of cellulose crystals, bacterial cellulose was hydrolyzed with sulfuric acid under different hydrolysis conditions. The number of sulfate groups in the crystals was determined by potentiometric titration. The thermal degradation behavior was investigated by thermogravimetric analysis. The sulfate group content increased with acid concentration, acid-to-cellulose ratio, and hydrolysis time. Even at low levels, the sulfate groups caused a significant decrease in degradation temperatures and an increase in char fraction confirming that the sulfate groups act as flame retardants. Profile analysis of the derivative thermogravimetric curves indicated thermal separation of the degradation reactions by the sulfate groups into low- and high-temperature processes. The Broido method was used to determine activation energies for the degradation processes. The activation energies were lower at larger amounts of sulfate groups suggesting a catalytic effect on the degradation reactions. For high thermostability in the crystals, low acid concentrations, small acid-to-cellulose ratios, and short hydrolysis times should be used.

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)0.001
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 score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
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 head0.012
GPT teacher head0.261
Teacher spread0.249 · 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

Citations1,253
Published2004
Admission routes1
Has abstractyes

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