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Record W3179402598 · doi:10.1002/app.51375

<scp>In‐depth</scp> material characterization of polyhydroxybutyrate from a forest biorefinery

2021· article· en· W3179402598 on OpenAlexafffund
Karolin Dietrich, Marie‐Josée Dumont, Valérie Orsat, Luis F. Del Rio

Bibliographic record

VenueJournal of Applied Polymer Science · 2021
Typearticle
Languageen
FieldMaterials Science
Topicbiodegradable polymer synthesis and properties
Canadian institutionsMcGill University
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsHydrolysatePolyhydroxybutyrateDifferential scanning calorimetryHardwoodBiorefinerySugarMaterials scienceDynamic mechanical analysisFourier transform infrared spectroscopyCrystallinityCarbon fibersGlass transitionChemistryChemical engineeringPolymerRaw materialFood scienceOrganic chemistryComposite materialBotanyHydrolysis

Abstract

fetched live from OpenAlex

Abstract Large‐scale replacement of petroplastics with compostable plastics, like polyhydroxybutyrates (PHB) will contribute to elimination plastic pollution, decrease greenhouse gas emissions, and valorize local biomass resources. Lignocellulose hydrolysates have emerged as potentially sustainable carbon sources for PHB production. For industrial processing, it is necessary to know the polymer properties. Yet, most studies on PHB samples from lignocellulose report few material properties. PHB samples produced from a pilot scale hardwood holocellulose hydrolysate conversion process were characterized and compared with PHB from a sugar hydrolysate and a commercial PHB powder. PHB from hardwood holocellulose hydrolysate was found to be comparable with commercial PHB in all properties. Differential scanning calorimetry and thermal gravimetric analysis showed that all samples had similar thermal behavior, where the melting temperature was 176°C and the decomposition temperature was 293°C. From the melting enthalpy, all samples showed 63% crystallinity. Dynamic mechanical analysis showed a glass transition temperature at 5°C and a crystallization temperature of 57°C. Fourier transform infrared spectroscopy and nuclear magnetic resonance confirmed that the samples were homopolymers comprised of hydroxybutyrate units. The difference among the samples was the number average molecular mass, being lower for wood hydrolysate (246.4 kDa) than sugar hydrolysate (670.3 kDa).

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 score0.616

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.001
Scholarly communication0.0000.001
Open science0.0010.000
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 head0.014
GPT teacher head0.211
Teacher spread0.198 · 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

Citations10
Published2021
Admission routes2
Has abstractyes

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