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Record W3055723019 · doi:10.1021/acs.biomac.0c01031

Xyloglucan Structure Impacts the Mechanical Properties of Xyloglucan–Cellulose Nanocrystal Layered Films—A Buckling-Based Study

2020· article· en· W3055723019 on OpenAlexafffund
Taylor C. Stimpson, Bernard Cathala, Céline Moreau, Jose Moran‐Mirabal, Emily D. Cranston

Bibliographic record

VenueBiomacromolecules · 2020
Typearticle
Languageen
FieldMaterials Science
TopicAdvanced Cellulose Research Studies
Canadian institutionsUniversity of British ColumbiaMcMaster University
FundersNatural Sciences and Engineering Research Council of CanadaAgence Nationale de la RechercheLabEx SERENADE
KeywordsXyloglucanCelluloseMaterials scienceElastic modulusPolymerChemical engineeringComposite material

Abstract

fetched live from OpenAlex

Interactions between polysaccharides, specifically between cellulose and hemicelluloses like xyloglucan (XG), govern the mechanical properties of the plant cell wall. This work aims to understand how XG molecular weight (MW) and the removal of saccharide residues impact the elastic modulus of XG-cellulose materials. Layered sub-micrometer-thick films of cellulose nanocrystals (CNCs) and XG were employed to mimic the structure of the plant cell wall and contained either (1) unmodified XG, (2) low MW XG produced by ultrasonication (USXG), or (3) XG with a reduced degree of galactosylation (DGXG). Their mechanical properties were characterized through thermal shrinking-induced buckling. Elastic moduli of 19 ± 2, 27 ± 1, and 75 ± 6 GPa were determined for XG-CNC, USXG-CNC, and DGXG-CNC films, respectively. The conformation of XG adsorbed on CNCs is influenced by MW, which impacts mechanical properties. To a greater degree, partial degalactosylation, which is known to increase XG self-association and binding capacity of XG to cellulose, increases the modulus by fourfold for DGXG-CNC films compared to XG-CNC. Films were also buckled while fully hydrated by using the thermal shrinking method but applying the heat using an autoclave; the results implied that hydrated films are thicker and softer, exhibiting a lower elastic modulus compared to dry films. This work contributes to the understanding of structure-function relationships in the plant cell wall and may aid in the design of tunable biobased materials for applications in biosensing, packaging, drug delivery, and tissue engineering.

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)0.000
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
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 score0.003
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
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 head0.032
GPT teacher head0.271
Teacher spread0.239 · 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.

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

Citations19
Published2020
Admission routes2
Has abstractyes

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