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Record W4229020758 · doi:10.1002/app.52520

A green composite hydrogel based on xylan and lignin with adjustable mechanical properties, high swelling, excellent <scp>UV</scp> shielding, and antioxidation properties

2022· article· en· W4229020758 on OpenAlexaff
Yanbin Yi, Xiaohui Wang, Zhongming Liu, Chao Gao, Pedram Fatehi, Shoujuan Wang, Fangong Kong

Bibliographic record

VenueJournal of Applied Polymer Science · 2022
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicHydrogels: synthesis, properties, applications
Canadian institutionsLakehead University
FundersNatural Science Foundation of Shandong ProvinceInnovative Research Group Project of the National Natural Science Foundation of China
KeywordsSwellingMaterials scienceComposite numberLigninThermogravimetric analysisComposite materialSelf-healing hydrogelsFourier transform infrared spectroscopyXylanToughnessSwelling capacityScanning electron microscopeDynamic mechanical analysisPolymerChemical engineeringPolymer chemistryChemistryPolysaccharideOrganic chemistry

Abstract

fetched live from OpenAlex

Abstract This study successfully prepared a novel green composite hydrogel based on carboxymethyl xylan and lignin with adjustable mechanical properties, high swelling, excellent UV shielding, and antioxidation performance. The structure and morphology of the hydrogel were characterized by Fourier transform infrared spectra, scanning electron microscopy, thermogravimetric analysis, rheological analysis, and swelling ratio. Results showed that lignin could significantly improve the mechanical properties of composite hydrogels. The compression stress and toughness of the composite hydrogel contained lignin increased by 39% and 60%, respectively, and the compressive deformation reached 90%. In addition, the addition of lignin increased the swelling ratio of the composite hydrogel reached 79.9 g/g. In addition, the composite hydrogel exhibited excellent UV shielding and antioxidation performance. The removal ratio of UV and free radicals is as high as 80% and 90%, respectively. The simple procedure and cost‐effective lignin as raw material for hydrogel with adjustable properties are favorable for medical‐biological applications.

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 score0.005
Threshold uncertainty score0.597

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 studies0.0010.000
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 head0.013
GPT teacher head0.204
Teacher spread0.191 · 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

Citations22
Published2022
Admission routes1
Has abstractyes

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