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Influence of washing with sodium lauryl sulphate (SLS) surfactant on different properties of ramie fibres

2024· article· en· W4392801896 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueBioResources · 2024
Typearticle
Languageen
FieldEngineering
TopicAgricultural Engineering and Mechanization
Canadian institutionsCarleton University
FundersAl-Imam Muhammad Ibn Saud Islamic University
KeywordsRamiePulmonary surfactantSodiumMaterials scienceChemical engineeringComposite materialFiberMetallurgy

Abstract

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Green composite materials are a means of reducing reliance on synthetic and especially single-use plastics (SUP) and raising public awareness of the need for urgent action to protect the planet. Natural (lignocellulosic) fibres are increasingly utilized as the reinforcement in polymer matrix composites, in search for increased renewability and sustainability. This work concerns the effect of washing ramie (Boehmeria nivea) fibres using sodium lauryl sulphate (SLS) surfactant. The SLS-treated ramie fibres were examined for their morphological, physical, thermal, structural, and mechanical properties by powder X-ray diffraction (XRD), Fourier transform infrared (FTIR) spectroscopy, thermogravimetric analysis (TGA), scanning electron microscopy (SEM), and tensile testing. SLS treated ramie fibres density and crystallinity index values were 1.23 g/cc and 84.5%, respectively, with a very high cellulose content of 81.3%, because hemicellulose and loose particles were dissolved. SEM images depicted the relevant changes, with no significant damage on treated fibre surfaces. With some assistance from the treatment, fibres initiated their degradation only above 250 °C, culminating at 327 °C, which appears suitable for the manufacturing of composites with the most common matrices.

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.

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)0.000
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 score0.362
Threshold uncertainty score0.289

Codex and Gemma teacher scores by category

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)0.0000.000

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 head0.006
GPT teacher head0.159
Teacher spread0.153 · 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