MétaCan
Menu
Back to cohort
Record W4385310221 · doi:10.1016/j.heliyon.2023.e18702

Ultrasonic-assisted sustainable extraction and dyeing of organic cotton fabric using natural dyes from Dillenia indica leaf

2023· article· en· W4385310221 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.

fundA Canadian funder is recorded on the work.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueHeliyon · 2023
Typearticle
Languageen
FieldEngineering
TopicDyeing and Modifying Textile Fibers
Canadian institutionsnot available
FundersUniversity of DhakaCentre for Interdisciplinary Research in Rehabilitation
KeywordsDyeingExtraction (chemistry)Thermogravimetric analysisMaterials sciencePulp and paper industryNatural dyeHueTextileComposite materialChemistryOrganic chemistryComputer scienceEngineering

Abstract

fetched live from OpenAlex

As a means of preventing environmental damage caused by synthetic dyes, eco-friendly textile dyeing with natural dyes is gaining popularity worldwide. This study focused on the extraction of dyes from the leaf of Dillenia indica ( D. indica ) tree using an ultrasonic extraction technique and applied on the organic cotton fabrics. The ultrasonic method was used for both extractions of D. indica dyes and dyeing of organic cotton fabrics. Here, the amount of D. indica powder used were 5% and 6.67% for producing light and dark shade, respectively. The investigation of the color fastness to washing, rubbing, and light for the dyed organic cotton fabrics indicated an excellent rating. The spectrophotometric analysis revealed the L* (lightness or darkness), a* (redness or greenness), b* (yellowness or blueness), C* (chroma), h* (hue), R% (reflectance), and K/S (color strength) values, which accurately represented the shade of the dyed organic cotton fabric. To understand the interaction between D. indica dye and organic cotton fabrics, different characterization including, Fourier transform infrared spectroscopy (FTIR) and scanning electron microscopy (SEM) were performed. The characterization outcomes confirmed the successful deposition of D. indica dyes on the organic cotton fabrics. The other comparable testing results such as bursting strength, air permeability, and thermogravimetric analysis (TGA) of dyed and undyed organic cotton fabrics were in the acceptable range. One of the important findings of this research was no chemicals were utilized during the extraction and dyeing of organic cotton fabrics. This process can be referred to as completely chemical-free and advantageous for the environment because no chemicals were needed during extraction or dyeing. Therefore, the natural dye extracted from D. indica is extremely promising and could be a viable option for the sustainable dyeing of cotton fabrics in the textile dyeing industry.

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 score0.535
Threshold uncertainty score0.695

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 head0.013
GPT teacher head0.237
Teacher spread0.224 · 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