Comprehensive characterization of Yanchama (Poulsenia Armata) fiber cloth from the Ecuadorian Amazon region: Towards sustainable reinforcement materials
Bibliographic record
Abstract
Natural fibers are valued for their sustainability, low cost, and availability, positioning them as attractive alternatives to synthetic materials. This study comprises a comprehensive characterization of Poulsenia Armata fiber cloth (PAFC), focusing on its physical, mechanical and thermal properties. The fiber morphology was examined using scanning electron microscopy (SEM), thermal stability by thermogravimetric analysis (TGA), chemical composition through ANKOM procedures, crystallinity by X-ray diffraction (XRD), surface and chemical structure through Fourier-transform infrared spectroscopy (FTIR) and 13 C Solid State Nuclear Magnetic Resonance (NMR) spectroscopy. The mechanical performance was investigated via tensile testing. Results revealed a low lignin and hemicellulose content with percentages of 1.38 and 0.51%, respectively, while the cellulose content was determined to be around 58%. SEM micrographs showed that PAFC consists on a rough surface with several interconnected fibrils. The experimental density was measured to be 1.53 g/cm 3 . TGA showed a loss of approximately 5% of weight due to moisture elimination and the beginning of thermal degradation at around 245°C with a maximum decomposition rate at 371.8 °C. XRD analysis yielded a crystallinity index and a crystallite size of around 70% and 2.76 nm, respectively. FTIR and NMR spectra confirmed the predominance of cellulose content relative to hemicellulose and lignin through the presence of several characteristic peaks. Tensile tests revealed an ultimate tensile strength of 30 MPa, a modulus of elasticity of 227 MPa, and an elongation at break of 15%. Collectively, these findings highlight the potential of PAFC as a novel lignocellulosic material for diverse engineering applications.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
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".