Green synthesis of novel biocomposites from treated cellulosic fibers and recycled bio-plastic polylactic acid
Bibliographic record
Abstract
This study investigated mechanical properties of biocomposites developed from recycled polylactic acid (PLA) from packaging industry and treated cellulosic fibers from pulp and paper solid waste. Microwave and enzymatic treatments were used for extraction and surface modification of hydrophilic cellulosic fibers. Enzymatic treatment was specifically performed for activation of hydroxyl groups and improvement of adhesion between matrix and fibers including controlling the length of cellulosic fibers with size reduction of around 50% (142 and 127 μm for primary and mixed biosolids, respectively) as compared to microwave treatment. Microwave treatment produced cellulosic fibers of 293 and 341 μm, for primary and mixed biosolids, respectively. Mechanical properties of biocomposites with 2% (w/w) of treated cellulosic fibers (Young's Modulus 887.83 MPa with tensile strain at breakpoint of 7.22%, tensile stress at yield 41.35 MPa) was enhanced in comparison to the recycled PLA (Young's Modulus 644.47 ± 30.086 MPa with tensile strain at breakpoint of 6.01 ± 0.83%, tensile stress at yield of 29.49 ± 3.64 MPa). Scanning electron microscopy revealed size reduction of cellulosic fibers. X-ray diffraction and Fourier transform infrared spectroscopy confirmed strong mechanical properties of novel biocomposites.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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 source (direct Gemma or distilled Codex), 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".