Highly filled blends of a vinylic copolymer with plasticized lignin: Thermal and mechanical properties
Bibliographic record
Abstract
Abstract The objective of this study was the development of new vinyl flooring formulations with increased resistance to attack by fungi and microorganisms, formulated with plasticizers having chemical compositions different from that of common dioctyl phthalate (DOP). Alkyl phthalate plasticizers are considered to be toxicological and ecotoxicological hazards, although this is still under debate. It is suspected that during the service life of poly(vinyl chloride) (PVC) flooring, the attack of fungi and microorganisms leads to the degradation of DOP and the release of some volatile organic compounds. For this reason, in the new flooring formulations, the vinyl chloride/vinyl acetate copolymer (VC–VAc) was partially replaced with lignin, a natural polymer and a major component of wood and vascular plants. Besides its other functions in wood, lignin imparts resistance to microorganisms. An organosolv lignin from Alcell Technologies, Inc. (AL), was used as a partial replacement of PVC. The influence of the new plasticizers, as well as the influence of the partial replacement of VC–VAc with lignin, on the morphology and thermal and mechanical properties of the composites was investigated with scanning electron microscopy, differential scanning calorimetry, and tensile testing. Butyl benzyl phthalate and diethylene glycol dibenzoate were used as plasticizers; both were compatible with PVC and AL. The results indicated that diethylene glycol dibenzoate was the best plasticizer for these blend composites. In these formulations, AL could replace up to 20 parts of the copolymer. At this level of replacement, the key mechanical properties of the new composites compared very favorably with those of the DOP control formulations. The obtained formulation will be tested further for resistance to fungi and microorganisms. © 2003 Wiley Periodicals, Inc. J Appl Polym Sci 89: 2000–2010, 2003
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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) | 0.001 | 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".