Toughening and Heat-Resistant Modification of Degradable PLA/PBS-Based Composites by Using Glass Fiber/Silicon Dioxide Hybrid Fillers
Bibliographic record
Abstract
In this paper, to enhance the toughness and heat resistance properties of polylactic acid (PLA)/polybutylene succinate (PBS) composites, the PLA/PBS matrix was modified by different glass fiber (GF), GF/SiO2, and GF/(Polyaluminium chloride) PAC fillers. Additionally, the effect of filler type, filler content, components interaction and composite structure on the mechanical and thermal properties of the PLA/PBS composites was researched. The results showed that the addition of GF, GF/SiO2 and GF/PAC make the PLA/PBS composites appear significantly higher mechanical properties compared with the pristine PLA/PBS composite. Among the different inorganic fillers, the 10%GF/1%SiO2 fillers showed excellent strengthening, toughening and heat resistant effects. Compared with the pristine PLA/PBS matrix, the tensile strength, elastic modulus, flexural strength, flexural modulus and Izod impact strength improved by 36.28%, 70.74%, 67.95%, 66.61% and 135.68%, respectively. Considering the above, when the weight loss rate was 50%, the thermal decomposition temperature of the 10%GF/1%SiO2 modified PLA/PBS composites was the highest 412.83 °C and its Vicat softening point was up to 116.8 °C. In a word, the 10%GF/1%SiO2 reinforced PLA/PBS composites exhibit excellent mechanical and thermal properties, which broadens the application of biodegradable materials in specific scenarios.
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.
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 | 0.000 | 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 | 0.001 | 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 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".