Rheological, Structural and Melt Spinnability Study on Thermo-plastic Starch/PLA Blend Biopolymers and Tensile, Thermal and Structural Characteristics of Melt Spun Fibers
Bibliographic record
Abstract
In this study, rheology, structure and melt spinnability of thermoplastic starch TPS/PLA blend compounds as well as characteristics of melt spun fibers was studied. Thermoplastic starch is further modified with tartaric acid and blends are compatibilized using graft copolymer, maleic anhydride grafted PLA. Results from rheology analysis of compounds shows significantly reduced melt flow rate MFR and reduced viscosity as a result of tartaric acid modification and compatibilization, but the viscosity was increased as TPS_TA content in the blend increased. In addition, storage modulus (G`) and loss modulus (G``) were increased with increasing TPS_TA content in the blends. Fourier transform infrared spectroscopy FTIR analysis confirmed O-H peak shifts and peak intensity changes associated to starch thermosplasticization and further peak shifts associated with more O-H bond breakages due to tartaric acid modification, indicating acid hydrolysis action of tartaric acid which agrees with results from rheology study. Melt spinning trials show the possibility of melt spinning of biopolymer fibers from blends with up to 40%w/w TPS_TA content. The melt spun fibers have diameter in range of 12.0–124.0 μm depending on take up speed and TPS_TA content. Differential scanning calorimetry DSC analysis of melt spun fibers shows glass transition Tg shifts attributed to molecular orientation and rigid amorphous TPS phase formation as well as the occurrence of double melting peaks Tm associated to different crystals resulting from induced crystallization. The overall result from this study shows the possibility of melt spinning thermoplastic starch/PLA blend biopolymers in to fibers, revealing opportunity to utilize starch biopolymer for fiber spinning. Furthermore, the results also show the need for further research engagements to get fibers with better performance.
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 | 0.004 | 0.001 |
| 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 | 0.006 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".