Carbon Dioxide–Derived Poly(propylene carbonate) as a Matrix for Composites and Nanocomposites: Performances and Applications
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Abstract The conversion of CO 2 into polymers such as poly(propylene carbonate) (PPC) can contribute to the reduction of dependence on fossil fuel resourced polymers. PPC is a polymer synthesized from the catalyzed copolymerization between CO 2 and propylene oxide. The global demand for renewable and biodegradable polymers coupled with the recent success in catalysis for the copolymerization of CO 2 with epoxides has paved the way for an increased interest and growth in PPC polymers. On the contrary, the extensive utilization of PPC in many applications is still challenging due to its poor thermal stability, mechanical strength, and dimensional stability. Thus, many research efforts currently focus on improving these limitations. On the other hand, polymer processing and application development efforts have continued to utilize the existing PPC. This article presents a comprehensive review of PPC polymer as a matrix component of polymer composites and nanocomposites. Progress in current research on PPC‐based material applications, including industrial packaging, electromagnetic shielding, energy storage, and biomedical applications are included. A critical review of the biodegradability, compostability, and overall sustainability of PPC is also conducted. Finally, challenges that limit the extensive use of such materials, and future research and development directions are highlighted.
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.
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 | 0.000 | 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 it