Degradable Alternatives to Single-Use Plastics: Mechanisms, Materials, and Strategies for Sustainable Polyolefin Replacement
Bibliographic record
Abstract
The widespread use of single-use plastics, particularly polyethylene (PE) and polypropylene (PP), has resulted in severe environmental pollution due to their durability and resistance to degradation. This report reviews current degradable alternatives to conventional polyolefins and strategies for enhancing their breakdown in natural and managed environments. Mechanisms of abiotic and biotic degradation are examined alongside the influence of environmental factors and standardized testing protocols. Commercially available biodegradable polymers-such as polylactic acid (PLA), polyhydroxyalkanoates (PHAs), poly(butylene succinate) (PBS), poly(butylene adipate-co-terephthalate) (PBAT), starch-based plastics, cellulose derivatives, chitosan, and protein-based materials-are evaluated for their sources, degradation behavior, applications, scalability, and limitations. In addition, modification techniques for PE and PP, including copolymerization, pro-degradant additives, blending with biodegradable fillers, surface functionalization, enzyme-assisted degradation, and photocatalytic additives, are critically assessed for their potential to reduce environmental persistence. Key challenges such as performance trade-offs, incomplete degradation, ecotoxicity, cost, scalability, and end-of-life management are discussed within the context of circular economic integration. This report concludes with future research directions aimed at developing cost-effective, high-performance materials that degrade completely under real-world conditions while minimizing ecological impacts.
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 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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".