Biodegradability and Compostability of Lignocellulosic Based Composite Materials
Bibliographic record
Abstract
Lignocellulosic composites have attracted interest from both academia and industry due to their benefi cial environmental and sustainability attributes. The lignocellulosic industry has seen remarkable improvements in the development of composites for high performance applications. Both biodegradable as well as non-biodegradable polymers are used in the design and engineering of lignocellulosic composites. Biodegradability studies of lignocellulosic composites in soil and composting environments help in planning their end-life management. Biodegradability tests are complex and dependent on the environment in which the testing is carried out. Due to this, standards have been developed by international agencies such as the American Society for Testing and Materials (ASTM) and International Organization for Standardization (ISO) to adopt and test plastic materials in both composting and soil environments. The fi rst part of this intended review article deals with the classifi cation of lignocellulosic composites, biodegradation and composting concepts, biodegradability testing standards, and factors affecting biodegradation. A comparative analysis of ASTM and ISO biodegradability standards in terms of testing methodology and results interpretation is provided.. A special focus is given to the biodegradation mechanisms found in polymers and their composites. The second part of this review article is devoted to biodegradation studies of lignocellulosic composites under composting conditions and soil environments. The effect of fi ller type, environmental conditions, and compatibilization on the biodegradation of lignocellulosic composites is discussed in detail. Also, a special section on the biodegradability of lignin-based materials is given.
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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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".