Ageing, optical and life-cycle analysis of clay-reinforced cassava starch biocomposites
Bibliographic record
Abstract
Bioplastics’ life cycle assessment (LCA) is a vital tool for evaluating their environmental impact. It makes it possible to measure the consequences throughout the life cycle, from creation to the end of life. New composites are increasingly tending to be part of a circular economy. It is therefore essential to know how they behave (production, processing, uses, ageing, composting, etc.) throughout the recovery cycle. Additives make it simple to plastify starch, a naturally occurring polymer. However, the primary characteristics of thermoplastic starch-based polymers are their high-water sensitivity and malleable mechanical qualities. For packing purposes, they are either heat-treated or not, and strengthened with kaolin and metakaolin. The objective of this work is to evaluate the life cycle and aging of clay-reinforced cassava starch-based biocomposites. To do this, a clay denoted KB from Bonoua composed mainly of quartz (14 %) and clay minerals kaolinite (75 %) and illite (11 %) and cassava starch (powder) with a median diameter of 19 μm were used. The biocomposites developed by the evaporative casting method were reinforced with kaolin (noted BPKB) and metakaolin (heat-treated kaolin at 700 °C/1h) (noted BPMKB). Based on investigations into thermal, optical, and biodegradation processes, it seems that in the UV-B, UV-A, and visible spectrums, biocomposites become most opaque at wavelengths of 300 nm, 350 nm, and 750 nm. Kaolin and metakaolin reinforced biocomposites (BPKB and BPMKB) are resistant up to 150 °C. Biocomposites placed in the soil or on the surface degrade up to 98 % (m/m). Degraded biocomposites can be used as compost and fertilizer for cassava crops.
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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 | 0.000 |
| 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 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".