Bio-plastic from renewable biomass sources
Bibliographic record
Abstract
Bio-plastics are environment – friendly and biodegradable hence provide an effective way to replace the conventional plastics. In this experiment five different crops were taken and then extracted the starch from each crop. Starch is used as a source for producing bio-plastics. Bio-plastic were generated from different starches. Sorghum showed the maximum production of starch (369gm). 15% glycerol is used as a plasticiser and bio-plastics was produced from the extracted starch. Glycerol increases its flexibility. Sodium meta-bisulphate was used as a antimicrobial activity. Maize showed the maximum production of plastic i.e. 28.26 gm. Once the bio-plastics made, the quality parameters were studied. Like tensile strength, elongation test and degradation test. While calculating tensile strength the stretchiness and toughness of that particular bio-plastic sample is important and the tensile strength of maize is 5.80 Mpa found to be maximum among all. An elongation test was carried out, and maximum elongation was takes place in plastic made from potato starch i.e it was elongated about 1.89 cm. In the degradation test the bio-plastic from rice takes more time for degradation. It degrades at the rate of 5.67 gm plastic in 10 days and plastic from sorghum degrades rapidly than other crops. In this study, the experiment conducted in order to produce biodegradable plastic from starch isolated from the different crops. The plastic sample produced may not characteristics of a petrochemical based plastic but it is good in biodegradability. Its tensile strength found that the plastic can be stretched as a conventional plastic. Bio-plastic s doesn’t contain any harmful chemicals. It will help us to protect the environment.
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 | 0.002 | 0.002 |
| 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 | 0.002 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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 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".