Developing and Characterization of a Biopolymeric Membrane Derived from Mature Banana Peel Biomass
Bibliographic record
Abstract
Biopolymeric films derived from starch are gaining attention due to their potential applications, which are primarily attributed to their availability and biodegradability. Here, we report developing and characterizing a biopolymeric film utilizing banana peel waste (BM2). Analytical techniques were employed, including water absorption analysis, determination of soluble matter, UV-visible absorption spectrophotometry, tensile strength assessment, morphological examination using scanning electron microscopy (SEM), and thermal analysis through thermogravimetric analysis (TGA). The water absorption analysis revealed a noteworthy absorption percentage of 115.23% and 61.75% of soluble matter. The UV-visible absorption spectrophotometry results demonstrated a light absorbance degree ranging from 0.9 to 720 nm, particularly between 400 and 1000 nm. However, the mechanical strength tests indicated relatively low resistance at 0.8 MPa, attributed to the irregular surface observed in the film's morphology as evidenced by scanning electron microscopy (SEM). Thermal analysis conducted via TGA offered valuable insights into the degradation behavior of the film. The findings reveal a degradation temperature ranging from 160 to 300 °C, thereby elucidating the thermal stability of the film and its potential applications. While mechanical limitations were evident, the biopolymeric film derived from banana peel waste demonstrated noteworthy water absorption properties, presenting potential in specific applications, particularly those that do not necessitate elevated mechanical strength. Continued efforts in optimizing and refining the film's structure promise to bolster its mechanical properties, making it suitable for various applications.
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 | 0.000 | 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 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".