Biodegradable Polylactide/Chitosan Blend Membranes
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Biodegradable blend membranes based on polylactide and chitosan with various compositions were prepared via a two-step processing pathway. In the first step, solutions of each component were properly mixed and cast into a gelatinous membrane, and in the second step, the obtained membrane was immersed into a mixed solution for the solvent extraction followed by a drying procedure to finally generate a well-blended membrane. An acetic acid-acetone solvent system was selected for poly(DL-lactide)/chitosan membranes, and another solvent system for poly(L-lactide)/chitosan membranes consisted of acetic acid and dimethyl sulfoxide. Some processing parameters, such as the concentration of component solutions and the composition ratio of mixed solvents and extraction solvents, were optimized by primarily considering whether the directly visible phase separation occurred during the processing procedures. Morphologies of these blend membranes were viewed using SEM. It was found that the processing parameters exerted quite notable impacts on the morphology of the membranes. The hydrophilicity of membranes was examined by measuring their water contact angle and swelling index. These blend membranes were also investigated for their miscibility using IR spectra, X-ray diffractograms, TG, DSC, and dynamic mechanical analysis methods. Although the presence of phase separation at a microscopic level was detected for these membranes, pronounced interactions between components were confirmed. The obtained results shown that some membranes prepared under optimized processing conditions had a partially miscible structure.
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.
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 | 0.000 | 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) | 0.001 | 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 it