Properties of Biopolymer Films in Ionic Solutions and their Applications as 3D Printed Personalized Wound Dressings
Bibliographic record
Abstract
This thesis describes the effects of ionic solutions on biopolymer films and the development of a 3D printed personalized wound dressing. Chitosan, gelatin, and composite chitosan/gelatin films were exposed to NaCl, Na2SO4, and CaCl2 solutions with varying ionic strength and their swelling and dissolution properties were measured. In addition, the release of the small ionic molecules Rhodamine B and Eosin Y from films into NaCl solutions of varying ionic strength was monitored. Next, a shear-thinning mixture of cellulose nanocrystals and chitosan-methacrylate was extruded with various patterns and polymerized by ultraviolet light irradiation or elevated temperature to form hydrogel wound dressings. Antimicrobial silver nanoparticles, a model protein (bovine serum albumin), and an antibiotic (gentamicin) were added to the hydrogel mixtures and their release from the dressings was monitored. In addition, phenol red-methacrylate was co-polymerized into the hydrogel dressing and exhibited a pH-responsive colour change suitable for the detection of infection.
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) | 0.001 | 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".