Biocompatible poly(N-vinyllactam)-based materials with environmentally-responsive permeability
Bibliographic record
Abstract
Biocompatible polymer-based materials whose properties respond to environmental stimuli are of great value in biomedical and biotechnological applications (e.g., controlled release of drugs and sensitive reactants, bioseparations, spontaneous adjusting of flow of liquids including flow control in microfluidic devices). This study describes preparation and properties of biocompatible poly(N-vinyllactam)-based environment responsive composite membranes. The non-charged network N-vinyl lactam polymers form hydrogels that can exhibit swelling and de-swelling behaviour and, thus, regulate porosity of the membrane. The first part of the study has involved investigation of bulk polymerization reactivity of N-vinylcaprolactam (VCL)-based systems. VCL has been combined with up to 20 mol% of N-vinylpyrrolidone (N-vinylbutyrolactam). These synthetic processes have been investigated as thermal polymerizations (with and without a free-radical initiator) and photopolymerizations. Subsequently, the most reactive systems have been used to prepare composite materials by polymerization-modifying borosilicate microfibre membranes. The modified membranes have been characterized by the net mass gain, infrared spectra, and change in permeability in response to changes in ionic strength of the aqueous media. The permeability experiments have been carried out at constant fluxes and the resultant changes in trans-membrane pressure observed. Those membranes that are ionic-strength responsive could potentially be used for bio-separations and other types of biomedical and biotechnological applications.
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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 | 0.000 | 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".