A Polyphenol Decorated <i>Triplex</i> Hybrid Biomaterial: Structure–Function, Release Profiles, Sorption, and Antipathogenic Effects
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
Herein, nonwoven alkali modified flax substrates were coated with incremental levels of chitosan, followed by immobilization of tannic acid, via a facile “dip-coating” strategy to yield a unique hierarchal “triplex” hybrid biomaterial, denoted as “THB”. The characterization of the physicochemical properties of THB employed complementary spectroscopic (IR, Raman, and NMR) techniques, which support the role of hydrogen bonding and electrostatic interactions between the components: chitosan as the secondary biopolymer coating and the tertiary adsorbed polyphenols. XRD and SEM techniques provide further structural insight that confirms the unique semicrystalline nature and porous hierarchal structure of the biocomposite. The THBs present a polyphenol kinetic release profile that follows the Korsmeyer-Peppas model that concurs with Fickian diffusion for heterogeneous polymer systems. Furthermore, these systems demonstrate a tailored solvent uptake capacity (up to 4 g/g) in aqueous PBS media. Antipathogenic activity tests revealed 95% elimination of pathogens ( E. coli, S. aureus, and C. albicans ) at a dose of 50 mg for the THB system. The trend in the structure–property relationships for the THB systems indicates synergistic effects of electrostatic multiform interactions between protonated chitosan and the polyphenol units. Herein, we report the first example of a unique hierarchal biomaterial via a facile design strategy for diversiform roles as responsive adsorbents for environmental remediation to biomedical applications (e.g., controlled release, topical administration, or antimicrobial surface coatings).
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.002 | 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