Silver nanoparticles-containing dual-function hydrogels based on a guar gum-sodium borohydride system
Bibliographic record
Abstract
Abstract Dual-function hydrogels, possessing both stimuli-responsive and self-healing properties, have recently attracted attention of both chemists and materials scientists. Here we report a new paradigm using natural polymer (guar gum, GG) and sodium borohydride (NaBH4), for the preparation of silver nanoparticles (AgNPs)-containing smart hydrogels in a simple, fast and economical way. NaBH4 performs as a reducing agent for AgNPs synthesis using silver nitrate (AgNO3) as the precursor. Meanwhile, sodium metaborate (NaBO2) (from NaBH4) behaves as a cross-linking agent between GG molecular chains. The AgNPs/GG hydrogels with excellent viscoelastic properties can be obtained within 3 min at room temperature without the addition of other cross-linkers. The resultant AgNPs/GG hydrogels are flowable and injectable, and they possess excellent pH/thermal responsive properties. Additionally, they exhibit rapid self-healing capacity. This work introduces a facile and scale-up way to prepare a class of hydrogels that can have great potential to biomedical and other industrial 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) | 0.000 | 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".