Nanoindentation Investigation on Chitosan Thin Films with Different Types of Nano Fillers
Bibliographic record
Abstract
Chitosan nanocomposite thin films were fabricated using two types of chitosan natural polymer (cross-linked chitosan (CLCS) and non-cross-linked chitosan (NCLCS)), with three different weight percentages nano-fillers (Graphene (G) and fullerene (F)). Nanoindentation tests were performed to investigate the local mechanical properties of the produced nanocomposite in comparison to the unreinforced chitosan thin films. Nano hardness values (H) and indentation modulus (E) were measured using 5 and 10 µm spherical indenters. The addition of nano fillers enhanced the hardness of both types of films with the amount of hardening being directly proportional to the fraction of nano filler added(p<0.001). Crosslinking has also significantly increased the hardness (p< 0.001). The larger indentation returned a lower hardness. The use of different radii nano indenters underlined the indenter size effect due to the differing strain fields. The promising mechanical properties resulting from this research will allow using the fabricated nanocomposites for tissue engineering, biomedicine, drug delivery, electronics, energy, surface coatings and packaging applications.
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How this classification was reachedexpand
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 | 0.005 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.002 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 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 teacher head, 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".