Constructing pristine and modified cellulose nanocrystals based cured polychloroprene nanocomposite films for dipped goods application
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
In this work, polychloroprene rubber (CR) nanocomposite films reinforced with native and modified cellulose nanocrystals (CNCs) were evaluated for dipped goods applications. The CNC modification, with a goal of enhancing the interaction between the CNC and CR, was conducted by surface graft polymerization of lactic acid. The films were then prepared by latex blending, casting, and curing (with ZnO/MgO). TEM studies displayed that the CNCs formed a partially structured network while modified CNCs (mCNCs) tend to disperse mostly individually in the polychloroprene and show percolation at 3 wt%. Tensile tests of the films showed a substantial increase in the modulus, tensile strength, and tear resistance for both CNC, and mCNC reinforced films while the elongation at break remained above 600%. The films made with CNCs and mCNCs exhibited similar acetone vapor permeability at different loadings of the filler. However, their permeability towards water and 2-propanol vapor increased steadily with an increase in CNCs loading. In contrast, the mCNC-based films displayed steady permeability and a surge at 3 wt%, which could be attributed to percolation. Overall, the fabrication of CNC and mCNC reinforced CR films demonstrated appealing physical properties for a range of dipped goods applications.
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.002 |
| 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 it