Investigation of moisture absorption and long-term properties of carbon nanotube-reinforced vinyl-ester composites
Bibliographic record
Abstract
Vinyl-ester resin (VE) is a polymer matrix frequently used in several civil applications, but its long-term properties in humid and harsh environments can be a concern. Carbon nanotubes (CNTs) have remarkable mechanical, physical, and thermal properties. Adding them to the resin is a promising solution and makes it possible to manufacture cost-effective products with enhanced engineering properties. Our study investigated the chemical functionalization of multi-wall carbon nanotubes (MWCNTs) through acid oxidation to evaluate the durability-related properties of vinyl-ester-based nanocomposites. Samples containing 0.1 wt% of as-received CNTs and functionalized CNTs were characterized by scanning electron microscopy (SEM), elemental analysis, and X-ray photoelectron spectroscopy (XPS). A small amount of two dispersing agents (BYK 104S and BYK 9076) was added to the mixtures to produce high particle stability in the nanocomposites. Barrier properties and moisture diffusivity were determined by immersing samples in a water bath at 50°C. Aging was conducted by fully immersing samples in NaOH solution at 50°C. Matrix degradation was assessed with tensile tests, dynamic mechanical analysis (DMA), and differential scanning calorimetry (DSC) before and after conditioning. The results indicate that the addition of oxidized CNTs significantly improved the mechanical, physical, and durability properties of the composites. Additionally, unlike nanoclay-based nanocomposites, oxidized CNTs do not increase water absorption at saturation.
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.
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 | 0.000 | 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 | 0.000 | 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 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".