Development and modeling of an ultra-robust TPU-MWCNT foam with high flexibility and compressibility
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
Abstract Developing a cost-effective industrially scalable manufacturing method that can improve the mechanical properties of nanocomposite foams with higher flexibility, compressibility, and, at the same time, mechanically robustness is of significant interest. In this study, porous thermoplastic polyurethane (TPU)/multiwalled carbon nanotube (MWCNT) was fabricated with the chemical blowing agent (CBA) by a combination of compounding-compression molding methods. The effects of CBA and MWCNT contents on the foam morphology, porosity, foam cell size, Young’s modulus, and compressibility of fabricated samples were investigated. Through conducting cyclic compressive tests, it was observed that nanocomposite foams exhibited consistent mechanical responses across multiple compressive cycles and demonstrated notable characteristics, including high compressibility (up to 76.4% compressive strain) and high elastic modulus (up to 8.8 ± 2.6 MPa). Moreover, theoretical approaches were employed to predict the elastic modulus of solid and foam TPU/MWCNT. For solid MWCNT/TPU, a specific micromechanical model based on different modifications of the Halpin-Tsai (HT) approach was used, which showed a good agreement with experimental data at different MWCNT contents. Furthermore, the constant parameters of Gibson and Ashby’s method were found to successfully predict the elastic modulus of foam TPU/MWCNT at different MWCNT and CBA percentages.
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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) | 0.000 | 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 it