Quasistatic response of a shear-thickening foam: Microstructure evolution and infrared thermography
Bibliographic record
Abstract
In this work, the authors study the thermo-mechanical response of a dilatant polymeric foam in quasistatic tension and compression, focusing on the links between microstructure, mechanical response, and associated temperature rises in these materials. The authors study these links for a commercially-available shear-thickening foam, named D3O LITE D. Samples were tested under quasi-static conditions for a strain rate of 0.1 s −1 in tension and compression. Micro X-ray computed tomography (XCT) was used to study the evolution of microstructure (pore size and wall thickness) as a function of strain and this was achieved by developing MATLAB-based programs to analyze these microstructural features. The foam specimens were loaded until failure which allowed for the investigation of the elastic, inelastic, and failure regimes. From the XCT images, pore stretching and cell wall tearing are observed in tension, and buckling and pore collapse are observed in compression. These mechanisms are studied in-situ using an infrared thermal camera which record temperature profiles, and temperature measurements are linked back to stress-strain, and temperature-strain responses. For this material, the tensile yield stress was 0.57 ± 0.10 MPa and the elastic modulus was 5.47 ± 0.10 MPa respectively, at a yield strain of 0.10 ± 0.04. At the time of failure, the average temperature of the specimen was found to increase by ∼3.00°C and a local temperature increase of ∼8.00°C was observed in the failure region. In compression, the elastic collapse stress and elastic modulus were found to be 0.130 ± 0.016 MPa and 2.5 ± 0.2 MPa, respectively. The temperature increase in compression at ∼0.83 strain was ∼0.65°C. These results represent some of the first mechanical properties on shear-thickening foams in the literature, and the discoveries on the linkages between the microstructure and the mechanical properties in this study are important for researchers in materials design and modelling.
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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 | 0.000 | 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 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".