Spall strength measurements in EPON 828 epoxy and an epoxy/carbon nanotube composite
Bibliographic record
Abstract
Polymer nanocomposites are seeing more frequent use in armor applications. The role of the microstructure on the performance of these materials under dynamic tensile loading is of particular interest. In the present study, plate impact experiments were conducted in order to observe the dynamic response of a neat epoxy (EPON 828) and an epoxy/carbon nanotube composite. The objective was to examine the effect of nano-scale particle inclusions on the spall strength of the composite. The material response was resolved with the combined use of shock pins and a multi-channel photonic Doppler velocimeter. The addition of raw carbon nanotubes (CNT) to epoxy resulted in a composite material with lower spall strengths compared to strengths measured for neat epoxy at elevated shock stresses. Tensile strain rate was found to have the greatest effect on spall strength. Recovered composite fragments were imaged with a scanning electron microscope. Instances of nanotube pull-out were identified on internal fracture surfaces. The low spall strengths of the epoxy/CNT composite were attributed to an increase in the density of potential nucleation sites for spallation caused by presence of the nanotubes in the matrix.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| 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) | 0.001 | 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 source (direct Gemma or distilled Codex), 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".