Miniaturized platform with on-chip strain sensors for compression testing of arrayed materials
Bibliographic record
Abstract
We report a microfabricated mechanical testing platform with on-chip strain sensors for in situ mechanical characterization of arrayed materials. The device is based on deformable elastomeric membranes that are actuated by pressure that is delivered through an underlying channel network. The bulging membranes compress material samples that are confined between the membranes and a rigid top-plate. Carbon nanotube-based strain sensors that exhibit strain-dependent electrical resistivity were integrated within the membranes to provide continuous read-out of membrane deflection amplitude. We used this platform to study the cyclic compression of several different silicone samples and thereby measured their elastic moduli. The results obtained using our miniaturized platform were in excellent agreement with those obtained using a commercially available mechanical testing platform and clearly demonstrated the utility of our platform for the mechanical testing of small samples in parallel. The miniaturized platform can significantly increase mechanical testing efficiency, particularly when testing of iterative sample formulations is required.
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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".