Paper-based piezoresistive MEMS force sensors
Bibliographic record
Abstract
This paper describes the development of piezoresistive MEMS force sensors constructed using paper as the structural material. The sensing principle of the paper-based sensor is based on the piezoresistive effect of conductive materials patterned on a paper substrate. The device is inexpensive (~$0.04/device for materials), simple to fabricate, lightweight, and disposable. The entire fabrication process can be completed within one hour in common laboratories with simple tools (e.g., a paper cutter and a painting knife), without requiring cleanroom facilities. The paper substrate allows easy integration of electrical signal processing circuits onto the paper-based MEMS devices. We demonstrated that the paper-based sensor can measure forces with moderate performance (i.e., detection limit: 120 μN, measurement range: ±16 mN, and sensitivity: 0.84 mV/mN), and applied the sensor to characterizing mechanical properties of soft materials. We also developed a paper-based weighting balance with a measurement range of 15 g and a resolution of 25 mg.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".