Strain Transfer Analysis of Surface-Bonded MEMS Strain Sensors
Bibliographic record
Abstract
The transmission of strain fields in adhesively bonded MEMS strain sensors is analyzed. In strain sensors that are attached to host structures using adhesive layers such as epoxy, complete strain transfer to the sensor is hindered due to the influence of the adhesive layer on the transfer. This paper presents an analytical model, validated by finite element method simulation, to provide insight and accurate formulation for strain transfer mechanism for bonded sensors. A shear-lag parameter has been introduced to account for the component geometry and properties. The model is capable of predicting the strain transmission ratio through a sensor gauge factor, and it clearly establishes the effects of the flexibility, length, and thickness of the adhesive layer and MEMS sensor substrate. Finally, modifications to sensor substrates, by the implementation of micromachined tapered edges and trench etching, are proposed in order to increase the strain transmission ratio. It has been found, for the selected case study, that the sensor sensitivity could be enhanced by up to 30%. This work on bonding analysis is applicable for performance prediction and calibration in sensor systems design.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".