Hydrogel Microelectromechanical System (MEMS) Resonators: Beyond Cost‐Effective Sensing Platform
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Abstract Mechanical resonators have been used for various applications including timing references, filters, accelerometers, and inertial sensors. Mostly, silicon‐based materials have been thought to be ideal considering robustness and stability and thus used to fabricate micro and nanoscale mechanical resonators. When enhanced sensitivity becomes more important than long‐term stability, materials repertoires other than silicon might be better suited. Herein, a novel manufacturing approach is proposed, which rapidly fabricates microelectromechanical system resonators with hydrogel by single UV exposure via dynamic mask and dry‐state “plugging out” sacrificial process where hydrogel structures are defined by spatially modulated UV light. For practical demonstrations, rectangular cantilevers and closed circular membranes are employed for humidity and pressure sensing applications, respectively. The cost‐effective fabrication route suggested herein not only enables rapid prototyping of suspended hydrogel structures outside a cleanroom, but also offers spatially tunable elastic modulus. Most remarkably, sensitivity enhancement resulting from high swelling rate and/or low elastic modulus exceeds stability deterioration, one of the major concerns for polymeric materials. Such exclusive beneficial features, yet demonstrated with any microfabrication materials and methods or their combinations, open a new avenue for photocurable polymeric materials to be used for specific applications as well as fundamental investigations.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 |
| 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 | 0.001 |
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 it