(Invited) Microfabricated Nanocomposite Polymers and Thin Films for Flexible Substrate Microfluidics and MEMS
Bibliographic record
Abstract
While many materials have been employed to fabricate microelectromechanical systems (MEMS) and microfluidic systems for lab-on-a-chip, polymers are under increasing focus to realize highly flexible microinstrumentation that can conform to the body or other surfaces. Polymers are also optically transparent, biocompatible, and inexpensive. For MEMS and microfluidics, active devices such as actuators, as well as conductive tracks for read-out and control electronics, are also required, but may be difficult to implement on polymers. This paper discusses new approaches to the development of highly flexible MEMS and microfluidics, including highly conductive and magnetic nanocomposite polymers for active devices and conductive tracks. Hybrid systems fabrication employing these polymers, as well as fabrication of thin-film-metal-on-polymer devices, is also presented. The preparation, micropatterning, and integration of the different polymers is discussed, together with materials characterization, and example devices including: flexible printed circuit boards; sensor microelectrodes; and micromagnets for miniaturized actuators and microfluidic interconnect structures.
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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) | 0.001 | 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 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.020 | 0.011 |
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".