Printing-based fabrication method using sacrificial paper substrates for flexible and wearable microfluidic devices
Bibliographic record
Abstract
Abstract We present a simple, fast, and inexpensive new printing-based fabrication process for flexible and wearable microfluidic channels and devices. Microfluidic devices are fabricated on textiles (fabric) for applications in clothing-based wearable microfluidic sensors and systems. The wearable and flexible microfluidic devices are comprised of water-insoluable screen-printable plastisol polymer. Sheets of paper are used as sacrificial substrates for multiple layers of polymer on the fabric’s surface. Microfluidic devices can be made within a short time using simple processes and inexpensive equipment that includes a laser cutter and a thermal laminator. The fabrication process is characterized to demonstrate control of microfluidic channel thickness and width. Film thickness smaller than 100 micrometers and lateral dimensions smaller than 150 micrometers are demonstrated. A flexible microfluidic mixer is also developed on fabric and successfully tested on both flat and curved surfaces at volumetric flow rates ranging from 5.5–46 ml min −1 .
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.
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 | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".