Rapid Prototyping of Meso-Scale Fluidic Devices and Masters for PDMS Molding
Bibliographic record
Abstract
We describe a new and simple fabrication method that enables inexpensive and rapid prototyping of meso-scale fluidic systems and interconnect structures between micro- and mesoscale fluidic devices. Devices and systems are designed using simple CAD software and printed in a few minutes using an inexpensive MakerBot 3D printer. Printed structures are used directly or as a master for molding of polydimethylsiloxane (PDMS) structures via soft lithography. Using this method, input and output ports, and interfaces to a meso-scale fluidic board or between meso-scale fluidic components, can be placed with high geometric versatility. Our method offers a costeffective alternative to prototyping of meso-fluidic systems using conventional microfabrication, or using injection-molding/conventional machining of polymers. This paper introduces the MakerBot 3D printer for prototyping of meso-scale fluidic structures and shows a demonstration of interconnect between MakerBot-printed and PDMS structures. Initial results show that the cylinder and hole interconnect structures result in a reversible mechanical and fluidic bond.
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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 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".