Xurography as a tool for fabrication of microfluidic devices
Bibliographic record
Abstract
Abstract Microfluidic devices have been conventionally fabricated using traditional photolithography or through the use of soft lithography both of which require multiple complicated steps and a clean room setup. Xurography is an alternative rapid prototyping method which has been used to fabricate microfluidic devices in less than 20–30 minutes. The method is used to pattern two-dimensional pressure-sensitive adhesives, polymer sheets, and metal films using a cutting plotter and these layers are bonded together using methods including adhesive, thermal, and solvent bonding. This review discusses the working principle of xurography along with a critical analysis of parameters affecting the patterning process, various materials patterned using xurography, and their applications. Xurography can be used in the fabrication of microfluidic devices using four main approaches: making multiple layered devices, fabrication of micromolds, making masks, and integration of electrodes into microfluidic devices. We have also briefly discussed the bonding methods for assembling the two-dimensional patterned layers. Due to its simplicity and the ability to easily integrate multiple materials, xurography is likely to grow in prominence as a method for fabrication of microfluidic devices.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 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".