The Additive Manufacturing Approach to Polydimethylsiloxane (PDMS) Microfluidic Devices: Review and Future Directions
Bibliographic record
Abstract
This paper presents a comprehensive review of the literature for fabricating PDMS microfluidic devices by employing additive manufacturing (AM) processes. AM processes for PDMS microfluidic devices are first classified into (i) the direct printing approach and (ii) the indirect printing approach. The scope of the review covers both approaches, though the focus is on the printed mold approach, which is a kind of the so-called replica mold approach or soft lithography approach. This approach is, in essence, casting PDMS materials with the mold which is printed. The paper also includes our on-going effort on the printed mold approach. The main contribution of this paper is the identification of knowledge gaps and elaboration of future work toward closing the knowledge gaps in fabrication of PDMS microfluidic devices. The second contribution is the development of a novel classification of AM processes from design thinking. There is also a contribution in clarifying confusion in the literature regarding the soft lithography technique; this classification has provided a consistent ontology in the sub-field of the fabrication of microfluidic devices involving AM processes.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.005 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 0.002 |
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".