µPump: An open-source pressure pump for precision fluid handling in microfluidics
Bibliographic record
Abstract
An open-source precision pressure pump system and control software is presented, primarily designed for the experimental microfluidics community, although others may find additional uses for this precision pressure source. This mechatronic system is coined 'µPump,' and its performance rivals that of commercially available systems, at a fraction of the cost. The pressure accuracy, stability, and resolution are 0.09%, 0.02%, and 0.02% of the full span, respectively. The settling time to reach 2 bar from zero and stabilize is less than 2 s. Material for building a four-channel µPump (approx. $3000 USD) or an eight-channel µPump (approx. $5000 USD) is approximately a quarter, or a third of the cost of buying a high-end commercial system, respectively. The design rationale is presented, together with documented design details and software, so that the system may be replicated or customized to particular applications. µPump can be used for two-phase droplet microfluidics, single-phase microfluidics, gaseous flow microfluidics and any other applications requiring precise fluid handling. µPump provides researchers, students, and startups with a cost-effective solution for precise fluid control.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.023 | 0.012 |
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".