A World-to-Chip Interface for Digital Microfluidics
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Digital microfluidics (DMF) is a fluid handling technique that enables manipulation of discrete droplets on an array of electrodes. There is considerable enthusiasm for this method because of the potential for array-based screening applications. A limitation for DMF is nonspecific adsorption of reagents to device surfaces. If a given device is used to actuate multiple reagents, this phenomenon can cause undesirable cross-contamination. A second limitation for DMF (and all other microfluidic systems) is the "world-to-chip" interface; it is notoriously difficult to deliver reagents and samples to such systems without compromising the oft-hyped advantages of rapid analyses and reduced reagent consumption. We introduce a new strategy for digital microfluidics, in which a removable plastic "skin" is used to (a) eliminate cross-contamination and (b) bridge the world-to-chip interface. We demonstrated the utility of this format by implementing on-chip protein digestion on immobilized enzyme depots. This new method has the potential to transform DMF from being a curiosity for aficionados into a technology that is useful for biochemical applications at large.
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.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 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 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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 it