Integrated Digital Microfluidic Platform for Voltammetric Analysis
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 an emerging technique for manipulating small volumes of liquids. DMF is particularly well suited for analytical applications as it allows automated handling of discrete samples, and it has been integrated with several inline analysis techniques. However, examples of the integration of DMF with electroanalytical methods are notably scarce, and those that have been reported rely on external electrodes that impose limitations on complexity. To combine the full capabilities of DMF with voltammetry, we designed a platform featuring a three-electrode electrochemical cell integrated in a microfabricated DMF device, removing the need for external electrodes and allowing for complete droplet control. The performance of the DMF/voltammetry system is comparable to that of a commercial screen printed electrode, and the new platform was applied to generating a calibration series for acetaminophen with a limit of detection of 76 μM and good precision (4% average RSD), all with minimal human intervention. We propose that this platform and variations thereof may be a useful new tool for microscale electroanalysis and will be a complementary system to existing inline analysis techniques for DMF.
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 | 0.001 |
| 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