Rapid bench-top fabrication of poly(dimethylsiloxane)/polystyrene microfluidic devices incorporating high-surface-area sensing electrodes
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
The development of widely applicable point-of-care sensing and diagnostic devices can benefit from simple and inexpensive fabrication techniques that expedite the design, testing, and implementation of lab-on-a-chip devices. In particular, electrodes integrated within microfluidic devices enable the use of electrochemical techniques for the label-free detection of relevant analytes. This work presents a novel, simple, and cost-effective bench-top approach for the integration of high surface area three-dimensional structured electrodes fabricated on polystyrene (PS) within poly(dimethylsiloxane) (PDMS)-based microfluidics. Optimization of PS-PDMS bonding results in integrated devices that perform well under pressure and fluidic flow stress. Furthermore, the fabrication and bonding processes are shown to have no effect on sensing electrode performance. Finally, the on-chip sensing capabilities of a three-electrode electrochemical cell are demonstrated with a model redox compound, where the high surface area structured electrodes exhibit ultra-high sensitivity. We propose that the developed approach can significantly expedite and reduce the cost of fabrication of sensing devices where arrays of functionalized electrodes can be used for point-of-care analysis and diagnostics.
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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