Fabrication of Porous Polymer Monoliths in Polymeric Microfluidic Chips as an Electrospray Emitter for Direct Coupling to Mass Spectrometry
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
Coupling of polymeric microfluidic devices to mass spectrometry is reported using porous polymer monoliths (PPM) as nanoelectrospray emitters. Lauryl acrylate-co-ethylene dimethacrylate porous polymer monolith was photopatterned for 5 mm at the end of the channel of microfluidic devices fabricated from three different polymeric substrate materials, including the following: poly(dimethylsiloxane) (PDMS), poly(methyl methacrylate) (PMMA), and cyclic olefin copolymer (COC). Spraying directly from the end of the chip removes any dead volume associated with inserted emitters or transfer lines, and the presence of multiple pathways in the PPM prevents the clogging of the channels, which is a common problem in conventional nanospray emitters. Spraying from a microfluidic channel having a PPM emitter produced a substantial increase in TIC stability and increased sensitivity by as much as 70x compared to spraying from an open end chip with no PPM. The performance of PPM emitter in COC, PMMA, and PDMS chips was compared in terms of stability and reproducibility of the electrospray. COC chips showed the highest reproducibility in terms of chip-to-chip performance, which can be attributed to the ease and reproducibility of the PPM formation due to the favorable optical and chemical properties of COC. We have further tested the performance of the COC chips by constant infusion of poly(propylene glycol) solution at organic content ranging from 10 to 90% methanol and at flow rates ranging from 50 to 1000 nL/min, showing optimum spraying conditions (RSD < 5%) at 50-70% organic content and at flow rates from 100 to 500 nL/min. The PPM sprayer was also used for protein preconcentration and desalting prior to mass spectrometric detection, and results were comparable with a chip spraying from an electrospray tip.
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