Nonfouling Hydrophilic Poly(ethylene glycol) Engraftment Strategy for PDMS/SU-8 Heterogeneous Microfluidic Devices
Bibliographic record
Abstract
We report a novel nonfouling passivation method using poly(ethylene glycol) (PEG) engraftment on the surfaces of poly(dimethylsiloxane) (PDMS) microfluidic devices sealed with SU-8. To achieve bonding between the PDMS and SU-8 surfaces, the PDMS surface was first functionalized with amines by treatment with 3-aminopropyltrimethoxysilane (APTMS) for subsequent reaction with epoxide functional groups on SU-8 surfaces. To modify the heterogeneous surfaces of the resulting PDMS/SU-8 microfluidic device further, the remaining SU-8 surfaces were amino functionalized using ethylene diamine (EDA), followed by treating both amino-functionalized PDMS and SU-8 surfaces with mPEG-NHS (N-hydroxysuccinimide) through an amine-NHS reaction for facile PEG immobilizations, thus simultaneously modifying both PDMS and SU-8 surfaces in one reaction. Detailed surface analyses such as the water contact angle, X-ray photoelectron spectroscopy (XPS), and atomic force microscopy (AFM) were conducted to confirm the chemical reactions and characterize the resulting surface properties. To test the efficacy of this surface-modification strategy, we conducted nonspecific protein and particle binding tests using microfluidic devices with and without modifications. The PEG-modified PDMS/SU-8 device surfaces showed a 64.5% reduction in nonspecific bovine serum albumin (BSA) adsorption in comparison to that of the unmodified surfaces and 92.0 and 95.8% reductions in microbead adhesion under both stagnant and flowing conditions, respectively.
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How this classification was reachedexpand
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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".