Multicharged Zwitterions form Superior Antifouling Interfaces
Bibliographic record
Abstract
The long-term prevention of unwanted protein and microbial accumulation on surfaces, including medical devices, remains a significant and largely unresolved challenge. Decades of research into antifouling surfaces have suggested that addressing this issue will require a sustained approach focused on incremental advances in chemical design. The creation of highly hydrophilic surfaces has long been recognized as a key strategy, initially pursued through polyethylene glycol-functionalized coatings. More recently, zwitterionic groups have emerged as effective antifouling moieties. However, the limited chemical diversity of zwitterion-forming chemical entities has constrained further progress. In this study, an alternative approach to enhancing surface hydrophilicity is presented by employing multicharged zwitterionic molecules (MZWs), which increase the density of charged hydrophilic groups per monomer unit. Surfaces functionalized with MZWs exhibited 40-45% lower protein adsorption compared to benchmark single zwitterionic molecules. Remarkably, the synthesized MZWs spontaneously assemble into vesicular aggregates (130-170 nm) without the need for additives or any form of external force. These findings strongly support further exploration of MZW-functionalization as a novel strategy to enhance antifouling performance, while remaining readily adaptable via minor modifications to existing synthetic routes used for the incorporation of conventional zwitterions into polymers, self-assembled monolayers, hydrogels, and nanocarriers.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 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".