Ultrahigh Nanoparticle Stability against Salt, pH, and Solvent with Retained Surface Accessibility via Depletion Stabilization
Bibliographic record
Abstract
For many applications, it is desirable to stabilize colloids over a wide range of buffer conditions while still retaining surface accessibility for adsorption and reaction. Commonly used charge or steric stabilization cannot achieve this goal since the former is sensitive to salt and the latter blocks the particle surface. We use depletion stabilization in the presence of high molecular weight polyethylene glycol (PEG) to stabilize a diverse range of nanomaterials, including gold nanoparticles (from 10 to 100 nm), graphene oxide, quantum dots, silica nanoparticles, and liposomes in the presence of Mg(2+) (>1.6 M), heavy metal ions, extreme pH (pH 1-13), organic solvents, and adsorbed nucleosides and drugs. At the same time, the particle surface remains accessible for adsorption of both small molecules and macromolecules. Based on this study, high loading of thiolated DNA was achieved in one step with just 2% PEG 20,000 in 2 h.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| 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 | 0.001 |
| 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 source (direct Gemma or distilled Codex), 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".