Bibliographic record
Abstract
Gel electrophoresis is recognized as a technique to separate nanoparticles based on size, shape and surface charge, and a means to study nanoparticle physicochemical properties. In this thesis, we first developed an electrokinetic model for bare charged sphere electrophoresis in polyelectrolyte hydrogels, addressing the importance of hydrogel permeability and fixed charge. The model identified parameter space where asymptotic approximations in the literature are accurate, and provided strategies to improve nanoparticle size separation by manipulating parameters, such as gel permeability and ionic strength. To interpret gel electrophoresis of polyelectrolyte coated nanoparticles, a theoretical model on soft sphere gel electrophoresis was established, focusing on the role of the polyelectrolyte shell. This electrokinetic model was validated by comparing to bare-particle gel electrophoresis models and free-solution electrophoresis models in the literature, and by fitting to experimental data for gold nanoparticles. It was observed that the gel electrophoretic mobilities of metallic-core particles in polyelectrolyte shells can be qualitatively different than for their non-metallic counterrparts. As indicated by the theoretical models, a low ionic strength may benefit nanoparticle size separation by varying the hydrogel permeability according to the particle charge mechanism, while varying the properties of the polyelectrolyte shell does not enhance separation. Moreover, we presented an experimental study of carboxymethyl PEGylated gold nanoparticle using a two-step synthesis and characterization of nanoparticle properties with various experimental techniques. The carboxymethyl end group was found to influence the nanoparticle hydrodynamic size and ζ-potential.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.015 | 0.019 |
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".