Stabilization of Neodymium Oxide Nanoparticles via Soft Adsorption of Charged Polymers
Bibliographic record
Abstract
In this work, two synthetic polyelectrolytes, PSS and PAH, are employed as strong adsorbed surfactants to disperse and stabilize neodymium oxide nanoparticles. The acid-base equilibria of the oxide surfaces of the particles were investigated under different pH conditions in the absence and presence of polyelectrolytes, to optimize particle stabilization through enhancement of the effective repulsive surface charges. Surface charge amplification of a 3:5 ratio was achieved to permit improved particle transparency of 100-fold in visible wavelengths in neutral and acidic pH regimes, and a stable 10-fold surface charge amplification was achieved under basic pH conditions. The potential of polyelectrolytes as stabilizing agents for neodymium oxide NPs in large-scale particle physics experiments requiring extremely high optical transparency over long path length is evaluated based on optical absorbance and particle stability.
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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 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".