Utilizing Hybrid Plasmon Modes to Probe Nanoparticle-Polymer Interfaces
Bibliographic record
Abstract
Nanoparticle-polymer composite materials have widespread applications in fields such as: sensing, electronics, and biology, due to their desirable physical properties.However, many fabrication techniques render little control over nanoparticle incorporation, and homogeneity of the resulting material.This thesis focuses on the thermally induced embedding of silver nanocubes (AgNCs) into polymer surfaces.The AgNCs were deposited onto polymer films, through a Langmuir approach, which allows fine control over nanoparticle density in the monolayer.The AgNC monolayer was then heated above the glass transition temperature of the polymer, which facilitates the irreversible incorporation of the AgNCs.Embedding of the AgNCs were monitored in real-time, through spatially separated hybrid plasmonic resonances supported by the AgNCs when deposited onto the polymer film, which allowed the determination of a surface layer on top of the bulk polymer with enhanced mobility as well as diffusion constants for the embedding process.support, superior English capabilities, and her one of a kind personality.I would also like to thank my father, for forcing me to take Chemistry and Physics in high school, even though at the time, I thought they were useless.Although we didn't always get along, I am very thankful for the time we had together, you have made me the person I am today, and for that, I am eternally grateful.I would also like to thank my grandparents for their weekly texts, effectively cheerleading me to the finish line.I would like to thank my fellow students and coworkers, whom I've had the privilege to know and work with, specifically, all the current and previous students in the Ianoul lab.With a focus on the graduate students: Ali, Dan, Emma, Adam, and Devin.And of course, all the undergraduate students, especially Joel, and his love of chickens.I would like to doubly thank Emma for her editing expertise and supporting conversations, it made this process considerably less painful.I would also like to thank Jason Coyle, a post doc in the Ianoul lab, for his interesting conversations and supply of Al2O3 coated glass slides.I would like to thank all the people in the department of Chemistry.Specifically, Dr. Jainqun Wang for electron microscopy and his thought provoking insights, Jim Logan for his help in fixing and making various experimental apparatuses, and Chantelle Gravelle for always being available to help.Thank you to the professors
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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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".