In-Situ Ellipsometric Study of the Optical Properties of LTL-Doped Thin Film Sensors for Copper(II) Ion Detection
Bibliographic record
Abstract
Optical sensors fabricated in zeolite nanoparticle composite films rely on changes in their optical properties (refractive index, n, and thickness, d) to produce a measurable response in the presence of a target analyte. Here, ellipsometry is used to characterize the changes in optical properties of Linde Type L (LTL) zeolite thin films in the presence of Cu2+ ions in solution, with a view to improving the design of optical sensors that involve the change of n and/or d due to the adsorption of Cu2+ ions. The suitability of two different ellipsometry techniques (single wavelength and spectroscopic) for the evaluation of changes in n and d of both undoped and zeolite-doped films during exposure to water and Cu2+-containing solutions was investigated. The influence of pre-immersion thermal treatment conditions on sensor response was also studied. Due to the high temporal resolution, single wavelength ellipsometry facilitated the identification of a Cu2+ concentration response immediately after Cu2+ introduction, indicating that the single wavelength technique is suitable for dynamic studies of sensor–analyte interactions over short time scales. In comparison, spectroscopic ellipsometry produced a robust analysis of absolute changes in film n and d, as well as yielding insight into the net influence of competing and simultaneous changes in n and d inside the zeolite-doped films arising due to water adsorption and the ion exchange of potassium (K+) cations by copper (Cu2+).
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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".