In-situ observation of nucleation and property evolution in films grown with an atmospheric pressure spatial atomic layer deposition system
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Abstract Atmospheric pressure—spatial atomic layer deposition (AP-SALD) is a promising open-air deposition technique for high-throughput manufacturing of nanoscale films, yet the nucleation and property evolution in these films has not been studied in detail. In this work, in situ reflectance spectroscopy was implemented in an AP-SALD system to measure the properties of Zinc oxide (ZnO) and Aluminum oxide (Al 2 O 3 ) films during their deposition. For the first time, this revealed a substrate nucleation period for this technique, where the length of the nucleation time was sensitive to the deposition parameters. The in situ characterization of thickness showed that varying the deposition parameters can achieve a wide range of growth rates (0.1–3 nm/cycle), and the evolution of optical properties throughout film growth was observed. For ZnO, the initial bandgap increased when deposited at lower temperatures and subsequently decreased as the film thickness increased. Similarly, for Al 2 O 3 the refractive index was lower for films deposited at a lower temperature and subsequently increased as the film thickness increased. Notably, where other implementations of reflectance spectroscopy require previous knowledge of the film’s optical properties to fit the spectra to optical dispersion models, the approach developed here utilizes a large range of initial guesses that are inputted into a Levenberg-Marquardt fitting algorithm in parallel to accurately determine both the film thickness and complex refractive index.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 | 0.001 |
| Open science | 0.000 | 0.000 |
| 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 it