Sol-Gel Derived Single Layer Zeolite-MgF2 Composite Antireflective Coatings with Improved Mechanical Properties on Polycarbonate
Bibliographic record
Abstract
Single layer antireflective coatings with good optical and mechanical properties are difficult to be obtained on temperature sensitive substrates like plastics. This challenge has been taken up in the present study. Single layer MgF2 and for the first time, zeolite 4Å and zeolite 4Å - MgF2 composite antireflective coatings were generated by a wet chemical route on flat polycarbonate sheets and characterized for their reflectance, surface roughness, thickness, porosity, surface morphology and scratch hardness by haze measurement. Autoclaving and boiling water treatment under microwave irradiation were used in case of MgF2 sols and zeolite/zeolite-MgF2 coatings respectively. Pure MgF2 coatings deposited after autoclaving of the MgF2 sol yielded a low refractive index of 1.28 and an average reflectance of 1.9% vis-à-vis 9.7% reflectance for an uncoated polycarbonate substrate over the wavelength range of 400-1100 nm. Single layer zeolite coatings after a brief treatment in boiling water under microwave irradiation yielded a reflectance of 5.1%. A composite zeolite-MgF2 coating exhibited a reflectance of 2.8% and the percentage change in haze after crockmeter testing in case of the composite coating was lower than that of a pure MgF2 coating. This implied that the composite layer had improved mechanical properties combined with good optical properties and could be suitable for practical applications.
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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) | 0.001 | 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".