Fabrication of Thickness Modulated Multilayer Thin Film Optical Filters for Color Rendering in Photovoltaics Using Ecr-PECVD and Magnetron Sputtering
Notice bibliographique
Résumé
Electric vehicles’ usage can reduce greenhouse gas emissions and their adverse health effects on humans. But we can only utilize the full environmental benefits of them when charging is done using renewable energy sources with zero or low carbon emissions. Researchers have suggested integrating low-cost, flexible, and thin-film copper indium gallium selenide solar cells directly onto all the upward-facing body parts of electric vehicles [1]. However, this integration comes with an aesthetic drawback. We are proposing replacing the anti-reflective coating present in standard solar cells with a notch filter (a narrow high-reflection region in the visible range along with high transmission for the rest of the solar spectrum) to give a distinct color rendering to solar-charged electric vehicles. Notch filters can be designed using a rugate filter structure consisting of continuously modulated refractive indices or using a repetitive two-material stack of alternating high (H) and low (L) refractive index materials with precise thickness, also known as the standard two-material technology (S2MT). Using OptiLayer and MATLAB, we designed our S2MT thickness modulated structures to obtain blue (400 nm), green (550 nm), and red (632 nm) colors with minimum number of layers. Layer numbers in each design range between 2 – 12 depending on the chosen material pair and the targeted color, thus achieving simplicity and effectiveness. We used gradual evolution method followed by thin layer removal to obtain our thickness modulated multilayer optical filter designs. We simulated our optical filter structures for various high and low refractive index material pairs, and a detailed analysis of our findings will be presented. In this analysis, we studied the effect of refractive index ratios (high refractive index to low refractive index) on the current response of the colorful solar cells and our merit function. This study helped us to understand the optimal material pair range suitable to our application. Our designs were fabricated using magnetron sputtering and electron cyclotron resonance plasma-enhanced chemical vapor deposition (ECR-PECVD) and validated through variable angle spectroscopic ellipsometry and reflectance spectroscopy, showing strong agreement with our simulations. We fabricated these optical filters with three different material pairs using ECR-PECVD (SiN-SiON, refractive index ratio of 1.38 [2]) and magnetron sputtering (Nb2O5-SiO2, with refractive index ratio of 1.71 [3] and Al2O3-SiO2, with a refractive index ratio of 1.21). With a minimal trade-off in the functionality and efficiency of solar cells, we were successfully able to transform standard solar cells into aesthetically pleasing components, broadening their appeal and potential applications in consumer products. A detailed comparison of our simulation and fabrication results will be presented. Figure 1: Observed color of the fabricated (a) blue, (b) green, and (c) red filter on silicon wafer using a solar simulator under 1 sun condition. [3] References: [1] M. H. Mobarak, R. N. Kleiman, and J. Bauman, “Solar-Charged Electric Vehicles: A Comprehensive Analysis of Grid, Driver, and Environmental Benefits,” IEEE Transactions on Transportation Electrification , vol. 7, no. 2, pp. 579–603, Jun. 2021, doi: 10.1109/TTE.2020.2996363. [2] P. Bhattacharyya, B. Ahammou, F. Azmi, R. Kleiman, and P. Mascher, “Design and fabrication of color-generating nitride based thin-film optical filters for photovoltaic applications,” Journal of Vacuum Science & Technology A , vol. 41, no. 3, May 2023, doi: 10.1116/6.0002357. [3] P. Bhattacharyya et al. , “Design method for generating multiple colors with thickness-modulated thin-film optical filters for silicon solar cells,” Journal of Vacuum Science & Technology A , vol. 43, no. 1, Jan. 2025, doi: 10.1116/6.0003977. Figure 1
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Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,000 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,001 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,001 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».