Electrical Conductivity Extracted From Optical Characterization of Polysilicon Films
Notice bibliographique
Résumé
The purpose of this work is to investigate the optical properties of polycrystalline silicon layers by means of spectroscopic Ellipsometry and other techniques to sustain the analysis (SEM, AFM and Hall effect).The studied MOS structures are composed of c-Si substrate(p-type, Cz<100> oriented), silicon oxide layer (100nm) and polysilicon film (175nm deposited by LPCVD at 625°C) with several doping levels(from 2x1019 to 3x1020 cm-3).A five-layers structure model has been applied, including in addition to MOS structure, a native oxide layer and an effective medium approximation (EMA) roughness layer based on linear growth of air medium. A Cauchy layer model was used to compute the optical parameters (for 400-900 nm wavelength range). The fitting sessions lead to good results as the theoretical and experimental ellipsometric angles curves superposed to each other. The total error was lowered to its minimum during fitting process, by reducing the partial errors on which one can act, like fixed values, misalignment of the angle of incidence [1], bad software convergence, specific measuring error,; and so on. Firstly, the SEM images correlated with AFM ones, of the doped or undoped deposited polysilicon, show sugar loaf shaped surface crystallites, like it appears in reference [2]. The Ellipsometry study showed that the polySi layer roughness has undergone a growth under the effect of the phosphorus thermal diffusion. It increases from 22.2 Å to a value between 23 and 58 Å, depending on the doping level, which agrees with SEM/AFM characterizations and what has been published elsewhere [3,4], in case of the temperature deposition of 625°C. Secondly, one noticed that ellipsometric angles curves were regularly shifted towards low wavelengths when the electrical conductivity increases and the wavelengths gap between the extrema angles, for the same curve, was monotonically decreasing in the same situation. Besides, Psi angle maxima and minima were growing till the doping level reaches a limit (when approaching the phosphorus solubility limit), then started to diminish. On the other hand, the Mean Square Error (MSE) [5,6], when determined between experimental curves, after and before phosphorus diffusion, linearly increases with conductivity enhancement. We took advantage of these curves properties for determining of the electrical conductivity (and resistivity) of the deposited PolySi films, by means of simple relationships between the latter, on the one hand, and the ellipsometric angles extrema and associated wavelengths, on the other hand. Even if this method is not a straightforward manner to extract the conductivity, it remains a good way to avoid electrical contacts on samples, mainly in case of small areas. The evolution of Delta and Psi curves (shift and extrema values variation) can be related to two main influent sources. In the first place, the evolution of the free electrons concentration modifies the complex refractive index in accordance to the Drude theory (correlation between SE and HE measurements). Secondly, the polysilicon layer crystallinity and roughness increase with the doping level, following the thermal budget during the diffusion process. Thirdly, the characterizations confirmed that the refractive index is reduced by the doping process, and that it is all lower as the phosphorus doping level is higher. In addition, we noticed that refractive indices evolution are, in all cases, in agreement with model that has been published in[7], in other words their values decrease on Vis-NIR domain, in accordance with a seven-terms polynomial function n2 = f (λ2), with alternate signs. Furthermore, the seven parameters fall on Gaussian curves and are very depending on the doping and the polysilicon layer thickness.
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,000 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,001 |
| 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 | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 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 tête enseignante, 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 ».