Notice bibliographique
Résumé
The primary objective of the work described in this thesis was to study the influence of undoped LEC GaAs substrate material from various suppliers on the performance of ion implanted and annealed active layers. Optical transient current spectroscopy (OTCS) was investigated as a qualification test for GaAs substrates. Deep level spectra of the substrates before ion implantation were obtained. It was found that while the OTCS spectra of high pressure grown GaAs from two suppliers were similar, that of the low pressure material showed different relative concentration of traps. The use of OTCS was further extended to study trap concentration as a function of surface treatment. It was found that the use of chemical etchants reduces the concentration of some levels, possibly those located on the surface as opposed to bulk traps. Surface damage was found to enhance the negative peak in the OTCS spectrum. The deep levels spectra were found to be affected by the geometry of the device and the type of electrode material. Channel current deep level transient spectroscopy (DLTS) was used to study both process- and substrate-induced deep levels in ion implanted MESFET channels. The spectra of process-induced traps were found to be different according to the encapsulant used. Silicon dioxide (both RF sputtered and plasma enhanced chemically vapor deposited (PECVD)) was found to induce a variety of process related defects. This is believed to be because silicon dioxide is permeable to gallium and hence does not preserve the stoichiometry of ion implanted GaAs during high temperature anneals. Deep level spectra of MESFETs annealed using silicon nitride, on the other hand, were found to contain single traps related to the defects in the starting material. For implants through silicon nitride, a high concentration of the main electron trap EL2 was found, whereas implants directly into the surface resulted in the level EL12. Comparison of the characteristics of the variety of LEC undoped GaAs material show that they differed widely and had inhomogeneous properties. For example, compared to the high pressure grown GaAs, the Litton’s low pressure substrate had lower activation, mobility, drain current and threshold voltage, good confinement of the scatter in the same characteristics, low concentration of deep levels, and the least backgating effect which makes it promising for IC fabrication. Comparison of the high pressure grown material from two suppliers showed that Cominco's recent material had good mobility, activation, relatively high scatter of threshold voltage, high concentration of deep levels, and was affected by backgating. In comparison, Sumitomo's material showed thermal instability, less scatter of threshold voltage, less mobility and deep level concentrations, and similar backgating characteristics. Substrate grown three years earlier showed higher diffusion of dopant, different deep levels, and better backgating characteristics. Finally, a substrate which had failed the qualification test by a device manufacturer showed minimal diffusion tails and threshold voltage scatter, the highest concentration of deep levels, and substantial backgating.
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 | 0,000 |
| 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 | 0,000 | 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 ».