Effect of Boro-Silicate Glass (BSG) Gate Dielectric with Antimony Surface Doping on Channel Transport of 4H-SiC Mosfets
Notice bibliographique
Résumé
In this work, we investigate the effect of Boro-silicate glass (BSG) gate dielectric in conjunction with Antimony (Sb) surface doped channels of lateral 4H-SiC MOSFETs. It has been reported that BSG gated 4H-SiC MOSFETs have a high channel mobility of ~100 cm2/V∙s for a wide range of surface transverse electric fields along with a large threshold voltage VT of ~5V in lightly doped p-epitaxial layers [1,2]. For vertical power MOSFETs with heavily doped p-wells, it is expected that BSG would cause an even further increase of VT (~10 V) which would be undesirable. Therefore in this work, our goal for combining the Sb surface doping process (demonstrated in our earlier works [3,4] and presented at ECSCRM 2014 [4]), with BSG gate dielectric was two-fold: (i) Tune VT to adequate value with high sub-threshold slope. (ii) Achieve high low-field channel mobility by Sb counter-doping while retaining the high-field mobility characteristics of BSG. The results from our experiments indicate that these goals were achieved. The 'Sb+BSG' process results in significant improvement of both low-field channel mobility to ~180cm2/V∙s (due to addition of Sb surface doping) and high-field channel mobility to ~90 cm2/V∙s (due to the BSG gate dielectric) along with a tuned threshold voltage of ~2V and a steeper sub-threshold slope. Lateral MOSFETs were fabricated on the Si-face of p-type 4H-SiC epitaxial layers doped at ~1x1016cm-3. Sb was implanted in the channel region with 80 keV at room temperature with dose of 2.5x1013cm-2, which results in a Gaussian profile with a depth of around 30nm below the surface of SiC. This was followed by post-implantation activation annealing at 1650°C using a graphitic carbon cap layer. Next, dry oxidation at 1150°C for 10 hours was performed followed by post-oxidation annealing using a planar diffusion source (Techneglas, GS-139) composed of boric oxide (B2O3) in a gas mixture of Ar (50sccm) and O2 (5sccm) at 950°C for 30 mins. Samples that received only boron annealing are referred to as 'BSG only' and samples underwent both Sb counter-doping and boron annealing are referred to as 'Sb+BSG'. Results for these samples are compared with standard NO-annealed devices in Table Ⅰ. The SIMS result in Fig. 1 shows B distributes throughout the oxide with a concentration of ~1x1022cm-3 and decreases as it reaches SiC. Threshold voltage and sub-threshold slope were characterized by Id-Vg measurement at room temperature and field-effect mobility was extracted from the transconductance of Id-Vg curve. Linear and log scale of Id-Vg curves in Fig. 2 and Fig. 3 demonstrate that 'Sb+BSG' tunes the threshold voltage to a more desirable value of ~2V along with a better sub-threshold slope than standard NO annealing. Fig. 4 shows a significant mobility improvement for 'Sb+BSG' at both high field due to the BSG passivation effect and low field due to the Sb counter-doping effect with a peak value of ~180cm2/V∙s compared to 'BSG only' with a peak mobility of ~140cm2/V∙s. In order to investigate the boron passivation effect on interface traps, C-V and constant capacitance deep level transient spectroscopy (CCDLTS) measurements were performed on the companion BSG capacitors. The interface trap density of 'NO' was determined to be ~2.5 times higher than that of 'BSG' for very shallow energy traps (<0.2 eV) from C-V measurements and ~1.5 times higher for the energy trap distributions centered at 0.15 eV and 0.39 eV by CCDLTS, as shown in Figs. 5 and 6. The mechanism of boron passivation has been suggested to be oxide stress relaxation by the reduction of required oxygen bonds due to the occupation of Si site by B [5]. In this presentation, further details of the nature of transport and mobility behavior in BSG gated channels will be presented as a function of temperature. References [1] D. Okamoto, M. Sometani, S. Harada, R. Kosugi, Y. Yonezawa, and H. Yano, IEEE Electron Device Lett. 35, 12 (2014). [2] T. Isaacs-Smith, Y. Zheng, C. Jiao, A. C. Ahyi, and S. Dhar, 2016 MRS Spring Meeting & Exhibit, Phoenix, Arizona, 4 (2016). [3] A. Modic, G. Liu, A. C. Ahyi, Y. Zhou, P Xu, M. C. Hamilton, J.R Williams, L. C. Feldman, and S. Dhar, IEEE Electron Device Lett.35, 894 (2014). [4] A. C. Ahyi, A. Modic, C. Jiao, Y. Zheng, G. Liu, L. C. Feldman, and S. Dhar, Materials Science Forum, Vols. 821-823, (2015) pp. 693-696. [5] Xiao Shen, and Sokrates Pantelides, 11th annual SiC MOS workshop meeting, UMD College Park, August 15, 2016. Figure 1
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 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) | 0,000 | 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) | 0,001 | 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 ».