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Record W2610894537 · doi:10.1149/ma2017-01/27/1289

Effect of Boro-Silicate Glass (BSG) Gate Dielectric with Antimony Surface Doping on Channel Transport of 4H-SiC Mosfets

2017· article· en· W2610894537 on OpenAlexaff
Yongju Zheng, Tamara Isaacs‐Smith, A. C. Ahyi, P. M. Mooney, Sarit Dhar

Bibliographic record

VenueECS Meeting Abstracts · 2017
Typearticle
Languageen
FieldEngineering
TopicSilicon Carbide Semiconductor Technologies
Canadian institutionsSimon Fraser University
Fundersnot available
KeywordsMaterials scienceDopingOptoelectronicsThreshold voltageDielectricElectron mobilityMOSFETGate dielectricEpitaxyElectrical engineeringNanotechnologyVoltageTransistorLayer (electronics)

Abstract

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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

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How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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.

Opus teacher head0.011
GPT teacher head0.233
Teacher spread0.221 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

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".

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