Characterization of Near-Interface Traps at Dielectric/SiC Interfaces Using CCDLTS
Bibliographic record
Abstract
Charge trapping at 4H-SiC/dielectric interfaces in 4H-SiC MOS capacitors has been investigated using constant capacitance deep level transient spectroscopy (CCDLTS). The experiments were focused on further understanding of the following aspects related to 4H-SiC/SiO 2 interfaces: (i) Origin of near interface oxide traps (NITs), (ii) Effect of interfacial impurity/passivation methods and (iii) Characterization of near-interface oxide traps for different SiC wafer orientations. For the (0001) Si-face 4H-SiC/ SiO 2 interface, two types of NITs are typically detected by CCDLTS, named ‘O1’ and ‘O2’ traps with emission activation energies of about 0.15±0.05 eV and 0.39±0.1 eV respectively below the 4H-SiC conduction band. Based on comparison with previous ab initio calculations, the physical identities of these defects have been suggested to be carbon dimers substituted for O dimers (‘O1’) and interstitial silicon atoms (‘O2’) in the near interfacial SiO 2 respectively. In this work, it is shown for the first time that such traps are not observed for 4H-SiC/ Al 2 O 3 interfaces, proving that these traps are inherent to the near-interfacial SiO 2 . In addition, the summary of CCDLTS results for Si-face with different interface trap passivation methods are included in this study. Finally, a comparison is presented for NO annealed (0001) Si-face, (11-20) a-face and (000-1) C-face interfaces that highlight the difference of CCDLTS signatures for the different crystal faces.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
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".