Hf1−xZrxO2 and HfO2/ZrO2 gate dielectrics with extremely low density of interfacial defects using low temperature atomic layer deposition on GaN and InP
Bibliographic record
Abstract
Achieving a negative capacitance field effect transistor with a subthreshold swing beyond the Boltzmann limit requires a “defect-free” dielectric-semiconductor interface. We grew alloyed (Hf1−xZrxO2) and stacked (HfO2/ZrO2) gate dielectrics on GaN and InP substrates using low temperature plasma enhanced atomic layer deposition. In situ ellipsometry data show that alloying hafnia with zirconia reduces the refractive index and widens the bandgap. The stacked and alloyed structures reveal very low capacitance-voltage hysteresis of 35 and 45 mV, respectively, on GaN. The density of interfacial traps as low as 1.12 × 1010 cm−2 eV−1 was achieved on GaN mainly due to the combination of very low dielectric growth temperature (100 °C) and high postfabrication heat treatment temperature (510 °C). The conduction and valence band offsets of the alloyed gate dielectrics on InP were measured and compared to pure zirconia using a combination of x-ray photoelectron spectroscopy and ellipsometry. The alloyed structures show a wider bandgap, larger conduction band offset, and smaller valence band offset compared to pure zirconia. This was attributed to the increase in the valence band width with hafnia addition, which reduces the alloyed gate dielectric’s valence band offset. We resolved the band structure alignement to be type I with band offsets of 3.53 eV for electrons and 1.03 eV for holes in Hf0.25Zr0.75O2/InP heterojunctions. The results allow for a clear and detailed picture of two distinct growth procedure that affect the interfacial defect concentration.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| 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 | 0.000 |
| 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 source (direct Gemma or distilled Codex), 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".