Low-Temperature Self-Aligned-Silicide-Capable Transistor Process Using Solid-Phase-Epitaxy and Lift-Off for Hybrid Substrates
Bibliographic record
Abstract
Details of a large-area-compatible sub-600 °C process for the fabrication of high mobility field-effect transistors on single crystalline silicon are presented. It is shown that lift-off and solid-phase-epitaxy (SPE) can be used in conjunction with plasma enhanced chemical vapor deposition (PECVD) to create MOSFET transistors with mobilities comparable to other high-performance techniques. Furthermore, use of an amorphous silicon/silicon oxynitride (SiOxNy) sacrificial bilayer is shown to make the process capable of self-aligned silicidation. The topography of the deposition is studied using cross-sectional scanning electron microscopy (SEM). It is shown that a successful lift-off can be achieved through the proper design of the sacrificial bilayer despite the high degree of step coverage generally exhibited by PECVD films. Cross-sectional transmission electron microscopy (TEM) is used to reveal the microstructure of the epitaxy and silicidation. Current-voltage characteristics of the fabricated transistors are presented and the field effect mobility of electrons on the fabricated devices is reported. The developed process is particularly useful in applications where high mobility transistors need to be built on silicon/nonsilicon hybrid platforms that exclude high processing temperatures.
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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 | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".