Stress redistribution in individual ultrathin strained silicon nanowires: a high-resolution polarized Raman study
Bibliographic record
Abstract
Strain nano-engineering provides valuable opportunities to create high-performance nanodevices by a precise tailoring of semiconductor band structure. Achieving these enhanced capabilities has sparked a surge of interest in controlling strain on the nanoscale. In this work, the stress behavior in ultrathin strained silicon nanowires directly on oxide is elucidated using background-free, high-resolution polarized Raman spectroscopy. We established a theoretical framework to quantify the stress from Raman shifts taking into account the anisotropy associated with the nanowire quasi-one-dimensional morphology. The investigated nanowires have lateral dimensions of 30, 50 and 80 nm and a length of 1 μ m top-down fabricated by patterning and etching 15 nm thick biaxially tensile strained silicon nanomembranes generated using heteroepitaxy and ultrathin layer transfer. The concern over the contribution of Raman scattering at the nanowire 〈110〉 oriented sidewalls is circumvented by precisely selecting the incident polarization relative to the sidewalls of the nanowire, thus enabling an accurate and rigorous analysis of stress profiles in individual nanowires. Unlike suspended nanowires, which become uniaxially strained as a result of free surface-induced relaxation, we demonstrated that stress profiles in single nanowires are rather complex and non-uniform along different directions due to the oxide–nanowire interface. As a general trend, higher stresses are observed at the center of the nanowire and found to decrease linearly as a function of the nanowire width. Using multi-wavelength high-resolution Raman spectroscopy, we also extracted the stress profiles at different depths in the nanowire. The residual stress in the top ∼10 nm of the nanowire was found to be nearly uniaxial and increase from the edge toward the center, which remains highly strained. In contrast, the average stress profiles measured over the whole nanowire thickness exhibit different behavior characterized by a plateau in the region ∼200 nm away from the edges. Our observations indicate that the lattice near the newly formed free surface moves inwards and drags the underlying substrate leading to a complex redistribution of stress. This nanoscale patterning-induced relaxation has direct implications for electrical and mechanical properties of strained silicon nanowires and provides myriad opportunities to create entirely new strained-engineered nanoscale devices.
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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".