Phonon Engineering in Isotopically Disordered Silicon Nanowires
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Bibliographic record
Abstract
The introduction of stable isotopes in the fabrication of semiconductor nanowires provides an additional degree of freedom to manipulate their basic properties, design an entirely new class of devices, and highlight subtle but important nanoscale and quantum phenomena. With this perspective, we report on phonon engineering in metal-catalyzed silicon nanowires with tailor-made isotopic compositions grown using isotopically enriched silane precursors (28)SiH4, (29)SiH4, and (30)SiH4 with purity better than 99.9%. More specifically, isotopically mixed nanowires (28)Si(x)(30)Si(1-x) with a composition close to the highest mass disorder (x ∼ 0.5) were investigated. The effect of mass disorder on the phonon behavior was elucidated and compared to that in isotopically pure (29)Si nanowires having a similar reduced mass. We found that the disorder-induced enhancement in phonon scattering in isotopically mixed nanowires is unexpectedly much more significant than in bulk crystals of close isotopic compositions. This effect is explained by a nonuniform distribution of (28)Si and (30)Si isotopes in the grown isotopically mixed nanowires with local compositions ranging from x = ∼0.25 to 0.70. Moreover, we also observed that upon heating, phonons in (28)Si(x)(30)Si(1-x) nanowires behave remarkably differently from those in (29)Si nanowires suggesting a reduced thermal conductivity induced by mass disorder. Using Raman nanothermometry, we found that the thermal conductivity of isotopically mixed (28)Si(x)(30)Si(1-x) nanowires is ∼30% lower than that of isotopically pure (29)Si nanowires in agreement with theoretical predictions.
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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 | 0.000 |
| 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 it