Bibliographic record
Abstract
We built an atomically engineered laboratory inside a silicon nanowire (SiNW) to study fundamental transport mechanics and correlate results with crystal structure. We quantify the effects of ordered stacking faults (OSFs) present in SiNWs on their \nelectrical transport capabilities. We use Raman spectroscopy to characterize the hexagonal-phase core structure of the Si crystal in our novel nanowires caused by the OSFs. \nOur results indicate that electrical current is prevented from \nowing within the hexagonal-phase core. Using OSFs to tune crystal structure in SiNWs can be used to control the effective cross-section of the nanowire without the need to change its \nphysical dimensions. We find that the channel conductivity of field-effect transistors formed using these nanowires is decreased substantially compared to the familiar cubic phase counter-part (from roughly 100 to 1 mu*S/cm). This result indicates that modulating crystal phase can be effective in tuning material conductivity, offering an additional degree of freedom in device engineering. We also show that hexagonal-core SiNWs have larger \neffective Schottky barriers with gold electrode contacts (from 0.48 to 0.67 eV), which increases device contact resistance. \nHaving a cubic-phase portion and a hexagonal-phase portion in series within a single kinked SiNW exploits this barrier asymmetry to create excellent gate-controlled and temperature-dependent rectifiers with rectifying ratios exceeding 100. Our transport model explains how the kink region also acts as a 10-nm scale diode. \nThese results indicate that controlling OSF density could be exploited in new device architectures and help optimize SiNWs for applications in high-impedance Schottky barrier rectifying transistors.
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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 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| 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".