Photo absorption enhancement in strained silicon nanowires: An atomistic study
Bibliographic record
Abstract
The absorption spectra of silicon nanowires are calculated using semi-empirical sp3d5s* tight binding and Density Functional Theory methods. The roles of diameter, wave function symmetry, strain, and crystallographic direction in determining the absorption are discussed. We find that compressive strain can change the band edge absorption by more than one order of magnitude due to the change in wave function symmetry. In addition, photon polarization with respect to the nanowire axis significantly alters the band edge absorption. Overall, the band edge absorption of [110] and [100] silicon nanowires can differ by as much as three orders of magnitude. We find that compared to bulk Silicon, a strained Silicon nanowire array can absorb infrared photons (1.1 eV) approximately one hundred times better. Finally, we compare a fully numerical and a computationally efficient semi-analytical method, and find that they both yield satisfactory values of the band edge absorption.
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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 | 0.000 |
| 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 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".