Second-harmonic and linear spectroscopy of <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"><mml:mrow><mml:mi>α</mml:mi><mml:mtext>−</mml:mtext><mml:msub><mml:mi>In</mml:mi><mml:mn>2</mml:mn></mml:msub><mml:msub><mml:mi>Se</mml:mi><mml:mn>3</mml:mn></mml:msub></mml:mrow></mml:math>
Bibliographic record
Abstract
We report spectroscopic measurements of optical transmission, ellipsometry, and second-harmonic generation (SHG) from as-grown vapor-deposited $\ensuremath{\alpha}{\text{-In}}_{2}{\text{Se}}_{3}$ nanoflakes ranging in thickness from a single quintuple layer (QL) to bulk material. We compare these measurements with ab initio calculations of structural and optical properties. Linear optical measurements yield thickness-dependent band gaps and dielectric functions, while SHG diagnoses microscopic film structure and ferroelectric polarization. The rotational anisotropy of SHG for $s$-polarized incident photons of energy $1.4\phantom{\rule{0.16em}{0ex}}\mathrm{e}\mathrm{V}$ reveals crystalline symmetry and orientation of individual QLs. Peak SHG intensity increases from one to three QLs, then decreases for larger numbers, tracking thickness-dependent trends in the second-order susceptibility components ${\ensuremath{\chi}}^{xxx}$ and ${\ensuremath{\chi}}^{zxx}$. Comparison of measured and calculated SHG spectra for $s$-polarized photons of energies between 1.2 and 1.7 eV incident upon two QL samples discriminates among candidate stacking arrangements, and favors an arrangement with electric polarization vectors of the two QLs pointing outward in opposite directions.
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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) | 0.003 | 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".