Wavelength-Controlled Etching of Silicon Nanocrystals
Bibliographic record
Abstract
A detailed investigation of the photochemical etching of silicon nanocrystals (Si-NCs) in aqueous hydrofluoric acid (HF) mixtures is described. By increasing the HF concentration and lowering the pH upon addition of hydrochloric acid (HCl), oxide-embedded Si-NCs were rapidly etched, and photoluminescence (PL) from the resulting hydride-terminated Si-NCs tailored from the near-IR to the yellow/green spectral region by irradiating the reaction mixture at the desired PL wavelength. These results are consistent with a hole-driven etching pathway rather than the chemically induced oxidation/etch pathway commonly exploited for Si nanostructures. The relationship among NC size, polydispersity, and PL was investigated using small-angle X-ray scattering. We suggest the defect density of Si-NCs is a crucial parameter for effective size control via photochemical exciton-mediated HF etching. Improved HF etching methods are expected to enable Si-NC applications through the realization of narrow polydispersity and PL bandwidth.
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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) | 0.001 | 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".