Ideal Passivation of Luminescent Porous Silicon by Thermal, Noncatalytic Reaction with Alkenes and Aldehydes
Bibliographic record
Abstract
This paper describes the chemical modification of high surface area, photoluminescent porous silicon (PSi) by reaction at a moderately elevated temperature (<115 °C) with alkenes (RCH CH 2 ) and aldehydes (RCHO) to give organic monolayers covalently bonded to the surface through Si−C and Si−O−C linkages, respectively. The monolayers are characterized using diffuse reflectance infrared Fourier transform (DRIFT), transmission FTIR, Raman, X-ray photoelectron, and Auger spectroscopies. Auger depth profiling results are consistent with homogeneous incorporation of organic molecules on the internal surface of the PSi. The functionalized surfaces demonstrate high chemical stability in boiling aqueous and organic solvents and even in harsher environments such as aqueous HF or KOH. Aging in ambient air for several months has no effect on the PL intensity or energy. Notably, when the surfaces were treated at 100 percent humidity at 70 °C for 6 weeks, only a small increase in the PL intensity was observed. This severe treatment completely transformed H-terminated PSi into a transparent oxide layer. This result is consistent with the formation of organic films with a very low defect density at the interface. Thus, these organic monolayers have unprecedented stability and ideally passivate the PSi.
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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".