Dehydrogenative Silane Coupling on Silicon Surfaces via Early Transition Metal Catalysis
Bibliographic record
Abstract
Derivatization of silicon surfaces is an area of intense interest due to the centrality of silicon in the microelectronics industry and because of potential promise for a myriad of other applications. In this paper, we investigate the feasibility of Si-Si bond formation directly on the surface to contrast with the more widely studied Si-C and Si-O bond forming reactions. Functionalization of hydride-terminated silicon surfaces with silanes is carried out via early transition metal mediated dehydrogenative silane coupling reactions. Zirconocene and titanocene catalyst systems were evaluated for heterocoupling of a molecular silane, RSiH3, with a surface Si-H group on Si(s). The zirconocene catalysts proved to be much more reactive than the titanium system, and so the former was examined exclusively. The silanes, aromatic or aliphatic, are bonded to the silicon surface through direct Si-Si bonds, although the level of incorporation of the trihydroarylsilanes was substantially higher than that of the aliphatic silanes. The reaction proceeds on nanocrystalline hydride-terminated porous silicon surfaces, as well as flat Si(100)-H(x) and Si(111)-H interfaces. The reactions were studied by a variety of techniques, including FTIR, SIMS, and XPS.
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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".