Unmasking Fluorinated Moieties on the Surface of Hydride-Terminated Silicon Nanoparticles
Bibliographic record
Abstract
Despite the widespread use of hydrofluoric acid (HF) in the preparation of silicon surfaces, the true nature of fluorinated surface species remains unclear. Here, we employ an array of characterization techniques led by solid-state nuclear magnetic resonance spectroscopy to uncover the nature of fluorinated moieties on the surface of hydride-terminated silicon nanoparticles (H-SiNPs). A structural model that explains the observed trends in 19 F and 29 Si magnetic shielding is proposed and further supported by quantum chemical computations. Fluorine is incorporated into local oxidation domains on the surface and clustered at the interface of the oxide and surrounding hydride-terminated surface. Silicon sites capped by a single fluorine are also identified by their distinct 19 F and 29 Si chemical shifts, providing insight into how fluorine termination influences the electronic structure. The extent of fluorine passivation and the effects of fluorine on the optical properties of SiNPs are also discussed. Finally, challenges associated with Teflon contamination are highlighted that future explorations of nanomaterials may have to contend with.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.001 | 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 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".