Nanotube Matrices for Flexible SnIP Nanowires
Bibliographic record
Abstract
A detailed density functional theory (DFT) study on 1D-SnIP@2D-material hybrids was conducted. Selected two-dimensional (2D) materials like carbon nanotubes (CNTs), MoS2, phosphorus allotropes (gray and black P), carbon nitrides, and boron nitride were tested as potential 2D hosts or matrices for a highly flexible, pseudo one-dimensional semiconductor SnIP. For a matrix, we selected sheets of the 2D materials rolled-up to nanotubes of 13.1 to 13.8 Å in diameter to accommodate one enantiomeric form of double helical SnIP. SnIP, an atomic-scale inorganic double helix compound, is composed of a racemic mixture of M- and P-double helices that form a pseudo-hexagonal rod packing in the bulk phase. Hybrid materials investigated in this study were classified based on total energy, the internal diameter of the matrix, and bonding interactions. Less-probable and most-probable hybrids were identified. With the hybrid SnIP@C6N8 (8,4), the first example was identified, which seems to allow separation of the M- and P-SnIP enantiomers due to significant differences in bonding interactions and overall fit. Differential crystal orbital Hamilton population analysis shows clear preference of M-SnIP over P-SnIP with a 31 kJ/mol stabilization in total energy for M-SnIP@C6N8. A vibrational mode analysis of all hybrids illustrates that the length of the propagation vector of the SnIP double helix directly correlates with a red shift of the SnIP phosphorus modes. As a proof of principle, a core–shell particle consisting of SnIP and hBN was successfully prepared and investigated.
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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) | 0.000 | 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".