Carbon nanotube alignment and sorting: Attempting a sulfur moiety as anchoring component
Bibliographic record
Abstract
Previously, the Schipper group established a method for simultaneously sorting and aligning single walled carbon nanotubes using an alignment relay technique (ART) with molecule 1. Here, further synthetic investigations were pursued to explore another anchoring group and expand functionalization onto different surfaces, in particular for gold substrates. A thiophosphonate moiety (2) is attempted as a substitute for the phosphonate ester on 1 as sulfur has been shown to efficiently chemisorb onto gold surfaces and could make an interesting substrate pursuit for better carbon nanotube alignment. For 2 – it has potential to be obtained through the use of Lawesson’s reagent, although currently the synthesis here failed to demonstrate isolation of the compound. Therefore, additional screening for different intermediate sulfur aligning molecules was also conducted, as to improve the density along side molecule 1 for ART applications. Outcomes are compared with the results on gold surfaces yielding from 1 to establish if more or fewer nanotubes are present on the surface in a horizontally aligned manner with respect to one another. Orientation is characterized via atomic force microscopy and chiralities of the nanotubes are observed via Raman spectroscopy.
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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 | 0.001 | 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".